WPS8210 Policy Research Working Paper 8210 Information Disclosure and Demand Elasticity of Financial Products Evidence from a Multi-Country Study Xavier Giné Cristina Martínez Cuellar Rafael Keenan Mazer Development Research Group Finance and Private Sector Development Team October 2017 Policy Research Working Paper 8210 Abstract This study tests the effectiveness of behavioral-based dis- using brochures and −3.19 using the simplified KFS, with closure formats. Around 1,700 individuals from Mexico smaller effects for savings products. Finally, while financial and Peru chose among loans and savings accounts pre- literacy is correlated with better decision-making, the effect sented in different formats, including a simplified key of the disclosure format for loans is about three times as facts statement (KFS) and current marketing brochures. large as that of financial literacy. More importantly, the The study finds that the price elasticity of loans is −1.04 KFS helps financially illiterate individuals relatively more. This paper is a product of the Finance and Private Sector Development Team, Development Research Group. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at xgine@worldbank.org. The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent. Produced by the Research Support Team Information Disclosure and Demand Elasticity of Financial Products: Evidence from a Multi-Country Study∗ Xavier Giné Development Economics Research Group, World Bank Cristina Martínez Cuellar Citibank Rafael Keenan Mazer CGAP, World Bank Keywords: financial information, disclosure, lab experiment. JEL codes: C91, D14, D83, G18, G21, O16.  Giné: xgine@worldbank.org; Martínez: cristinam@chicagobooth.edu Mazer: rmazer@worldbank.org. We thank Leyla Castillo and Marianna Camino from the World Bank, CONDUSEF in Mexico and the Superintendencia de Banca, Seguros y AFP (SBS) in Peru and in particular, Luís Daniel Allain Cañote, Daniel Bouroncle, Jesús Chavez Ugalde, Isis Marín, María Fernanda Saldivar Cortes, and Mariela Zaldivar Chauca for their constant encouragement and support. We also thank the team at Berumen and IPA for data collection and to Ildrim Valley and Bernardo Ribeiro for superb research assistance. In addition, Luís Daniel Allain Cañote and Jesús Chavez Ugalde provided valuable help with the calculations of key terms. We gratefully acknowledge financial support from SECO and KCP. The views expressed in this paper are those of the authors and should not be attributed to the World Bank, its executive directors, or the countries they represent. 1. Introduction Many consumers in financial markets find out about the characteristics of products exclusively from providers, even when their staff has better information about the cost of the product and the incentives between customers and staff are misaligned. It is thus important to ask whether firms are successful at providing information and ultimately, whether consumers are well-informed. Two crucial pieces of evidence, however, should give us pause. First, financial markets are characterized by substantial price dispersion (see, for example, Hortaçsu and Syverson, 2004, Stango and Zinman, 2016, Giné and Mazer, 2017 and Zinman, 2015 for a review).1 While the variation in prices may be driven by riskiness or the transaction costs involved in servicing different customers, Stango and Zinman (2016) and Giné and Mazer (2017) find that the same individuals in the same months are offered credit cards and credit or savings products, respectively, with substantially different interest rates. Second, there is little comparison shopping, even when customers face substantial price dispersion. Woodward and Hall (2012), for example, show that mortgage borrowers overpay at least USD 1,000 by shopping from too few brokers. In rational search models, consumers expand their choice set up to the point where the benefit of doing so is equal to its cost. But even when choices are provided at no additional cost, comparison frictions may still cause consumers to place more weight on non-financial factors like brand loyalty or non-professional advice from friends and family to the detriment of the cost of the product (Bertrand et al., 2010). In addition, the decision of which product to contract may involve unfamiliar concepts especially to individuals with limited financial capabilities (Lusardi and Mitchell, 2011, 2014) and as a result, financial consumers may not necessarily choose the most cost-effective product or the one most suitable to their needs (see for example, Gross and Souleles, 2002; Choi et 1 Table 1 in Giné and Mazer (2017) reports summary statistics for estimated costs and yields of credit and savings products, respectively, offered by a sample of financial institutions in Mexico and Peru. The total annual cost of credit including usage fees ranges from 22.1 percent in Peru to over 225 percent in Mexico. The total annual yield of a transaction account also including usage fees ranges from -14.5 percent in Mexico to 0.8 percent in Peru. 2 al., 2011; Duarte and Hastings, 2012; Hastings et al., 2013; Agarwal et al., 2013, 2015 and Campbell et al., 2011 and DellaVigna, 2007 for reviews). Governments and academics have focused on financial education as a tool to improve financial wellbeing, but the efficacy of these initiatives is mixed (for example, Cole and Shastry, 2010; Cole, Sampson, and Zia, 2011; Bruhn, Ibarra, and McKenzie, 2014; Lusardi and Mitchell, 2014, and Fernandes et al., 2014). As an alternative to educating financial consumers, governments around the world have tried to encourage comparison shopping by introducing legislation to improve disclosure and transparency. An early example of mandated financial disclosure is the Truth in Lending Act of 1968 which required that consumers in the U.S. be presented with key financial terms for credit products, and standardized the calculation of certain key product terms and disclosure formats. Peru and Mexico introduced similar disclosure laws in 2005 and 2009, respectively. As noted by Campbell et al. (2011) and Loewenstein et al. (2014), effective information disclosure should mitigate asymmetric information, reduce search costs and encourage competition. But if consumers do not understand the information, its effectiveness will be limited as they may believe that it is not relevant to their decision making, or do not know how to use it. In a speech given in 2007, then governor Krozner stated that “effective disclosures give consumers information they notice, understand, and can use.” From a political economy perspective, mandated disclosure laws are easy to enact because they only require the provision of information leaving the actual products unregulated (Sunstein, 1999). The fact that large price dispersion still persists, however, indicates that these efforts may not have been successful (see for example Weil et al., 2006 or Lowenstein et al., 2014). While disclosure regulation dictates what terms should be disclosed and how they should be calculated, the actual design of the forms is typically left to the financial providers. Their interests, however, do not necessarily coincide with those of consumers and thus, formats are difficult to understand and not easily comparable. Online Appendix 3 OA4 contains two examples of market-designed key facts statements in Peru.2 The APR, for example, appears around the center in the 10th row for one institution but in the top left corner for the other. Other terms also appear in different places, making the comparison between both products difficult. This study seeks to understand the role of disclosure formats in facilitating comparison shopping for savings and credit products by low-income consumers in Peru and Mexico. These countries were chosen because they both have similar levels of financial access but have de jure regulations with different transparency requirements. According to the market conduct index published by the Economist Intelligence Unit’s 2014 Global Microscope Index and Report, Peru is ranked second while Mexico is ranked 25th (middle of the sample of countries).3 We implement a laboratory experiment in which low-income consumers were assigned a profile and then incentivized to choose the product that best fit their needs from among 5 or 10 products. In each round of decision-making, information about the products was presented in a different format, including current marketing materials gathered from financial institutions during sales visits by actual consumers and a simplified key facts statement (KFS) designed using behavioral insights to facilitate comparison shopping. Our results show that the simplified KFS with its standardized format significantly improves consumer decision-making compared to the marketing materials currently provided by financial institutions. The effects are however much stronger for credit than savings products. The probability of choosing the cheapest loan increases from 42 percent using the marketing materials to 65 percent using the simplified KFS but it only increases from 32 percent to 34 percent for savings accounts. One reason is perhaps that individuals may not care about the total yield of the savings account and focus instead on other characteristics. After all, a consistent finding from the literature on savings is that 2 A product key facts statement (KFS) is a document that provides concise information of the key features and risks of a financial product. 3 Market conduct includes indicators of the capacity to protect the financial consumer, the content of disclosure rules, the disclosure of product terms, pricing information and non-discrimination in the financial service provision. 4 the behavioral response to changes in the price of saving is not large (see Hastings et al., 2013 for a review). Alternatively, subjects evaluating savings products may not have had enough information as the lack of impact is concentrated in Mexico where the simplified KFS did not contain the total yield earned by the savings account. We also find that transparency increases price elasticity. The price elasticity of credit products is -1.04 using brochures and -3.19 using the simplified KFS, that is, about three times as large. For savings products, the price elasticity is 0.02 using brochures and 0.03 using the simplified KFS, and the difference is not statistically significant. In addition, non-price factors such as the (random) order in which savings products are presented to consumers matter more when brochures are used rather than simplified KFS, consistent with the idea that transparency allows individuals to focus on the price. Finally, we show that financial education is correlated with better financial decision-making, but for credit products, the effect of the disclosure format is about three times as large as that of the effect of financial literacy. More importantly, the simplified KFS is particularly useful to financially illiterate individuals as financial literacy increases the price-elasticity of credit products by 58 percent when using brochures but only by 7 percent when using the simplified KFS. These results, therefore have relevant implications for how government-mandated information should be presented and its potential to influence choices and competition in consumer finance markets. This paper contributes to the literature in household finance and other fields that study the impact of disclosure regulations in various consumer markets (see Ben-Shahar, 2011 and Dranove and Jin, 2010 for a review). The evidence on the effectiveness of disclosure regulations is mixed, and because there may be factors other than the disclosure regime that change at the same time, it is hard to attribute changes in behavior to the disclosure regulation alone. In contrast, in our controlled setting the same subjects make decisions using the same information presented with a different format, allowing us to make causal statements about the effectiveness of the disclosure treatment. Our evidence comes from the laboratory rather than the field. The advantage is that subjects are rewarded to pay attention when making decisions. This increases our 5 statistical power considerably and may explain the magnitude of the price elasticities found.4 The disadvantage is that the environment may be artificial as individuals typically face competing demands on their time and attention when making decisions. In the field, complexity can lead to inaction, as shown by Bettinger et al. (2012) in the context of college financial aid applications, by Hastings and Weinstein (2008) that study school choice and by Barghava and Manoli (2015) that study benefits of simplification in the take-up of the Earned Income Tax Credit. More related to our context, in Adams et al. (2016), for example, holders of low-yielding savings accounts were given information about higher-rate paying products, a form that enabled simplified switching and a reminder about their low rate. About 90 percent of study participants failed to take any action when it was in their interest to do so. Perhaps more troubling, they did not even recall receiving or reading such information. Similarly, Ponce et al. (2017) find muted effects from information disclosures in the Mexican credit card market. Another advantage of field experiments is that they allow researchers to observe not only consumer responses, but also how firms respond to greater disclosure requirements. Duarte and Hastings (2012) evaluate a change in government disclosure in Mexico’s privatized social security system and find strong evidence that firms find ways to undermine the effects of disclosure reform by altering their fee structures. Anagol and Kim (2012) also find evidence that firms respond to disclosure policy by altering products to maintain lack of clarity in pricing.5 The paper finally contributes to the literature documenting consumer financial mistakes and the role of disclosures in preventing them. Hastings and Tejada (2008) show that presenting the cost of a financial product in amounts instead of percentages allows people to choose better products and to focus on other characteristics like fees. Thus, echoing the findings here, minor changes on how information is presented can have significant effects on decision-making. Related, Bertrand and Morse (2011) show that 4 Beshears et al. (2013) and Choi, Laibson, and Madrian (2010) also conduct laboratory experiments that vary the presentation of investment fees while holding other fund characteristics constant to test whether making fees less shrouded changes fund choice; both studies find however, little evidence to suggest that changing the framing of fees has a large impact on investor decisions. 5 For evidence of responses to disclosure from another industry see Newell et al. (1999) for purchases of appliances. 6 disclosing the cumulative costs of payday loans in amounts (rather than percentages) significantly reduces the demand of such loans. The remainder of the paper is organized as follows. Section 2 presents the experimental design and the different treatments; Section 3 reports the empirical strategy, Section 4 presents the results and Section 5 concludes. 2. Experimental Design Individuals from around the capital city of Peru and Mexico were invited to participate in the experiment to test different disclosure forms. During recruitment, individuals were told that they would earn money making decisions but no details were provided about the nature of the decisions. Experimental sessions were conducted in 2013 in Mexico and 2017 in Peru. They took place in a room set up in a way to ensure that communication between subjects was not possible. A total of 600 subjects in Peru and 1,071 in Mexico participated in 57 sessions (10 sessions for each product in Peru and 20 and 17 for credit and savings, respectively, in Mexico), with around 30 subjects per session (see Table 1 for details). Prior to the sessions, a subset of participants in Mexico received SMS and live calls with tips about the terms that were important for financial decision-making. In particular, prospective participants in credit sessions were told to verify the total amount to be paid, including interest payments, commissions and insurance premia. Participants of savings sessions were told to choose the accounts offering the highest yield. Online Appendix OA2 contains the scripts to the live calls and the text of the SMS. While there is an extensive literature on messages as reminders (see, for example, Karlan et al., 2016) here we test messages as a way to disclose information. Subjects only participated in one experimental session that lasted between 1.5 and 2 hours. Each session started with a 20-minute survey, then three rounds of decision- making in Peru and 5 in Mexico where subjects were instructed to choose the product that best fit their needs, followed by an end-of-session survey. The initial survey included questions on demographic characteristics, knowledge and preferences of financial institutions, factors that affect subjects’ financial decisions, and financial literacy. 7 Table 2 presents the characteristics of participants. Participants were stratified by gender and they vary by education and occupation. Although Mexico is a richer country, the Peruvian sample has a lower proportion of low-income participants (NSE C- or D). For this reason, monthly household income is slightly higher in Peru (USD 641 in Mexico compared to USD 783 in Peru) and participants seem on average more educated. Participants in Peru are also more familiar with financial institutions and report higher ownership of savings accounts and credit cards. In addition, less than one-third of participants in Peru report comparing more than one product when they last contracted a savings account or loan. When we correlate a dummy for comparing different products against individual characteristics we find that richer individuals (as per their socioeconomic status), those with internet at home and those that are familiar with banks are more likely to engage in comparison shopping.6 While more than half tend to view the staff and marketing materials as the primary source of information about financial products, less than 15 percent of participants in either country is familiar with a key facts statement. These individuals appear to be poorly equipped when deciding among financial products (Lusardi and Mitchell, 2011) and thus are good candidates for the focus of this study. We note that there is within country variation in the levels of education and financial literacy, a feature that we will exploit later when comparing the difference in the probability of choosing the right financial product for a given participant facing different disclosures designs to that of participants with different levels of financial literacy facing a given format. Online Appendix Table OA1 regresses our preferred proxy for financial literacy, which takes value 1 if the participant answered a question about interest rate correctly, against other individual characteristics.7 Not surprisingly, for the pooled sample in column 3 financial literacy is correlated with household income, education and usage of financial products. It is also correlated with 6 Data on product comparisons were only collected in Peru and therefore are not reported in Table 2. 7 The interest rate question used is a simplified version of the one from Lusardi and Mitchell (2011): “If you deposit 100 pesos / soles in a bank account that charges you nothing and guarantees you a yield of 2% per year, how much would there be in the account by the end of the year, if no deposits or withdrawals are made?” Possible answers are: (a) Over 102. (b) Exactly 102. (c) Less than 102. (d) I don’t know. (e) I prefer not to answer. Lusardi and Mitchell (2011) use the timeframe of 5 years instead of one year. 8 being a male, although it is not always him who makes financial decisions in the household. Following the survey, the experimenter explained the rules for decision-making to all participants in Spanish. In each decision-making round, subjects were first provided with a sheet to mark their decisions. They then were given 10 minutes to record the three best products on the sheet.8 Sheets were then collected after each round by an assistant and inputted into a computer to calculate payouts for the round. After the end-of-session survey, subjects were paid a show-up fee of 200 pesos (USD 16) in Mexico and could win 100 pesos (USD 8) more depending on the number of correct answers. In Peru, they were paid similar amounts using a voucher for a family meal in a popular fast food restaurant. 2.1 Task In each round, subjects received information about 5 or 10 products, each offered by a different institution. The terms of each product were simulated using the dispersion of values in the market. No pair of participants received the same combination of products. Participants were instructed to choose the best product in accordance to a profile randomly assigned to them at the beginning of the session.9 Half of the participants were randomized into one profile and the other half into the other. In credit sessions, all participants were told that they were going to acquire a 12-month loan with monthly installments of 10,000 pesos (USD 800) in Mexico and 1,500 Peruvian soles (USD 450) in Peru. In Mexico there was only one profile that mentioned that every monthly installment was made on time. In Peru, half of the participants were randomized into another profile where all monthly installments but one were paid on time. Put differently, there was one missed installment but paid in full in the next installment. In savings sessions, participants were told that they had a fictional endowment to be deposited into a savings account of 1,000 Peruvian soles (USD 300) in Peru and 5,000 8 We believe that 10 minutes was enough to make decisions without pressure. Typically, participants completed the sheet with few minutes to spare. 9 For credit, the best product is the one that yields the least total cost; for savings, the product with the highest net yield. 9 pesos (USD 400) in Mexico. Savings Profile 1 mentioned that each month participants would make two deposits and two withdrawals of 100 Peruvian soles (USD 30) in Peru and 250 pesos (USD 20) in Mexico each and two balance inquiries at a teller of the financial institution. Savings Profile 2 in Mexico had no monthly activity, while in Peru it was similar to Savings Profile 1 in that one transaction (withdrawals, deposits and balance inquiries) would be made instead of two. The balance inquiry would be made at an ATM instead of at a teller. 2. 2 Treatments In recent years, both Mexico and Peru have developed a regulatory framework to supervise and promote the use of financial services. Mexico enacted a law similar to the U.S. Truth in Lending Act of 1968 in 2009 that also requires financial providers to disclose the APR and APY. Peru enacted disclosure regulation in 2005 and in 2012, which, similar to the regulatory financial transparency regime in Mexico, also defines the criteria for the determination and definition of interest rates, fees, charges and yields – including methods for calculating the total effective costs and rates for credit and savings products. Current regulation requires financial institutions to disclose information to consumers through brochures, key facts statements, webpages, ATMs, and verbally at the branches. While disclosure regulation of most countries dictates what terms should be disclosed and how they should be calculated, the actual design of the forms is typically left to the financial providers. The goal of the experiment is to test alternative disclosure formats to the ones developed by the financial industry. Each session in Peru had three rounds and in Mexico 5 rounds, each with a different disclosure format. In Peru, the first disclosure treatment used marketing materials such as brochures, amortization tables, and simulations that were offered to 10 prospective clients when shopping for financial products at the time of the experiment.10 These materials combined pictures with information about the terms, but each institution had its own design, making comparisons across similar products difficult. The second disclosure treatment used key facts statements (KFS) that institutions were required to give customers after contracting a product. The SBS regulated the minimum number of terms that had to be disclosed, but the design and whether to show the terms in fine print was left to the financial institution. As a result, these market-designed KFS had different layout of information, again making comparisons across products difficult. The third and final disclosure format used a standardized key facts statement designed jointly by SBS and us. This format presents the more relevant information in the top right corner using a large font and because the information is standardized, a given term will always be in the exact same place for every institution thus facilitating comparability. In Mexico, the first disclosure treatment also used brochures. The second disclosure treatment used a standardized key facts statement designed jointly by CONDUSEF and us that is similar to the standardized KFS used in Peru. The remaining treatments used comparative tables with either 5 or 10 products that varied the number of financial terms presented. The complex treatment presented information for 5 products with 8 terms for credit and 12 terms for savings (Complex 5). The simple treatment also presented information for 5 products, but with 4 terms for credit and 3 terms for savings (Simple 5). Finally, the long, simple treatment presented the same terms as the Simple 5 treatment just described but provided information about 10 different products (Simple 10). Online Appendix OA4 contains examples of all the disclosure formats used in the experiment. The order in which formats were presented to participants was randomized in each session to avoid learning effects. Given the objective of comparing the performance of different formats, all materials had to have key information about the APR / YPR and user fees to make the informational content comparable across formats. This meant that terms of the product had to be added to the materials if these were missing in the original one, which was typically the case for brochures. 10From all the marketing material collected by CONDUSEF and SBS, we chose the 5 materials with the highest amount of information about the product. 11 3. Econometric Analysis To examine the effectiveness of different disclosure formats for loans and savings products, we first look at the impact of the different formats on the probability of choosing the best product. We run logit regressions using data from Peru and Mexico separately and then combined. For Peru we use the following specification: ′ ℎ = + 1 + 2 + 3 + + (1) where ℎ is a dummy variable that takes value 1 if participant i in round j and session k chose the cheapest credit product or the savings product with highest yield given the profile assigned. and are dummy variables that take value 1 if participants in round j and session k were given the standardized KFS or the market- designed KFS, respectively. The omitted treatment is the one that uses marketing materials such as brochures. takes the value of 1 if participant i in session k was assigned to Profile 1 described in the previous section. The vector of characteristics includes whether participant i in session k is a male, whether he or she has post- secondary education, age and age squared (divided by 100) and our proxy for financial literacy. All specifications include round fixed effects and standard errors are clustered at the participant-session level. In Mexico, selected participants received either a phone call or a series of SMS messages on behalf of CONDUSEF one or two days prior to participating in the experiment. These phone calls and text messages contained simple information on key financial terms that were used in the disclosure formats and would help participants select the best product. Online Appendix OA2 contains the scripts of the calls and messages. In addition, we follow the literature (Hasting and Tejada, 2008; Gigerenzer et al., 2003 and Shu and Townsend, 2010) and varied whether the total amount to be paid for the loan or the total amount earned in the savings accounts was displayed in peso amounts or in percentages. In particular, the marketing brochures and the simple table with 5 products had the total amount in peso amounts for participants with an even-numbered ID and in 12 percentage values for participants with odd-numbered IDs. In contrast, the complex table and simple table with 10 institutions were presented in peso amounts for participants with odd-numbered IDs and in percentage terms for participants with even-numbered IDs. The simplified KFS designed by us with CONDUSEF always displayed the total amount to be paid or earned in peso amount. This way, the same individual was presented with the total amount to be paid (credit products) or earned (savings products) in peso amounts or percentages depending on the format. Finally, a glossary explaining key financial terms was distributed in half of the sessions. Table 1 reports the number of participants who received the glossary and the messages or calls. Given these interventions, we use the following specification for Mexico: ℎ = + 1 + 2 + 3 5 + 4 10 + 5 + 6 + 7 + 8 + 9 + ′ + (2) where , , 5 and 10 are dummies that take value 1 if participants received the respective treatment in round j of session k. The omitted treatment is again the one that uses marketing materials such as brochures. is a dummy variable that takes the value 1 if participant i in round j of session k saw the total amount to be paid (credit product) or earned (savings product) displayed in pesos and 0 if in percentages. is a dummy indicating that participant i was provided with a glossary of terms during session k and 0 otherwise and / takes the value of 1 if participant i received a call / SMS prior to session k and 0 otherwise. We finally pool the data from both Peru and Mexico and run the following regression: ′ ℎ = + 1 + 2 + + (3) In this pooled specification, we include country fixed effects and keep only the treatments that are common in both countries, namely the simplified format and brochures. 13 Because individuals ranked the choice of three products, we can also run a rank- order logit specification that includes the total cost of the credit product or the total yield in case of a savings product. This specification is ideal to assess the price sensitivity across treatments by interacting the price variable (cost of loan or yield of savings account) with the treatment dummies. In addition, we can also assess how financial literacy affects price sensitivity across treatments. Using data from Peru we run the following specification: = + 1 + 2 + 3 ∗ + 4 ∗ + 5 ∗ ∗ + 6 + 7 ∗ + 8 ∗ ∗ + (4) where takes value 3 for the first choice of individual i in round j in session k, 2 for the second choice and 1 for the third choice. is either the total cost of the loan or total yield of a savings product chosen in order c by individual i in round j in session k. is a proxy for financial literacy of individual i in session k that takes value 1 if the individual correctly answered the question on interest rate. Finally, and denote the market-designed and simplified KFS. Using data from Mexico, we run: = + 1 + 2 + 3 ∗ + 4 ∗ + 5 ∗ ∗ + 6 + 7 ∗ + 8 ∗ ∗ + 9 5 + 10 5 ∗ + 11 5 ∗ ∗ + 12 10 + 13 10 ∗ + 14 10 ∗ ∗ + (5) where , , 5 and 10 are treatment dummies defined before. Finally, we pool data from both countries and run: = + 1 + 2 + 3 ∗ + 4 ∗ + 5 ∗ ∗ + (6) Standard errors for all specifications are calculated using bootstrap and clustered at the participant level. 14 We can also use a ranked-order logit specification to investigate whether certain treatments make individuals more likely to rely on non-financial factors like brand loyalty or the (random) order in which products were received in detriment to the cost of the product (Bertrand et al., 2010). We run the following specification using pooled data = + 1 + 2 + 3 + 4 ∗ + 5 ∗ + (7) where takes value 1 if product chosen in order c by participant i in round j of session k was among the first half of the products given in a round or was shown in the upper half of a comparative table in Mexico. is another dummy that takes value 1 if the participant had or had ever had a financial product from the institution of the product chosen in order c. 4. Results Table 3 reports the coefficients from regressions in (1) (in columns 1 and 4) in (2) (in columns 2 and 5) and in (3) in columns 3 and 6. The dependent variable is a dummy that takes value 1 if the individual chose the best product. Columns 1 to 3 (4 to 6) report the results for credit (savings) sessions. In all regressions, the first rows show the coefficients associated with the disclosure treatments followed by the coefficient for the profile dummy and the participant characteristics. The table also reports the mean of the dependent variable for the omitted disclosure treatment (marketing materials) and the p- value of a t-test that two different disclosure treatments are equal. Column 1 of Table 3 shows the results for credit sessions in Peru. The simplified KFS increases the probability that individuals chose the right loan product by 12.6 percentage points relative to the brochures (and other marketing materials) and it is significant at the 1 percent level. In contrast, KFS designed by financial institutions do not significantly improve decision-making relative to brochures. The p-value associated with the t-test that the coefficients on both disclosure treatments are equal is 0. The coefficient associated to the profile is also not significant, suggesting that individuals are equally able to choose the best loan product regardless of whether they expect to make all 15 payments on time or with one missed payment. We note that for 80 percent of all products (including loans and savings accounts), the best product according to Profile 1 would not be chosen under the other profile so that choosing according to the profile was important. Finally, none of the participant characteristics in Peru affects financial decision-making, including proxies for education and financial literacy. Column 2 of Table 3 shows that in Mexico, the simplified KFS, the complex table and simple table with 5 products were equally effective at increasing the probability of choosing the best credit product by around 25 percentage points or by 64 percent (from a base of 38.6 percentage points) relative to credit choices using brochures. Interestingly, doubling the number of products from 5 to 10 eviscerates the positive impact on decision- making as participants do no better with the 10-product comparative table than with brochures. This result is consistent with the concept of choice overload coined by Toffler (1970) and described in Iyengar and Lepper (2000) and Schwartz (2004). We also find that showing the total cost of the credit in pesos (instead of in percentages) increases the probability of choosing the cheapest credit product by 8 percentage points, confirming the findings of Hasting and Tejada (2008), Gigerenzer et al. (2003) and Shu and Townsend (2010). In contrast, the live calls, SMS or the glossary did not improve decision-making. About half of the participants had heard about CONDUSEF, and indeed receiving an SMS prior to the experiment increased the odds of knowing about CONDUSEF by 25 percent. Participants received an average of 2.4 SMS from CONDUSEF in the 5 days prior (and they recalled receiving around 3 SMS per day). They received about 1.2 live calls from CONDUSEF. Despite the number of SMS and calls, the message did not register, as it did not improve the ability to choose the best financial product. Perhaps since they were not facing a teachable moment at the time they received the SMS or call, they ignored the content. The lack of impact of the glossary may be explained by the fact that it was difficult to understand. Online Appendix OA3 reports the glossary that was handed out. Among the participant characteristics, financial literacy is the only one that contributed to better decision-making by 10 percentage points, but the impact of the simplified KFS is 2.5 times larger than that of financial literacy. Column 3 of Table 3 16 presents the pooled regression comparing the simplified KFS to the brochures. These were the disclosure treatments common to both countries. We find that the simplified KFS improves the probability of choosing the best credit product by 23 percentage points (p-value is 0). This result is remarkable because it indicates that the same individual can improve his or her decision-making simply by using a different format. When we compare individuals with and without financial literacy, we find that financially literate individuals are 6.6 percentage points more likely to choose the right credit product. This comparison is somewhat problematic because financially literate individuals may differ in other characteristics to those that are financially illiterate and therefore differences in decision-making cannot be solely attributed to financial literacy. By comparing the coefficients, however, what is remarkable is that the simplified KFS is almost 3.5 times more effective than financial literacy. While the simplified format significantly improves decision-making for credit products, columns 4 to 6 show that this is not the case for savings products. The coefficient on simplified KFS is positive in columns 4 and 6 but negative in column 5 and never statistically significant. In column 4, the market-designed KFS does not improve the choice of savings products (relative to marketing materials) either. In column 5, the simple table with 5 products and to a lesser extent the complex table and the simple table with 10 products increase the probability of choosing the highest-yielding savings account according to the profile assigned. The simple table increases the probability by 17.7 percent or by 51 percentage points (from a base of 34.2 percent among those offered brochures). Similar to column 2, when the yield is presented in pesos rather than percentage terms, the probability of choosing the right savings product increases by 4.1 percent. Among participant characteristics, being a male, having post-secondary education and correctly answering the financial literacy question improve financial decision-making. The impact of financial literacy is again about half that of using the simple table with 5 products to compare across savings products. Table 4 presents the results of the rank-ordered logit. In Peru and in the pooled regression (columns 1 and 3, respectively), the higher the cost of the loan, the lower the probability that that loan will be selected as the first choice. This suggests that individuals 17 are price sensitive. More interestingly, in all of the credit-related specifications (columns 1 to 3), the interaction of the total cost with a dummy for the simplified format is also negative and significant, suggesting that price sensitivity is enhanced by the simplified KFS. Put differently, comparison shopping is enhanced with more transparent disclosure. Related, financial literacy also increases price sensitivity in Mexico and using the pooled sample (columns 2 and 3, respectively). Echoing the results of Table 3, the impact of financial literacy is however more muted than that of the disclosure format. Individuals also seem price sensitive when evaluating savings products (columns 4 to 6). In Peru, using the simplified KFS helps, but not in Mexico. Online Appendix OA4 shows an example of the simplified KFS used in Peru (E) and in Mexico (H). While the format in Peru includes the total yield earned in a month with two usage profiles, the format in Mexico does not contain this information. This is perhaps the reason why the simplified KFS is effective in Peru but not in Mexico. As a result, in the pooled regression only financial literacy matters. Table 5 computes the price-elasticity from the estimates of Table 4. In practice, we use data from one disclosure treatment and run a simple rank-ordered logit without interactions.11 Columns 1 and 4 use the sample of all respondents. In columns 2 and 5, the sample is restricted to individuals that are not financially literate, that is, individuals that did not answer the question on interest rate correctly ( = 0), while in columns 3 and 5 only individuals who correctly answered that question are included ( = 1). Panel A of Table 5 contains data from Peru, Panel B from Mexico and Panel C pools data from both Peru and Mexico. The price-elasticities reflect the results discussed in Table 4. For example, according to the elasticities reported in column 1 of Panel C, when individuals compare credit products using brochures, an increase of 1 percent in the cost of the loan leads to a decline in the probability of that loan being chosen first of 1 percent (p-value is 0). In contrast, when individuals use the simplified KFS the decline in 11 In particular, we run the following specification: = + + . See Online Appendix 5 for details on how the elasticities were calculated. 18 the probability is roughly three times as large at 3.2 percent. When comparing columns 2 and 3, financial literacy leads, as previously discussed, to higher elasticities in magnitude. When individuals use brochures to compare credit products, the probability that a loan will be chosen first when its costs increases by 1 percent declines by 0.8 percent for a financially illiterate individual to 1.2 percent for a financially literate one. Similarly, when individuals use a simplified KFS the probability declines by 3 and by 3.2 percent, respectively for a financially illiterate and literate individual. Also notably, the simplified KFS is able to correct differences in financial literacy by not only increasing the magnitude of everyone’s price elasticity but also by making the difference in price elasticity between financially literate and illiterate individuals smaller, in percentage terms. Related, Online Appendix Table OA2 reports individual perceptions about the different formats and their knowledge of the interest rate for the chosen product. As shown in column 3, financially illiterate individuals are 17 percent more likely to perceive the simplified KFS as being clear compared to the marketing brochures. Similarly, in column 6 these individuals are 13.2 percent more likely to correctly state the interest rate of the loan chosen. For savings products, the results are far more muted in magnitude and statistical significance. In column 1 of Table 5, an increase in the yield of a savings account by 1 percent increases the probability of choosing that product first by 0.02 percent when individuals use brochures to compare across savings products. When individuals use simplified KFS, the probability of choosing the account first increases by 0.03 and the difference in elasticities is not statistically significant. Columns 9 and 12 of Online Appendix Table OA2 show neither differences in clarity nor correct recall of interest rates between formats. Why are the results for savings so muted? There are a couple of reasons. First, unlike Peru, the simplified KFS in Mexico did not contain the net yield from the account to be earned in a year. Thus, while the simplified KFS in Peru is the only disclosure format with a positive and significant elasticity, in Mexico the simplified KFS is not at all effective. In fact, the price elasticity is lower than that of the brochures and is not significant for financially illiterate individuals. Second, when choosing a savings product, the net yield from the account may not be as relevant as other factors 19 such as convenience, speed, familiarity and trust of the institution offering the product, etc. In the context of our lab experiment we cannot explore convenience and speed of service, but we can study other non-price factors such as the order in which products are presented or appear in a comparative table in Mexico, and whether familiarity with the institution offering the product, defined as a dummy that takes value 1 if the individual has ever contracted a product from that institution. In the context of elections, Ho and Imai (2008) use the naturally occurring variation in ballot order and find that being listed first on the ballot increases the likelihood of being voted especially in primary elections. Similarly, Luca and Smith (2013) study a change in the way universities were ranked in the U.S. News and World Report and find that the ranking matters. Columns 1 and 4 of Table 6 show that individuals using the market-designed KFS in Peru are more likely to choose products that are presented among the first three of the five or that come from institutions that are familiar to the individual. When using the simplified KFS, individuals are less influenced by these factors. Thus, in Peru transparency increases price elasticity while familiarity and the order in which products are presented matter less. In Mexico, neither the order nor familiarity affects the probability of choosing a credit or savings product in columns 2 and 5. As a result, the pooled regression reflect, to some extent, the results in Peru. Individuals are more likely to choose products presented first when using brochures than when using the simplified KFS. 5. Conclusion This study conducts a laboratory experiment to test the effectiveness of behavioral- based financial disclosure by focusing on how comparability and the standardization of formats can improve financial decision-making for low-to-middle income consumers in Peru and Mexico. We find that a standardized key facts statement significantly improves the ability of consumers to make financial decisions and suggests that regulators should not only 20 mandate certain key terms but also the format in which these terms are presented to encourage comparison shopping and improve financial wellbeing. It is encouraging that, in recent years, some regulators have begun mandating standardized formats.12 Interestingly, the standardized format tested increased the probability that individuals choose the best credit product by a factor of three, relative to the increase in probability between financially literate and illiterate individuals. More importantly, the standardized format seems to “democratize” financial decision-making as it is particularly effective for individuals that are financially illiterate. The effects are however concentrated in credit products rather than savings. The lack of impact in savings is concentrated in Mexico, where the simplified format failed to disclose the total yield of the savings account in pesos, which may indicate that total yield calculations can be a useful requirement for disclosure rules to improve consumers’ ability to understand the cost or return of the savings account. The laboratory setting approach taken also suggests an effective mechanism to test the design of financial disclosure initiatives. This approach is not new. For example, the Consumer Financial Protection Bureau and the Federal Reserve of the U.S. constantly survey and test financial consumers on how they understand information, which information they think is useful, and finally how the information can be more effectively conveyed (Kroszner, 2007). Interestingly, Online Appendix Table AO3 shows that among individuals who showed up for a session in Mexico, those that participated in the laboratory experiment (compared to those that were randomly turned away due to lack of space) were more likely to report contracting the session’s financial product in the following 6 months. Owning a business and being a male were also positively correlated with the self-reported likelihood of contracting the financial product. In addition, regulators in Mexico and elsewhere are requiring lenders to send detailed product information in a machine-readable format so they can be downloaded by startups like ComparaBien, ComparaGuru, and rocket.la which provide timely comparative 12 For an emerging market example of such mandatory formats, see Bank of Ghana mandatory disclosure format for loan products: https://www.bog.gov.gh/supervision-a-regulation/consumer-information/pre- agreement-truth-in-lending-disclosure-statement 21 information to individuals looking for financial products. These channels also have the advantage of being fully digital, removing the time and travel burdens to shopping around, and making it easier to review and compare competing key facts statements on the same screen at the same time. In the U.S., a similar initiative called “Smart Disclosure” was undertaken by the Obama Administration (Sunstein, 2013) to provide sharable information so that intermediaries could help consumers make, for example, better informed decisions about energy and health care. A final important consideration for the effectiveness of KFS is the timing of the provision of information. The KFS is most useful early on during the sales visit, so that consumers can quickly receive competing offers and compare across products. However, sales staff may be incentivized to only disclose the KFS late, after the product has been contracted. This practice will undermine the effectiveness of disclosure and the consumer’s propensity to shop around. Policy makers should therefore take care to develop rules regarding the timing of disclosures and monitor compliance with timely disclosure of KFS through mystery shopping (see Giné and Mazer, 2017) and other market monitoring tools. 22 References Adams, P., S. 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Details of Laboratory Experiment Peru Mexico Credit Savings Total Credit Savings Total Number of Sessions 10 10 20 20 17 37 Number of Decisions 900 900 900 1,912 2,372 4,284 Number of participants 300 300 600 479 594 1,073 Number of participants that received a SMS - - - 74 164 238 Number of participants that received a call - - - 92 133 225 Number of participants that received neither a call nor an SMS - - - 312 296 608 Number of participants that received a glossary - - - 221 328 549 Table 2: Participant characteristics Mexico Peru Mean St. Dev Min Max Mean St. Dev Min Max Demographics Male (1 = yes) 0.50 0.50 0 1 0.45 0.50 0 1 Married (1 = yes) 0.55 0.50 0 1 0.63 0.48 0 1 Age 39.27 9.27 25 60 39.87 9.24 25 65 Monthly household income $641 $424 $0.4 $3,516 $783 $590 $1 $4,734 Reports having no income 0.14 0.35 0 1 0.15 0.35 0 1 Socioeconomic level*: (1 = yes) NSE: C 0.32 0.47 0 1 0.82 0.39 0 1 NSE: C- 0.31 0.46 0 1 0.06 0.24 0 1 NSE: D 0.37 0.48 0 1 0.12 0.33 0 1 Education: (1 = yes) Secundary 0.48 0.50 0 1 0.56 0.50 0 1 Post Secundary 0.16 0.37 0 1 0.43 0.50 0 1 Occupation: (1 = yes) Employed 0.38 0.49 0 1 0.32 0.47 0 1 Owns business 0.20 0.40 0 1 0.17 0.38 0 1 Unemployed or housewife 0.27 0.44 0 1 0.28 0.45 0 1 Internet: (1 = yes) Has internet at home or office 0.69 0.46 0 1 0.84 0.36 0 1 Uses internet to compare prices and search for offers 0.16 0.37 0 1 0.79 0.41 0 1 Familiar with Types of Financial Insitutions Banks (1 = yes) 0.26 0.44 0 1 0.42 0.49 0 1 Number of types of financial institutions known out of 10 0.54 0.93 0 7 1.67 2.01 0 10 (banks, cajas, cooperatives, etc) Knows at least one type of financial institution (1 = yes) 0.34 0.48 0 1 0.61 0.49 0 1 Product Usage: (1 = yes) Has credit 0.33 0.47 0 1 0.33 0.47 0 1 Has savings account 0.36 0.48 0 1 0.67 0.47 0 1 Has credit card 0.19 0.39 0 1 0.53 0.50 0 1 Sources of information about financial products* (1 = yes) Staff of financial institutions 0.37 0.48 0 1 0.27 0.45 0 1 Brochures and marketing materials 0.21 0.41 0 1 0.17 0.38 0 1 Friends and family 0.21 0.40 0 1 0.10 0.30 0 1 Media 0.17 0.38 0 1 0.16 0.37 0 1 Financial literacy (1 = yes) Is familiar with Key Facts Statement 0.14 0.35 0 1 0.16 0.37 0 1 Knowledge of interest rate*** 0.66 0.47 0 1 0.48 0.50 0 1 Number of observations 1073 900 Data come from the initial survey. The types of financial institutions considered (out of 10) are: banks, cajas de ahorro, insurance companies, cooperatives, finance companies, edpymes, EEDE, AFP, pawn shop and moneylenders. *In Mexico, C-D socioeconomic groups identify low-to-middle income household. ** Only credit products for Mexico. *** Knowledge of interest rate is tested with the following multiple choice question: "If you deposit 100 soles/pesos in a bank account that charges you nothing and guarantees you a yield of 2% per year, how much would there be in the account by the end of the year, if no deposits or withdrawals are made?" Possible answers are: (a) Over 102. (b) Exactly 102. (c) Less than 102. (d) I don’t know. (e) I prefer not to answer. Table 3: Product choice Best choice (1 = yes) Credit Savings Peru Mexico Pooled Peru Mexico Pooled (1) (2) (3) (4) (5) (6) Simplified format (1 = yes) 0.126*** 0.251*** 0.231*** 0.039 -0.012 0.019 (0.037) (0.032) (0.024) (0.033) (0.027) (0.020) Peru Market designed KFS (1 = yes) -0.043 0.040 (0.038) (0.035) Mexico Complex Table (5 institutions) 0.224*** 0.071*** (0.030) (0.026) Simple Table (5 institutions) 0.293*** 0.177*** (0.029) (0.026) Simple Table (10 institutions) 0.020 0.117*** (0.033) (0.027) Amount in pesos 0.080*** 0.041** (0.022) (0.019) Live call -0.036 -0.011 (0.029) (0.027) SMS 0.002 -0.022 (0.026) (0.026) Glossary -0.003 -0.041* (0.021) (0.022) Low Profile Low Profile (1 = yes) 0.019 -0.009 0.001 -0.028 -0.014 (0.039) (0.044) (0.034) (0.022) (0.024) Participant Characteristics Male (1 = yes) 0.009 -0.014 -0.002 0.008 0.057*** 0.050** (0.040) (0.021) (0.026) (0.035) (0.022) (0.025) Age -0.014 -0.006 -0.001 0.002 0.005 0.001 (0.018) (0.009) (0.012) (0.015) (0.010) (0.011) Age Squared (divided by 100) 0.015 0.008 0.000 -0.005 -0.008 -0.002 (0.021) (0.012) (0.014) (0.018) (0.013) (0.013) Education (Post secundary) 0.028 0.043 0.025 -0.037 0.144*** 0.033 (0.041) (0.026) (0.031) (0.036) (0.030) (0.030) Financial Literacy (1 = yes) -0.012 0.102*** 0.066** 0.046 0.088*** 0.050** (0.042) (0.022) (0.027) (0.035) (0.023) (0.026) N 900 2,390 1,558 900 2,965 1,788 R-squared 0.035 0.088 0.068 0.015 0.050 0.015 Round FE Y Y Y Y Y Y Country FE N N Y N N Y Control Mean 0.477 0.386 0.421 0.273 0.342 0.319 P-values of difference in means Peru Simplified - Market designed 0.000 0.979 Mexico Simplified - TComplex 0.374 0.003 Simplified - TSimple 5 0.165 0.000 Simplified - TSimple 10 0.000 0.000 TComplex - TSimple 5 0.019 0.000 TSimple 5 - TSimple 10 0.000 0.0261 Notes: This table reports the estimation of the following specifications: 1) For Peru, BestChoice ijk = αj + β1Simplified jk + β2Mkt jk + β3LowProfile ik + X ik'γ+ εijk. Simplified jk and Mkt jk denote the different disclosure formats. LowProfile ik takes the value of 1 if participant i in session k is assigned to Profile 1. 2) In columns 2 and 5, for Mexico, BestChoice ijk = αj + β1Simplified jk + β2Complex jk + β3Simple 5jk + β4Simple 10jk + β5AmountPesos ijk + β6Glossary ik +β7LiveCall ik +β8SMS ik + β9LowProfile ik + X ik'γ + εij. Simplified jk, Complex 5jk, Simple 5jk and Simple 10jk denote the different disclosure formats. AmountPesos ijk is a dummy variable that takes the value 1 if participant i in round j of session k saw the total amount to be paid (credit product) or earned (savings product) displayed in pesos and 0 if in percentages. Glossary ik is a dummy indicating if participant was provided with a glossary of terms during session k and 0 otherwise. LiveCall ik / SMS ik take the value of 1 if the participant i received a call/SMS prior to session k and 0 otherwise. LowProfile ik is only used in regressions for savings sessions and takes the value of 1 if participant i in session k is assigned to Profile 1. 3) Pooling data from both Peru and Mexico, BestChoice ijk = αj + β1Simplified jk + β2LowProfile ik + X ik'γ+ εijk. In this specification we include country fixed effects. In all specifications, BestChoice ijk takes the value of 1 if participant i in round j and session k has chosen the best product and 0 otherwise. Vector of characteristics X ik includes the following variables: male, whether the individual has a post secondary education, age and age squared (divided by 100) and a proxy for financial literacy that takes value 1 if the individual correctly answered the question on interest rate. In all specifications we use round fixed effects. Control treatment includes promotional materials (brochures, amortization tables etc.) collected from financial institutions. Standard errors are clustered at the participant level and are reported in parenthesis under coefficient estimates. Levels of significance * p<0.10 ** p<0.05 *** p<0.01. Table 4. Product choice based on price (rank-ordered logit) Credit Savings Peru Mexico Pooled Peru Mexico Pooled (1) (2) (3) (4) (5) (6) Total yield or cost -0.006*** -0.000 -0.003*** 0.012** 0.008** 0.008** (0.002) (0.000) (0.000) (0.006) (0.003) (0.003) Simplified format (1 = yes) 4.379*** 4.787*** 0.131*** 0.055*** -0.014 -0.001 (0.932) (0.543) (0.023) (0.013) (0.013) (0.010) Simplified x Yield / Cost -0.008*** -0.004*** -0.000*** 0.004*** -0.002 0.001 (0.002) (0.000) (0.000) (0.001) (0.005) (0.001) Fin lit x Yield /Cost -0.003 -0.002*** -0.003*** 0.014 0.010*** 0.012*** (0.002) (0.000) (0.001) (0.009) (0.004) (0.004) Simplified x Yield / Cost x Fin Lit 0.000 0.001 -0.000 (0.001) (0.005) (0.002) Peru Market designed KFS (1 = yes) 0.183 0.009 (0.896) (0.012) Market designed KFS x Yield / Cost -0.000 0.001 (0.002) (0.001) Market designed KFS x Yield / Cost x Fin Lit 0.000 -0.000 (0.000) (0.001) Mexico Complex Table (5 institutions) 4.185*** 0.019 (0.516) (0.014) Simple Table (5 institutions) 4.113*** -0.009 (0.523) (0.012) Simple Table (10 institutions) 2.811*** -0.016 (0.571) (0.012) Complex Table (5 institutions) x Yield / Cost -0.004*** 0.004 (0.000) (0.004) Simple Table (5 institutions) x Yield / Cost -0.004*** 0.001 (0.000) (0.004) Simple Table (10 institutions) x Yield / Cost -0.003*** 0.009* (0.001) (0.005) Complex Table (5 institutions) x Yield / Cost x Fin Lit -0.000 0.005 (0.000) (0.005) Simple Table (5 institutions) x Yield / Cost x Fin Lit -0.000 0.005 (0.000) (0.005) Simple Table (10 institutions) x Yield / Cost x Fin Lit -0.000*** -0.000 (0.000) (0.006) N 2,700 7,169 4,668 2,700 8,895 5,358 Number of individuals 300 478 778 300 593 893 Notes: This table reports the following rank-ordered logit specification: 1) For Peru, Ordercijk = αj + β1Price cijk + β2Simplified jk + β3Simplified jk*Price cijk + β4Price cijk*FinLit ik + β5Simplified jk*Price cijk*FinLit ik + β6Mkt jk + β7Mkt jk*Price cijk + β8Mkt jk*Price cijk*FinLit ik + εcijk,. Simplified jk, and Mkt ij denote the Simplified KFS and the Market designed KFS. 2) For Mexico, Ordercijk = αj + β1Price cijk + β2Simplified jk + β3Simplified jk*Price cijk + β4Price cijk*FinLit ik + β5Simplified jk*Price cijk*FinLit ik + β6Complex5 jk + β7Simple5 jk + β8Simple10 jk + β9Complex5 jk*Price cijk + β10Simple5 jk*Price cijk + β11Simple10 jk*Price cijk + β12Complex jk*Price cijk*FinLit ik + β13Simple5 jk*Price cijk*FinLit jk + β14Simple10 jk*Price cijk + εcijk. Simplified jk, Complex jk, Simple5 jk and Simple10 jk denote the different main treatments. 3) Pooling data from both Peru and Mexico, Ordercijk = αj + β1Price cijk + β2Simplified jk + β3Simplified jk*Price cijk + β4Price cijk*FinLit ik + β5Simplified jk*Price cijk*FinLit ik + εcijk. An observation is a choice c made by each individual participant i in round j and session k. In all specifications, Price cijk is either the total loan cost or the savings yield of the each product. Ordercijk takes value 3 for the first choice of individual i in round j in session k, 2 for the second choice and 1 for the third choice. FinLit ik is a proxy for financial literacy that takes value 1 if the individual correctly answered the question on interest rate. Control treatment includes promotional materials (brochures, amortization tables etc.) collected from financial institutions. Standard errors are clustered at the participant level and are reported in parenthesis under coefficient estimates. Levels of significance * p<0.10 ** p<0.05 *** p<0.01. Table 5. Price Elasticities Panel A: Peru Credit Savings Fin literacy Fin literacy All All No Yes No Yes (1) (2) (3) (4) (5) (6) Brochures -2.154*** -1.767* -2.451*** 0.003 0.000 0.007 (0.622) (0.967) (0.781) (0.008) (0.010) (0.014) Simplified format -5.537*** -4.878*** -6.169*** 0.037*** 0.030*** 0.048*** (0.421) (0.664) (0.630) (0.009) (0.011) (0.015) Market designed KFS -2.286*** -1.897** -2.558*** 0.012 0.004 0.024 (0.523) (0.860) (0.681) (0.008) (0.011) (0.014) Panel B: Mexico Credit Savings Fin literacy Fin literacy All All No Yes No Yes (1) (2) (3) (4) (5) (6) Brochures -0.968*** -0.042 -1.563*** 0.034*** 0.017 0.042*** (0.278) (0.417) (0.345) (0.007) (0.012) (0.009) Simplified format -2.875*** -2.835*** -2.744*** 0.029*** 0.008 0.037*** (0.229) (0.275) (0.315) (0.008) (0.014) (0.009) Complex Table (5 institutions) -2.722*** -2.484*** -2.698*** 0.057*** 0.031** 0.075*** (0.157) (0.275) (0.269) (0.009) (0.013) (0.013) Simple Table (5 institutions) -2.337*** -2.383*** -2.090*** 0.054*** 0.028 0.070*** (0.165) (0.178) (0.279) (0.012) (0.019) (0.016) Simple Table (10 insitutions) -2.541*** -2.065*** -2.646*** 0.081*** 0.063*** 0.089*** (0.141) (0.391) (0.214) (0.015) (0.024) (0.018) Panel C: Pooled Credit Savings Fin literacy Fin literacy All All No Yes No Yes (1) (2) (3) (4) (5) (6) Brochures -1.038*** -0.759*** -1.196*** 0.024*** 0.012*** 0.031*** (0.046) (0.079) (0.054) (0.002) (0.003) (0.003) Simplified format -3.185*** -2.960*** -3.166*** 0.029*** 0.014 0.037*** (0.157) (0.254) (0.248) (0.006) (0.010) (0.008) Notes: This table reports the price-elasticities of the probability that a specific prouct is chosen first by an individual. These elasticities are estimated based on the following rank-ordered logit specifications: Order cijk = αj + β1Price cijk + εcijk. Each elasticity is calculated with correspondent data samples. An observation is a choice c made by each individual participant i in round j and session k. Price ijc is either the total loan cost or the savings yield of the each product. yijc is a variable that takes the value of 1 if the individual choses product first. Standard errors are clustered at the participant level and are reported in parenthesis under coefficient estimates. Levels of significance * p<0.10 ** p<0.05 *** p<0.01. Table 6. Product choice based on non-price factors (rank-ordered logit) Credit Savings Peru Mexico Pooled Peru Mexico Pooled (1) (2) (3) (4) (5) (6) Total yield or cost -0.016*** -0.009*** -0.007*** 0.023** 0.029*** 0.025*** (0.002) (0.000) (0.001) (0.009) (0.003) (0.004) Simplified format (1 = yes) -0.015 -0.149** -0.075 0.220*** 0.004 0.070 (0.073) (0.072) (0.049) (0.082) (0.054) (0.045) Top of the Table (1 = yes) 0.113 0.054 0.083 0.499*** 0.024 0.180** (0.134) (0.105) (0.082) (0.135) (0.092) (0.076) Institution familiarity (1 = yes) -0.232 -0.072 -0.128 -0.037 -0.025 -0.014 (0.187) (0.249) (0.229) (0.051) (0.226) (0.186) Peru Market design KFS -0.217*** 0.234*** (0.079) (0.074) Mexico Complex Table (5 institutions) -0.076 -0.039 (0.065) (0.056) Simple Table (5 institutions) -0.008 -0.071 (0.067) (0.054) Simple Table (10 institutions) -0.433*** -0.045 (0.066) (0.046) Top of the Table Simplified format * Top of the Table -0.140 0.134 0.009 -0.520*** -0.041 -0.195* (0.187) (0.141) (0.111) (0.188) (0.128) (0.105) Peru Market designed KFS x Top of the Table 0.447** -0.540*** (0.174) (0.174) Mexico Complex Table (5 institutions) x Top of the Table 0.000 0.000 (0.000) (0.000) Simple Table (5 institutions) x Top of the Table -0.086 0.104 (0.145) (0.129) Simple Table (10 institutions) x Top of the Table 0.096 -0.160 (0.146) (0.153) Institution familiarity Simplified format x Familiarity 0.000 0.395 0.401 0.061 0.046 0.028 (0.000) (0.325) (0.307) (0.055) (0.301) (0.244) Peru Market designed KFS x Familiarity 0.386* 0.059 (0.221) (0.057) Mexico Complex Table (5 institutions) x Familiarity 0.024 0.365 (0.356) (0.311) Simple Table (5 institutions) x Familiarity 0.736** 0.176 (0.327) (0.308) Simple Table (10 institutions) x Familiarity -0.020 0.643** (0.405) (0.267) N 2,700 7,169 4,668 2,700 8,895 5,358 Number of individuals 300 478 778 300 593 893 Notes: This table reports the following rank-ordered logit specification: 1) For Peru, Ordercijk = αj + β1Price cijk + β2Simplified jk + β3TopTable cijk + β4Familiarity cijk + β5Mkt jk + β6Simplified jk*TopTable cijk + β7Mkt jk*TopTable cijk + β8Simplified jk*Familiarity cijk + β9Mkt jk*Familiarity cijk + εcijk,. Simplified jk, and Mkt jk denote the Simplified KFS and the Market designed KFS. 2) For Mexico, Ordercijk = αj + β1Price cijk + β2Simplified jk + β3TopTable cijk + β4Familiarity cijk + β5Complex5 jk + β6Simple5 jk + β7Simple10 jk + β8Simplified jk*TopTable cijk + β9Complex5 jk*TopTable cijk + β10Simple5 jk*TopTable cijk + β11Simple10 jk*TopTable cijk + β12Simplified jk*Familiarity cijk + β13Complex ij*TopTable cijk + β14Simple5 jk*TopTable cijk + β15Simple10 jk*TopTable cijk + εcijk. Simplified jk, Complex jk, Simple5 jk and Simple10 jk denote the different main treatments. 3) Pooling data from both Peru and Mexico, Ordercijk = αj + β1Price cijk + β2Simplified jk + β3TopTable cijk + β4Familiarity cijk + β5Simplified jk*TopTable cijk + β6Simplified jk*Familiarity cijk + εcijk. An observation is a choice c made by each individual participant i in rounda j and session k. In all specifications, Price cijk is either the total loan cost or the savings yield of the each product. Ordercijk is a variable that takes value 3 for the first choice of individual i in round j in session k, 2 for the second choice and 1 for the third choice. TopTablecijk is a variable that takes the value of 1 if option c is the first on the table presented to individual i in round j and session k . Familiarity cijk dummy that takes value 1 if the participant had or had ever had a financial product from the institution of the product chosen in order c. Control treatment includes promotional materials (brochures, amortization tables etc.) collected from financial institutions. Standard errors are clustered at the participant level and are reported in parenthesis under coefficient estimates. Levels of significance * p<0.10 ** p<0.05 *** p<0.01. Online Appendix for Information Disclosure and Demand Elasticity of financial products: Evidence from a Multi-country Study by Xavier Giné, Cristina Martínez and Rafael Mazer NOT FOR PRINT PUBLICATION Contents: Page 1: OA1. Marketing materials Page 5: OA2. Scripts for live calls and SMS in Mexico Page 8: OA3. Glossary given to participants in Mexico Page 6: OA4. Treatments Page 23: OA5. Computation of price elasticities Page 24: OA6. Tables Section OA1. Marketing materials A. Example of Marketing materials in Peru (Credit) 1 B. Example of Marketing materials in Peru (Savings) 2 C. Example of Marketing materials in Mexico (Credit) 3 D. Example of Marketing materials in Mexico (Savings) 4 Section OA2. Scripts for live calls and SMS in Mexico A. Script for live calls (Savings) SAVINGS Good morning/afternoon, my name is Guadalupe Gomez and we are calling you as a part of START a pilot study on financial literacy in the name of Condusef. The goal of this call is to provide call you some advice on how to choose an account to save your money. This call will take up to 5 minutes. Have you ever signed Condusef is a public institution that protects and defends up for an account to the rights of the users of financial services. As part of this save your money at mission, we are calling you today to provide some advice on any financial how to choose an account to save your money. institution? YES NO Before opening an account to save your money, you should not only be aware of the offered interest rate (i.e. yield), but also be aware of the fees incurred. The Was the total yield minus the monthly fees determine if the information I just account will provide gains or losses to your savings. gave you clear? NO For example, if your total yield is 5 pesos but you pay 10 pesos per month in fees, your savings will decrease by 5 pesos every month. YES Additionally, we always recommend comparing at least 3 institutions when opening an account and Thank you for your time. We hope the choosing the one that offers the highest yield and information provided was useful. charges the lowest fees. If you have any questions or need help regarding financial products and services, please access www.condusef.gob.mx. END call 5 B. Script for live calls (Credit) CREDIT Good morning/afternoon, my name is Guadalupe Gomez START and we are calling from Condusef. The goal of this call is call to provide you some advice on how to choose a credit product. Have you ever signed up Condusef is a public institution that protects and defends for a credit product at the rights of the users of financial services. As part of this any financial institution? mission, we are calling you today to provide some advice on how to choose a credit product. When signing up for a credit product or personal loan is YES/NO very important to be aware of the total loan cost (i.e. the total amount to be paid). This information is not usually provided by the financial institution, but it is easily calculated by adding up all credit payments, fees and insurance costs. For example, if you ask for 5,000 in credit and the total cost is 15,000, you will end up paying three times the borrowed amount. You should use the total amount to be paid for a loan to make comparisons among different financial institutions. We recommend comparing at least 3 institutions when NO Was the information I signing up for a loan, asking for the same amount and just gave you clear? term conditions. You should always choose the one that offers the lowest total cost. YES Thank you for your time. We hope the information provided was useful. END If you have any questions or need help regarding call financial products and services, please access www.condusef.gob.mx. 6 C. SMS example (Savings) “SMS from CONDUSEF: When opening a savings account, choose the one that gives you the highest interest rate (yield) and charges you the lowest fees.” D. SMS example (Credit) “SMS from CONDUSEF: Before signing up for a loan, check the total amount to be paid, adding up all payments, fees and insurance.” 7 Section OA3. Glossary given to participants in Mexico FINANCIAL GLOSSARY TAC (Total Annual Cost): Total cost expressed in annual percentage, including credit costs and other expenses incurred when purchasing credit product. It allows for comparison between different credit products. Origination fee: One-time fee. Fixed amount or percentage that a financial institution charges the client for giving him/her credit. Disbursement fee: Fixed amount charged by the financial institution when the client uses the money lent to him/her. Credit check fee: Fixed amount charged by the financial institution for checking a client ’s credit history. Annual maintenance fee: Fixed amount charged annually by the financial institution for maintenance of credit product. Credit history: Report that contains the summary of all credit products taken by a client. Can be checked with special entities, such as the Buró de Crédito or the Circulo de Crédito. Advance payment: Payment of partial or total amount the credit borrowed by the client before the payment due date set by the financial institution. Principal or capital: Total amount deposited by the financial institution to the client when giving him/her a loan. Interest rate: Percentage charged by a financial institution when lending money to a client. Interest rate for late payment: Percentage charged by a financial institution when the clients delays the payment. Insurance products Life: Financial instrument that, in case of death of the insured, ensures the payment of an amount corresponding to the deficit balance, according to contract terms. Features: • Sum insured: Up to the deficit balance. • Coverage: Death and total, permanent disability. • Exclusions: Check policy details. • Questions: call 01 800 25 40 20 22. Unemployment: Financial product that, in case of job loss, ensures the payment of the principal installments and the corresponding interest for a certain period of time, according to contract terms. Features: • Sum insured: deficit balance. • Coverage: unjustified dismissal. • Exclusions: Check policy details. • Questions: call 01 800 25 40 20 22. 8 Section OA4. Treatments Peru A. Example 1 of Market Designed Key Facts Statements (Credit) Hoja Resumen CREDITO EFECTIVO N° Solicitud (**) Características Generales Soles Moneda NUEVOS SOLES Monto del préstamo S/. 1,500.00 Plazo (meses) 12 meses Periodo de gracia (meses) Cuotas Mensuales Cuotas al año 12 Tasas, comisiones y gastos S/. Tasa de interés compensatoria Tasa de Interés Compensatoria Efectiva Anual Fija (1) 42.60% Monto total de Intereses Compensatorios S/. 308.68 62.58% TCEA 0.00% Tasa de interés moratoria (3) Comisiones y Gastos Mensuales Físico Físico y electrónico S/. 10.00 Envío de Estado de Cuenta Electrónico No desea EECC sin costo Seguro de Desgravamen: Seguro BCP Seguro endosado Sin seguro Individual (2) (sobre el saldo del crédito) 0.040% Nombre de la Compañía de Seguros Pacífico Vida Nro. Póliza 28445 Comisiones y gastos en caso de ocurrencia Administración de póliza endosada (mensual) No Aplica Por cada póliza endosada. Se aplica si el cliente decide reemplazar el Seguro de Desgravamen ofrecido por el BCP por una póliza de otra Compañía de Seguros. Conceptos que se aplican por incumplimiento de obligaciones Penalidad por pago atrasado (3) S/. 90.00 Total a pagar por el crédito (Sin morosidad) S/. 1,932.79 Total a pagar por el crédito (Con morosidad) (4) S/. 2,022.79 (1) Se encuentra expresada en un año de 360 días. (2) Válido solo para el seguro BCP. Prima expresada en tasas mensuales. El beneficio que brinda el Seguro de (3) La penalidad se cobra una sola vez a partir del día siguiente al vencimiento de la cada cuota, si aplica. La tasa moratoria es un porcentaje fijo a ser aplicado al monto de la cuota, si aplica. (4) Monto calculado asumiendo que el cliente paga una (1) cuota con retraso. 9 Hoja Resumen CREDITO EFECTIVO Nro. Solicitud (**) Pagos Anticipados No se cobran comisiones por pagos anticipados totales o parciales. Garantías Crédito Personal aprobado con: + Fianza Solidaria Sí No + Garantía Hipotecaria Sí No Puede solicitar una copia de la tasación realizada al bien otorgado en garantía, en caso corresponda. La garantía respalda las obligaciones que usted tenga o pueda tener de forma directa o indirecta con el BCP. Cronograma de pago se entrega en hoja adjunta Notas: - Los desembolsos, el pago de las cuotas así como los pagos anticipados del crédito estarán gravados por el impuesto a las transacciones financieras (ITF): 0.005%. Para mayor detalle sobre las operaciones afectas, puede consultar la página web www.viabcp.com. - El aval o fiador es responsable del pago del crédito en caso usted incumpla con el mismo. - Recuerde que siempre que se encuentre al día en el pago de su crédito puede efectuar pagos anticipados en forma total o parcial, con la consiguiente reducción de los intereses al día de pago, deduciéndose asimismo las comisiones y los gastos derivados de las cláusulas contractuales pactadas entre las partes. También puede adelantar el pago de cuotas, en cuyo caso aplicaremos el monto pagado en exceso sobre la cuota del periodo a las cuotas inmediatas siguientes no vencidas, sin que se produzca la reducción de intereses, comisiones y gastos derivados de las cláusulas contractuales. - El cobro del seguro de desgravamen aplicará sobre el saldo deudor del crédito y hasta por un máximo de US$ 100,000. Se solicitará declaración de salud y/o exámenes médicos en caso el crédito en vigencia supere los US$ 50,000 y en otros casos en que se considere necesario. Para dichos casos la cobertura estará supeditada a la aprobación expresa de la Compañía de Seguros. - Ante el incumplimiento de pago según las condiciones pactadas, procederemos a reportarlo a las Centrales de Riesgo con la calificación que corresponda. Declaro haber leído y revisado la Hoja Resumen, el Contrato, la Póliza de Seguro y el Cronograma de Pago, que todas las dudas relacionadas a estos documentos fueron absueltas y que firmo con conocimiento pleno de las condiciones establecidas en dichos documentos. ___________________, ________de__________________________de_____________ Lugar Día Mes Año Firma del Titular o Rep. Legal Firma del Cónyuge Banco de Crédito del Perú Nombre del Cliente Nombre del Cliente RUC: 20100047218 Tipo y No Doc. Identidad Tipo y No Doc. Identidad 10 B. Example 2 of Market Designed Key Facts Statements (Credit) 11 C. Example of Simplified Key Facts Statement (Credit) SCOTIABANK PERU 30 PRODUCTO E HOJA RESUMEN PARA CRÉDITO PERSONAL Variables que deberás utilizar para comparar con otros productos**: Total a pagar por el crédito (sin S/. 1,807.15 TCEA 42.40% morosidad): Total a pagar por el crédito (con S/. 1,877.15 **Se sugiere comparar con créditos personales con el mismo monto y plazo de pago. 1 Monto calculado asumiendo que el cliente paga una (1) cuota con retraso. Cotización Pagos Crédito solicitado S/. 1,500.00 Plazo de pago: 12 meses Frecuencia de los pagos: Mensual (+) Total intereses a pagar S/. 304.07 Número de pagos: 12 Monto de los pagos: 151S/. Comisiones Por env ío físico de EECC S/. 0.00 Usted realizará 12 pagos de S/. 150.60 Penalidad por pago atrasado S/. 70.00 al mes Seguros Desgravamen* 0.030% Tasa de Interés Desempleo* 0.000% Tasa de Interés Efectiva 41.90% (+) Total seguros a pagar 0.030% Tasa de Interés Moratoria 0.0% Total a pagar por el crédito S/. 1,807.15 Avisos importantes a) Recuerde que ante el incumplimiento del pago según el contrato, se realizará el reporte correspondiente a la Central de Riesgos b) Su aval, de ser el caso, responderá por este crédito como si fuera obligado principal frente a la entidad financiera c) Usted tiene derecho a realizar pagos anticipados de las cuotas de su crédito, sin ningún costo d) Cualquier cambio en las comisiones y gastos, o en otros términos del contrato, deberá ser preavisado con 45 días de anticipación En caso de tener un reclamo Usted puede presentar su reclamo a través de los siguientes canales: Oficinas de atención al público a nivel nacional Teléfono: 0-800-94240 Correo electrónico: plataforma@scotiabankperu.pe o a través de la página web http://www.scotiabankperu.pe 12 D. Example of Market Designed Key Facts Statements (Savings) CARTILLA DE INFORMACIÓN CUENTAS DE AHORRO SOLES (S/.) Fecha: / / Información Previa de los Costos y Condiciones de Operaciones Pasivas. Ley N° 28587 y modificatorias / Resolución S.B.S. N° 8181 – 2012 Conceptos Cuenta Ahorro Personas / Negocio Tasa de Rendimiento Efectiva Anual (TREA) (1) 1.50% Tasa Efectiva Anual (TEA) Número de Operaciones Libres de Costo Retiros y/o transferencias por ventanilla (Red de Agencias) 2 Retiros y/o transferencias en la Red de Cajeros Automáticos (Scotiabank) y Cajeros Corresponsales Todas COMISIONES CATEGORÍA: Operaciones en Cuenta DENOMINACIÓN: Operaciones en otra localidad 1.00% Depósito Interplaza (2) Mín S/. 7.50 Max S/. 700 1.00% Retiro y Transferencia Interplaza (2) Mín S/. 7.50 Max S/. 700 CATEGORÍA: Uso de Canales DENOMINACIÓN: Uso de Cajero Automático Retiros y/o Transferencias en la Red Cirrus (3) S/. 6.50 Consulta de saldo y movimientos en la Red Cirrus (3) S/. 5.00 Las operaciones realizadas por los siguientes canales son libres de costo (4): Cajeros Automáticos (Red Propia), Banca telefónica, Terminal de Pagos y Consultas, Banca Internet - CrediScotia en Línea. DENOMINACIÓN: Operación en Ventanilla Consulta de Saldos S/. 5.00 Consulta de Movimientos S/. 5.00 Exceso de operaciones libres en ventanilla (Retiros y/o Transferencias) S/. 5.00 CATEGORÍA: Tarjeta de Débito adicionales a solicitud (5) y (6) DENOMINACIÓN: Reposición de Tarjeta Reposición (Duplicado) de la tarjeta de débito (7) S/. 5.00 CATEGORÍA: Servicios brindados a solicitud del cliente DENOMINACIÓN: Retención Judicial y/o Administrativa Retenciones Judiciales y/o Administrativas S/. 100.00 DENOMINACIÓN: Transacciones a través de Otras Instituciones Transacciones a través de otras instituciones (Carta de Instrucción) (8) S/. 5.00 (1) La Tasa de interés Efectiva Anual (TEA) es igual a la Tasa de Rendimiento Efectiva Anual (TREA) y se rige por un año de trescientos sesenta (360) días. Fecha de corte para el cálculo de intereses: el último día de cada mes. Fecha de abono de intereses: último día de cada mes (Si el último día del mes fuera Domingo se calculará al día anterior). (2) El término interplaza se refiere a las operaciones realizadas entre cuentas pertenecientes a agencias de una plaza distinta a la plaza donde se realizó la apertura. (3) Red Cirrus (Foránea): Red de Cajeros Automáticos de otros Bancos. (4) Lugares de Retiro: Red de Agencias (con DNI y Tarjeta de Débito), Cajeros Automáticos Scotiabank (con Tarjeta de Débito) y Cajeros Corresponsales (Con tarjetas de Débito): Son Cajeros ubicados en las Tiendas de aliados (Hiraoka, Curacao, TopiTop, Cassinelli, entre otros), que permiten realizar las operaciones más importantes según las restricciones y horarios pactadas con ellos. 13 (5) Límites diarios: Controla tus tarjetas con el "Límite Global Máximo", selecciona el monto diario máximo a disponer entre los siguientes importes: US $ 260, US $500, US $ 1,000, US $ 1,500, US $ 2,000, US $ 3,000 o su equivalente en soles al T/C del día. Esta opción es gratuita y define el monto a disponer en nuestros canales: Cajero Automático, CrediScotia en Línea, Servicio al Cliente y terminal de Pago y Consultas. (6) Cuando recibas tu tarjeta de débito fírmala antes de utilizarla. Para mayor seguridad cambia tu clave cada tres meses en los cajeros automáticos Scotiabank. Asimismo, si deseas realizar pagos y transferencias puedes realizarlo através de CrediScotia en línea adquiriendo tu TOKEN que contiene una clave dinámica que cambia constantemente. Consulta las tarifas y condiciones acerca de este dispositivo en la red de agencias o en www.crediscotia.com.pe. (7) Duplicado, reposición o reimpresión en caso de robo, pérdida o sustracción. En caso de emergencia: Si has sido víctima de fraude, bloquea tu tarjeta inmediatamente llamando a Servicio de Atención al Cliente al 211-9000 (Lima) o al 0-801-1-9000 (provincia), en ambos casos marca la opción 1 y solicita una nueva tarjeta en nuestras agencias CrediScotia. Si el Cajero Automático (Scotiabank) retiene tu tarjeta, bloquéala inmediatamente. (8) Se podrán realizar transferencias a cuentas propias o a terceros, intermoneda (soles o dólares). El cálculo de intereses se realiza de forma diaria (capitalización diaria) dependiendo del saldo de la cuenta al final del día. El Fondo de Seguro de Depósitos asegura los depósitos nominativos de personas naturales y personas jurídicas privadas sin fines de lucro. Ver los límites en: www.fsd.org.pe En caso de fallecimiento del titular, todo familiar tiene la obligación de comunicar a la Financiera el fallecimiento del mismo, presentando Partida de Defunción, certificado Médico de defunción, DNI y/o partida de nacimiento del titular fallecido. Ello implicará el bloqueo de los fondos de sus cuentas, los que son catalogados como herencia. De esta forma, los herederos, deberán efectuar los trámites correspondientes para ese tipo de procesos. De no encontrarse conforme con las condiciones contractuales, EL CLIENTE podrá solicitar unilateralmente la resolución del contrato suscrito ingresando una comunicación por escrito en la red de Agencias de LA FINANCIERA a nivel nacional. En el caso de reclamos por las operaciones o servicios realizados, los pueden presentar en cualquier agencia de la FINANCIERA a nivel nacional o llamando a la Banca Telefónica al 211-9000 o al 0-801-1-9000 (provincia). Adicionalmente al reclamo que pueda presentar ante LA FINANCIERA, El CLIENTE podrá acudir también a otras instancias con la finalidad de presentar sus reclamos, tales como la SuperIntendencia de Banca, Seguros y AFP, INDECOPI, entre otros. Las partes acuerdan que las tasas de interés, comisiones y gastos podrán ser modificados por LA FINANCIERA durante la vigencia de LA CUENTA, de acuerdo a las condiciones establecidas en el contrato respectivo y normatividad vigente. La permanencia o continuación en el uso de los servicios por parte de EL CLIENTE, significarán su total aceptación a las referidas modificaciones, por lo que de no estar conforme con ellas, EL CLIENTE deberá, manifestarlo por escrito dentro del plazo señalado en la comunicación y/o tomado conocimiento de las mismas, cesando en ese caso el servicio no aceptado, con el consiguiente retiro de lo depositado y de ser el caso, los demás pasivos que EL CLIENTE mantenga frente a LA FINANCIERA. El CLIENTE declara haber recibido la presente Cartilla y el Contrato para su lectura y que la Financiera ha absuelto todas sus preguntas, suscribiendo el presente documento y el Contrato con absoluto conocimiento de sus alcances en cuanto a derechos, obligaciones y responsabilidades contenidas. El presente documento carece de valor si no está acompañado del respectivo contrato firmado por los representantes de la Financiera. De acuerdo a lo señalado en el Contrato, el cliente otorga autorización a la FINANCIERA a cargar en cualquier cuenta, depósito y/o valor que mantuviere en la FINANCIERA las sumas que pudieren resultar de cualquier obligación exigible que mantiene o pudiera mantener en la FINANCIERA. Todas las condiciones se refieren al tarifario a la fecha en que se emite la presente Cartilla de Información. Las transacciones antes señaladas estarán afectas a los tributos de acuerdo a disposiciones legales vigentes. En lo que respecta al ITF, la tasa actual es de 0.005%. Cuenta Ahorro Personas / Negocio - TREA: Se considera para el cálculo un saldo promedio de S/.1000 durante 12 meses sin movimientos, en este caso la TREA es igual que la TEA. Saldo Mínimo de Equilibrio para obtener Rendimiento: S/.1.00. TREA Fija. ________________, ____ de _________ de 20____ Nombres y Apellidos: ________________________ N° de Documento: ________________________ Huella Digital Firma del Cliente (con lapicero tinta negra, Índice Derecho sin sobrepasar el recuadro) ____________________________________________________________________ Sello y firma del Responsable de la Atención 14 E. Example of Simplified Key Facts Statement (Savings) MIBANCO 1 PRODUCTO A Cartilla Informativa de Cuenta de Ahorros en Soles Variables que deberás utilizar para comparar con otras instituciones** Con un saldo medio de S/. 1000, podrá ganar / perder TREA 2.00% en un mes: (Tasa de Rendimiento Sin actividad1 S/. 1.65 Efectiva Anual) Con actividad 2 -S/. 22.35 Saldo Mínimo para Obtener Rendimiento: S/. 500.00 **TREA calculado con un saldo medio de S/ 1000 a un año. Deberá comparar con cuentas de ahorro con el mismo monto y plazo. 1. La ganancia sin actividad asume una consulta de saldo, un depósito y un retiro al mes en cajero autom ático propio. 2. La ganancia con actividad asume dos consultas de saldo, dos depósitos y dos retiros al mes en ventanilla. El Saldo Mínimo para Obtener Rendimiento equivale al saldo promedio que hay que tener en la cuenta para no perder dinero al final del mes, asumiendo que no se realiza operaciones con costo. Tasa de Interés Comisiones de Uso de Canales Cajeros Automaticos Propios: Hasta dos operaciones al mes: TEA 2.00% • Retiro de dinero y transferencias GRATIS • Consulta de saldo GRATIS Comisiones de Mantenimiento de cuenta y EECC A partir de la 3 a operación al mes • Mantenimiento de cuenta • Retiro de dinero y transferencias S/. 2 Con saldo superior al saldo mínimo de S/ 500 GRATIS • Consulta de saldo S/. 3 Con saldo inferior al saldo mínimo de S/ 500 S/. 10 Cajeros Automaticos de Otra Institucion: • Retiro de dinero y transferencias S/. 13 • Reposición de Tarjeta por pérdida o robo S/. 17 • Consulta de saldo S/. 5 En Ventanilla: • Retiro de dinero y transferencias S/. 7 • Consulta de saldo S/. 5 Lugares para efectuar retiros Beneficios • Ventanillas • Las dos primeras operaciones en cajero • Cajeros Automáticos propios o de la red automatico propio son gratis. • Comercios afiliados • Servicio de banca electrónica básica gratis. Avisos importantes a) En caso de pérdida de la tarjeta de débito, sírvase llamar al teléfono indicado en el casillero inferior inmediatamente para bloquearla b) Este depósito está cubierto por el Fondo de Seguro de Depósitos. Puede ver el saldo cubierto en http://www.fsd.org.pe c) Usted puede pedir la remisión de sus saldos y movimientos (estados de cuenta) por vía electrónica sin ningún costo d) Cualquier cambio en las tasas de interés, tarifas o en otros términos del contrato, deberá ser preavisado con 45 días de anticipación En caso de tener un reclamo Usted puede presentar su reclamo a través de los siguientes canales: Oficinas de atención al público a nivel nacional Teléfono: 0-800-90200 Correo electrónico: atencion@mibanco.pe o a través de la página web http://www.mibanco.pe 15 Mexico A. Example of Simple Table, 5 institutions (Credit) Monto que Pagos Producto Institución Seguro de vida En Total Pagas recibes mensuales A Crédito Familiar $ 10,000 $ 1,150 Si $ 13,796 B Financiera Ayudamos $ 9,611 $ 1,045 Si $ 12,934 C Dimex $ 9,484 $ 1,075 Si $ 13,419 D Scotiabank $ 10,000 $ 1,306 Si $ 15,674 E Bancomer $ 9,602 $ 1,087 Si $ 13,445 B. Example of Simple Table, 10 institutions (Credit) Monto que Pagos Seguro de En Total Producto Institución recibes mensuales vida Pagas A Bancoppel $ 10,000 $ 1,224 Si 146.85% B Financiera a Emprender $ 10,000 $ 1,281 Si 153.76% C Banorte $ 10,000 $ 1,162 Si 139.49% D Financiera Ayudamos $ 9,173 $ 1,205 Si 144.60% E HSBC $ 10,000 $ 1,177 Si 141.22% F Caja Popular Mexicana $ 10,000 $ 1,191 Si 142.87% G Banamex $ 8,797 $ 1,075 Si 129.03% H Finamigo $ 10,000 $ 1,286 Si 154.27% I Libertad Servicios Financieros $ 8,878 $ 1,231 Si 147.67% J Financiera Independencia $ 10,000 $ 1,137 Si 136.50% 16 C. Example of Complex Table, 5 institutions (Credit) 3 Intereses CAT Monto Seguro Product Pagos Comision Mensuales (Costo En Total Institución que de Requisitos o mensuales es totales (Incluye Anual Pagas recibes vida Total) IVA) A IFE, co mpro bante de Fincomún $ 10,000 $ 1,106 $ 297 $ - $ 350 70.06% $ 13,273 do micilio 8 Financiera B IFE, co mpro bante de $ 10,000 $ 1,290 $ 853 $ - $ 492 154.04% $ 15,475 Equipate do micilio 9 C IFE, co mpro bante de Santander $ 9,733 $ 1,045 $ 267 $ - $ 308 53.31% $ 12,812 do micilio 10 Libertad IFE, co mpro bante de D Servicios Financieros $ 10,000 $ 1,045 $ - $ - $ 317 45.37% $ 12,545 do micilio , co mpro bante de ingreso s, cuenta de telefo no , 4 referencias, un aval 11 E IFE, co mpro bante de Banamex $ 9,473 $ 1,211 $ 527 $ - $ 513 110.56% $ 15,063 do micilio 12 17 D. Example of Simplified Key Facts Statement (Credit) Financiera Ayudamos 30 OFERTA DE CRÉDITO PERSONAL Cotización Pagos Crédito solicitado $10,000 Monto neto a financiar: $10,000 Monto neto por depositar: $9,580 Intereses a pagar $3,977 Plazo de pago: 12 meses IVA $636 Frecuencia de los pagos: Mensual (+) Total intereses a pagar $4,613 Número de pagos: 12 Monto de los pagos: $1,217.74 Comisiones Por apertura $0 Usted realizará 12 pagos1 $1,217.74 Por disposición $0 al mes Por investigación $0 Cuota Anual $0 IVA $0 Tasa de Interés (+) Total comisiones a pagar $0 Anual 66% Tasa de Interés Mensual 5.5% Seguros Vida* $362 Observaciones Desempleo* $0 IVA $58 (+) Total seguros a pagar $420 Total a pagar por el crédito $15,033 Variables que deberás utilizar para comparar con otras instituciones**: CAT 152.8% Total a pagar por el crédito: $15,033 (Costo Anual Total) **Se sugiere comparar con créditos personales con el mismo monto y plazo de pago. Advertencias 1 Contratar créditos por arriba de tu capacidad de pago puede afectar tu historial crediticio. 2 El aval, obligado solidario o coacreditado responderá como obligado principal frente a la entidad financiera. 3 Incumplir con tus obligaciones te puede generar comisiones e intereses moratorios. 4 Oferta vigente hasta 14/02/2013. Aclaraciones y Reclamaciones Unidad Especializada de Atención a Usuarios (UNE) Domicilio: Federico Gómez No. 17 Local 1. Barrio de Santiago. Teléfonos: 591 100 03 30 Correo electrónico: atención@financiera.mx Registro de Contrato de Adhesión Número: 035-140-001098/03-12208-0411 Fecha: 1 de septiembre de 2012 Comisión Nacional para la Protección y Defensa de los Usuarios de Servicios Financieros Consulta tu contrato en línea, antes de firmarlo en: www.condusef.gob.mx Si tienes alguna duda llama al: 01-800-999-8080 y 53-40-09-99 18 E. Example of Simple Table, 5 institutions (Savings) Ganancias en un Ganancias en un GAT (Ganancia Producto Institución mes sin ninguna mes con Anual Total)* actividad actividad** A Batoamigo -0.02% $0.50 -$3.75 B Finamigo 1.79% $7.92 -$4.88 C Santander -0.68% -$1.00 -$1.00 D Banco Ahorro Famsa -0.08% -$0.17 -$0.25 E Financiera FinComun -0.63% -$0.42 -$12.88 * GAT (Ganancia Anual Total) es un porcentaje que representa el dinero obtenido de una inversión o ahorro durante un año, se obtiene de restarle al rendimiento generado las comisiones cobradas. ** Incluye dos consultas y dos retiros al mes de 250 pesos cada uno, sin ninguna penalidad por no mantener el saldo promedio mínimo mensual requerido. 19 F. Example of Simple Table, 10 institutions (Savings) Ganancias en un Ganancias en un GAT (Ganancia Producto Institución mes sin ninguna mes con Anual Total)* actividad actividad** A Inbursa -1.07% -$3.83 -$4.25 B Caja Popular Mexicana -0.28% $0.17 -$0.25 C HSBC 0.12% $1.08 $0.88 D Banco Compartamos 0.86% $4.58 $4.13 E Financiera FinComun -1.07% -$3.00 -$5.50 F Banco Autofin -1.65% -$6.67 -$7.00 G Banamex 1.27% $7.50 $6.75 H BBVA Bancomer -1.10% -$3.58 -$3.63 Libertad Servicios I -1.30% -$5.33 -$41.50 Financieros J Batoamigo -1.88% -$6.00 -$8.00 * GAT (Ganancia Anual Total) es un porcentaje que representa el dinero obtenido de una inversión o ahorro durante un año, se obtiene de restarle al rendimiento generado las comisiones cobradas ** Incluye dos consultas y dos retiros al mes de 250 pesos cada uno, sin ninguna penalidad por no mantener el saldo promedio mínimo mensual requerido 20 G. Example of Complex Table, 5 institutions (Savings) Comisión Saldo Comisión Comisión por Comisión por Monto GAT Ganancias Ganancias Comisión por promedio por no consulta de retiro de Tasa de mínimo Comisión por (Gananci en un mes en un mes Producto Institución por manejo mínimo mantener el saldo en efectivo en interés de inactividad a Anual sin ninguna con apertura de mensual saldo cajeros cajeros anual apertura Total)* actividad actividad** cuenta requerido mínimo propios del propios del Banco A $50 $10 $9 $450 $0 $0 $0 $0 1.1% -1.27% -0.10% -0.11% Azteca Caja B Popular $300 $25 $9 $900 $0 $9 $0 $0 1.7% -0.99% -0.41% -0.46% Mexicana Financiera C $750 $0 $0 $0 $0 $5 $10 $0 1.5% 1.49% -0.49% -0.54% FinComun Banco D $900 $25 $0 $450 $70 $0 $9 $0 0.1% -0.44% -0.35% -0.39% Walmart BBVA E $650 $15 $6 $900 $40 $0 $5 $0 0.3% -1.48% -0.30% -0.33% Bancomer * GAT (Ganancia Anual Total) es un porcentaje que representa el dinero obtenido de una inversión o ahorro durante un año, se obtiene de restarle al rendimiento generado las comisiones cobradas ** Incluye dos consultas y dos retiros al mes de 250 pesos cada uno, sin ninguna penalidad por no mantener el saldo promedio mínimo mensual requerido. 21 H. Example of Simplified Key Facts Statement (Savings) Scotiabank 30 PRODUCTO C CARÁTULA DE DEPÓSITO Características Comisiones (Precios más IVA) • Monto mínimo de apertura $0.00 Monto : $5,000 • Manejo de cuenta $7.00 Vigencia de la oferta: 1/31/2013 Plazo: 1 año • Comisión por no mantener el saldo $10.00 Cajeros Tasa de Interés Propios: • Retiro de efectivo $0.00 Anual De $1 a $5,000 0.02% • Consulta de saldo $0.00 Variables que deberás utilizar para comparar con otras instituciones GAT** -0.02% Por cada $100 pesos depositados Antes de impuestos podra ganar / o perder en un año: -$0.02 (Ganancia Anual Total) **GAT antes de impuestos calculado con un monto de $5,000 pesos a un plazo de 12 meses. Deberá comparar con cuentas de depósito con el mismo monto y plazo. Lugares para efectuar retiros Beneficios • Cuentas con una indemnización adicional, en caso de que • Ventanillas faltes, tus beneficiarios podrán cobrar tus ahorros, más otro • Cajeros Automáticos monto igual (Aplican restricciones) • Comercios afiliados • Servicio de banca electrónica básica gratis. Seguros Seguro de vida gratuito con beneficio adicional. Advertencias 1. El saldo promedio mínimo mensual que deberás mantener en la cuenta es de: $600.00 De no mantenerlo, el dinero depositado en la cuenta disminuirá cada mes por: $10.00 Garantía Tu dinero está garantizado hasta por 400,000 UDIS por el IPAB, equivalente a ($1,927,764) en términos de las disposiciones aplicables. (Cálculo al 23 de octubre de 2012. Valor de la UDI 4.819411). Aclaraciones y Reclamaciones Unidad Especializada de Atención a Usuarios (UNE) Domicilio: Federico Sánchez No. 34 Local 1. Barrio de Bernal. Teléfonos: 59 18 05 30 Correo electrónico: atención@financieraahorro.mx Registro de Contrato de Adhesión Número: 036-114-021990/02-11218-0324 Fecha: 26 de octubre de 2010 Si tienes alguna duda llama al: 01-800-999-8080 y 53-40-09-99 22 Section OA5: Computation of price elasticities The elasticities are calculated based on the following rank-ordered logit specification: = + + Following Beggs et al. (1981)1, the probability that a product is chosen first among 3 options is given by ℎ (1 > 2 > 3 ) = ∏3 ℎ=1 ∑3 , =ℎ where ℎ = ℎ + ℎ where ℎ has distribution extreme value. The reported elasticities in Table 5 are estimated as follows assuming individuals choose 3 products: 3 (1 > 2 > 3 ) ̅̅̅̅̅̅̅̅̅ 1 1 ℎ 1 = ∗ ̅̅̅̅̅̅̅̅̅ = 1 (1 − 3 )∏ 3 1 ̂1 ∑=ℎ ∑=ℎ ℎ=2 where ̅̅̅̅̅̅̅̅̅ 1 is either the average total loan cost or the average savings yield of all products ̂1 is the chosen as first option taken across all individuals in all rounds and all sessions; probability that a product is chosen first, evaluated at the average total loan cost or savings yield of all products chosen first taken across all individuals in all rounds and all sessions; (1 >2 >3 ) is the partial derivative of the probability that a product is chosen first with 1 respect to its total loan cost or the savings yield, again evaluated at the average total loan cost or at the average savings yield. For each column of Table 5, we restrict the sample observations for a given format and individuals with certain financial literacy level. In particular, columns 1 and 4 use all respondents, columns 2 and 5 use the sample of individuals who did not correctly answer the financial literacy question on interest rates, while columns 3 and 5 use only observations of individuals who correctly answered that question. Standard errors are calculated using bootstrap and clustered at the participant level. 1 Beggs, S., S. Cardell and J. Hausman. 1981. “Assessing the potential demand for electric cars.” Journal of Econometrics 17(1): 1-19. 23 Section OA6. Tables Table OA1. Financial Literacy (1) (2) (3) Peru Mexico Pooled Demographics Male (1 = yes) 0.072** 0.145*** 0.111*** (0.036) (0.030) (0.023) Married (1 = yes) 0.053 -0.013 0.002 (0.035) (0.029) (0.022) Age 0.000 -0.003* -0.001 (0.002) (0.002) (0.001) Monthly household income 0.000*** 0.000 0.000*** (0.000) (0.000) (0.000) Reports having no income -0.054 -0.014 -0.020 (0.051) (0.046) (0.034) Socioeconomic level*: (1 = yes) NSE: C 0.103* 0.005 -0.040 (0.053) (0.037) (0.029) NSE: C- 0.038 -0.001 0.004 (0.080) (0.035) (0.033) Education: (1 = yes) Post Secundary 0.187*** 0.073* 0.131*** (0.036) (0.040) (0.027) Occupation: (1 = yes) Employed 0.072* -0.074** 0.011 (0.041) (0.037) (0.028) Owns business 0.066 -0.010 0.048 (0.048) (0.042) (0.032) Internet: (1 = yes) Has internet at home or office 0.029 0.071** 0.034 (0.047) (0.033) (0.028) Product Usage: (1 = yes) Has credit -0.008 -0.028 -0.001 (0.036) (0.033) (0.024) Has savings account 0.031 0.117*** 0.044* (0.035) (0.031) (0.023) Has credit card -0.010 0.006 -0.035 (0.035) (0.039) (0.026) Number of individuals 887 1,071 1,958 R-squared 0.11 0.057 0.068 Country FE N N Y Mean Dep. Var. 0.481 0.664 0.581 Notes: This table reports the estimates of the regression of a dummy variable that indicates knowledge of interest rate FinLit i on individual characteristics. Knowledge of interest rate is tested with the following multiple choice question: "If you deposit 100 soles in a bank account that charges you nothing and guarantees you a yield of 2% per year, how much would there be in the account by the end of the year, if no deposits or withdrawals are made?". Possible answers are: (a) Over 102. (b) Exactly 102. (c) Less than 102. (d) I don’t know. (e) I prefer not to answer. Data come from the initial survey. *In Mexico, C-D socioeconomic groups identify low-to-middle income household. When pooling the data from Mexico and Peru in Column 3, we also include country fixed effects. Standard errors are reported in parenthesis under coefficient estimates. Levels of significance * p<0.10 ** p<0.05 *** p<0.01. 24 Table OA2: Knowledge of terms Credit Savings Clarity APY Clarity APY Peru Mexico Pooled Peru Mexico Pooled Peru Mexico Pooled Peru Mexico Pooled (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Simplified format (1 = yes) 0.100 0.328*** 0.170*** 0.158* 0.083 0.132* 0.012 -0.166 -0.056 -0.167 -0.026 -0.096 (0.084) (0.103) (0.064) (0.085) (0.117) (0.069) (0.087) (0.115) (0.067) (0.102) (0.122) (0.079) Simplified format x Fin Lit 0.169 0.003 0.091 0.061 0.060 0.041 0.016 0.221* 0.109 0.202 -0.040 0.088 (0.132) (0.126) (0.088) (0.133) (0.143) (0.094) (0.119) (0.130) (0.083) (0.140) (0.138) (0.097) Peru Market designed KFS (1 = yes) 0.004 -0.079 -0.196** -0.125 (0.098) (0.098) (0.090) (0.106) Market designed KFS x Fin Lit 0.039 0.157 0.100 0.118 (0.136) (0.136) (0.126) (0.148) Mexico Complex Table (5 institutions) 0.178 0.344*** -0.232** -0.090 (0.110) (0.125) (0.111) (0.118) Simple Table (5 institutions) 0.156 0.049 -0.256** -0.064 (0.105) (0.119) (0.122) (0.130) Simple Table (10 institutions) 0.314** 0.047 -0.195* 0.078 (0.121) (0.138) (0.111) (0.118) Complex Table (5 institutions) x Fin Lit 0.092 -0.080 0.383*** -0.025 (0.134) (0.152) (0.130) (0.138) Simple Table (5 institutions) x Fin Lit 0.065 -0.030 0.176 -0.098 (0.127) (0.144) (0.141) (0.150) Simple Table (10 institutions) x Fin Lit -0.184 0.067 0.179 -0.196 (0.139) (0.158) (0.130) (0.138) Low Profile Low Profile (1 = yes) 0.037 0.019 0.007 0.022 0.017 0.037 0.054 0.073 0.044 0.029 (0.053) (0.061) (0.053) (0.066) (0.049) (0.037) (0.039) (0.058) (0.039) (0.045) Participant Characteristics Male (1 = yes) 0.008 0.022 0.012 -0.182*** 0.001 -0.108** -0.002 0.064* 0.026 -0.070 0.087** -0.008 (0.054) (0.039) (0.044) (0.054) (0.044) (0.048) (0.051) (0.038) (0.040) (0.061) (0.040) (0.047) Age -0.018 0.028 0.006 -0.007 -0.016 -0.010 0.002 0.012 0.015 -0.030 0.005 -0.003 (0.025) (0.017) (0.020) (0.025) (0.020) (0.022) (0.022) (0.017) (0.017) (0.026) (0.018) (0.021) Age Squared (divided by 100) 0.026 -0.000 -0.010 0.008 0.000 0.007 -0.010 -0.000 -0.018 0.034 -0.000 0.004 (0.030) (0.000) (0.024) (0.030) (0.000) (0.026) (0.027) (0.000) (0.021) (0.031) (0.000) (0.025) Education (Post secundary) -0.036 0.011 -0.048 0.091 0.046 0.056 0.136*** 0.022 0.067 0.193*** 0.047 0.102* (0.056) (0.053) (0.051) (0.057) (0.060) (0.055) (0.052) (0.049) (0.046) (0.061) (0.052) (0.054) Financial Literacy (1 = yes) 0.031 0.082 0.053 0.053 0.084 0.083 -0.083 -0.139 -0.089 -0.131 0.096 -0.007 (0.096) (0.098) (0.067) (0.096) (0.111) (0.073) (0.090) (0.099) (0.063) (0.106) (0.105) (0.074) N 300 478 405 300 478 405 300 593 475 300 593 475 R-squared 0.048 0.077 0.068 0.093 0.065 0.061 0.067 0.048 0.021 0.057 0.038 0.033 Country FE N N Y N N Y N N Y N N Y Mean of Dep. Variable 0.656 0.607 0.632 0.622 0.571 0.598 0.789 0.739 0.761 0.544 0.387 0.455 Peru Simplified - Market designed 0.249 0.005 0.016 0.676 Mexico Simplified - Tcomplex 0.128 0.020 0.517 0.558 Simplified - TSimple 5 0.065 0.750 0.430 0.754 Simplified - TSimple 10 0.894 0.771 0.771 0.326 Notes: This table reports the estimation of the following specifications: 1) For Peru, yijk = αj + β1Simplified jk + β2Simplified jk*FinLit ik + β3Mkt jk + β4LowProfile ik + X ik'γ + εijk, , where i indexes each individual participant and in session j . yijk is the outcome variable that takes the value of 1 if participant i reports clear presentation of the product or if he/she is able to recall correctly the APR /APY of the product given in the last round. Simplified jk, and Mkt jk denote the Simplified KFS and the Market designed KFS. Low Profile ik takes the value 1 if participant is assigned to profile 1. 2) For Mexico, yijk = αj + β1Simplified jk + β2Simplified jk*FinLit ik + β3Complex jk + β4Simple 5jk + β5Simple 10jk + β6Complex jk*FinLit ik + β7Simple 5jk*FinLit ik + β8Simple 10jk*FinLit ik + β9LowProfile ik + X ik'γ + εijk. Simplified jk, Complex jk, Simple 5jk and Simple 10jk denote the different main treatments. LowProfile ik is only used in regressions for savings sessions and takes the value of 1 if participant i in session k was assigned to Profile 1. 3) Pooling data from both Peru and Mexico, y ijk = αj + β 1Simplified jk + β2Simplified jk*FinLit ik + β3LowProfile ik + X ik'γ + εijk. In savings sessions regressions, we assign all individuals in Mexico to profile 1. In this specification we include country fixed effects. An observation is an individual. Vector of characteristics X ik includes the following variables: male, whether the individual has a post secondary education, age and age squared (divided by 100) and a proxy for financial literacy (FinLit ij) that takes value 1 if the individual correctly answered the question on interest rate. In all specifications we use round fixed effects. Control treatment includes promotional materials (brochures, amortization tables etc.) collected from financial institutions. Standard errors are clustered at the participant level and are reported in parenthesis under coefficient estimates. Levels of significance * p<0.10 ** p<0.05 *** p<0.01. 25 Table OA3. Demand for actual financial product (Mexico) (1) (2) Consider getting product in the next 6 months (1=yes) Credit Savings Participated in the experiment (1=yes) 0.099*** 0.179*** (0.034) (0.037) Demographics Male (1=yes) 0.113*** 0.064* (0.036) (0.038) Married (1=yes) 0.023 0.066* (0.034) (0.036) Age -0.004** -0.002 (0.002) (0.002) Socioeconomic level*: (1 = yes) NSE: C -0.028 0.010 (0.044) (0.047) NSE: C- -0.001 -0.013 (0.040) (0.045) Education: (1 = yes) Post Secundary -0.089* -0.044 (0.049) (0.050) Occupation: (1 = yes) Employed 0.056 0.080* (0.040) (0.043) Owns business 0.134*** 0.136*** (0.048) (0.048) Internet: (1 = yes) Has internet at home or office 0.077** 0.040 (0.036) (0.041) Product Usage: (1 = yes) Has credit 0.114*** 0.019 (0.039) (0.042) Has savings account -0.051 0.023 (0.037) (0.039) Has credit card 0.035 -0.061 (0.049) (0.050) Financial literacy (1 = yes) Knowledge of interest rate** 0.004 0.024 (0.035) (0.039) Number of individuals 626 733 Experiment participants 290 395 Non-participants 336 338 R-squared 0.101 0.078 Mean Dep. Var. for non-participants 0.185 0.290 Notes: This table reports the estimates of the regression of a dummy variable that takes value of one of the respondent considers getting a credit or savings product in the next 6 months on another dummy variable that takes value of one if the individual participated in the lab experiment and individual characteristics. Data comes from survey taken in Mexico only. Data come from the initial survey. *In Mexico, C-D socioeconomic groups identify low-to-middle income household. ** Knowledge of interest rate is tested with the following multiple choice question: "If you deposit 100 soles in a bank account that charges you nothing and guarantees you a yield of 2% per year, how much would there be in the account by the end of the year, if no deposits or withdrawals are made?". Possible answers are: (a) Over 102. (b) Exactly 102. (c) Less than 102. (d) I don’t know. (e) I prefer not to answer. Standard errors are reported in parenthesis under coefficient estimates. Levels of significance * p<0.10 ** p<0.05 *** p<0.01. 26