Search

Do different loan application formats affect consumer loan requests? Six studies show that when consumers are asked to provide a preferred monthly payment (MP) (vs. loan amount [LA]), they request different principal amounts. This is because these loan application formats differ in the scale-compatible information they bring to consumers' mind. When LAs are elicited, consumers think of and request the cost of the expenditure they seek to finance. When MPs are elicited, however, consumers think of their monthly budget slack to construct and then request MPs they perceive to be affordable. For lower cost loans with a given term and interest rate, the MP (vs. LA) format results in larger principal requests. This effect reverses for higher cost acquisitions because individuals' budget slack caps out around $500 per month. These studies provide insight into how consumer loan application formats can affect consumer borrowing, as well as the psychological underpinnings responsible for the effect. Theoretical, managerial, and consumer welfare implications of the findings are discussed. [ABSTRACT FROM AUTHOR]

The article examines the peculiarities of the protection of consumer rights in the field of lending under the legislation of Ukraine and the EU from the point of view of bringing national legislation into line with the requirements of EU law in this area. It was determined that the EU is actively working on improving legal mechanisms for the protection of consumer rights in the field of consumer credit through the adoption of new acts. The article analyzes individual changes in this area, as well as outlines the reasons for such changes. In modem banking practice, a fairly wide list of types of consumer loans is used, the main classification features of which are: types of creditors; types of borrowers; repayment methods; terms of use; degree of credit coverage of the cost of goods, works, and services; software; interest payment methods; lending facilities, loan amounts, loan currency, etc. But the presence of a large number of banking products does not exclude the possibility and does not reduce the need for their further development and expansion, which should contribute to the development of consumer lending in general. The level of socio-economic development of the country directly affects the development of consumer lending, at the same time, the dynamics of such macro-indicators as gross domestic product, income and expenditure of the population, volumes of services provided, retail turnover, average monthly nominal wages, etc. have the greatest influence. Consumer lending has a higher efficiency compared to corporate lending, and this is explained not only by its high profitability, but also by the presence of additional income that accompanies the provision of consumer loans. At the same time, the effectiveness of consumer lending depends on the terms of granting, and accordingly, short-term consumer loans are more effective. Therefore, the performance of banks in general as part of the banking system of Ukraine depends on how the mechanism of consumer lending in banking institutions is formed, how regulation and regulation of consumer lending is carried out. Positively evaluating the adoption of the relevant Law in 2016, the author notes the need for its revision and improvement, taking into account Ukraine's European integration progress, as well as the importance of preserving the economic well-being of the population of our state in the face of a full-scale invasion. According to the author, the corresponding changes should concern the requirements for information about consumer credit, the specifics of its conclusion from the point of view of accompanying financial instruments, as well as the simplification and improvement of legal mechanisms for early termination of consumer credit contracts. [ABSTRACT FROM AUTHOR]

In this paper, we use the concept of 'alterity' to explore the hallmarks and transformative potential of Community Development Finance Institutions (CDFIs) in the UK consumer credit market. By providing small, short‐term personal loans to individuals on low incomes (i.e. microcredit), these lenders act as an alternative to exploitative forms of subprime lending, which have proliferated as a consequence of cuts in welfare state provision and growing income insecurity. In‐depth interviews (n = 23) were conducted with lenders and stakeholders and a typology of 'alternatives' was developed in relation to the clients of CDFIs and their role in the consumer credit market. Our contribution to knowledge is twofold: We provide a nuanced picture of 'alterity' in finance, finding that CDFIs embody multiple 'alterities' at the same time, and we extend the conversation about alternative and sustainable finance to the consumer credit market, which is an overlooked, yet critical, area. [ABSTRACT FROM AUTHOR]

We studied the effect of a major bank adopting an AI-enabled credit scoring model on financial inclusion as measured by changes to the approval rate, default rate, and utilization level of a personal loan product for an underserved population. The bank serves over 50 million customers and previously used a traditional rule-based model to evaluate the default risk of each loan application. It recently developed an AI model with a higher prediction accuracy of default risk and used the AI model and the traditional model together to assess loan applications for one of its personal loan products. Although the AI model may be more accurate in estimating default risk, little is known about its impact on financial inclusion. We investigated this question using a differencein-differences approach by comparing changes in financial inclusion of the personal loan product that adopted the AI model to that of a similar personal loan product that did not adopt the AI model. We found that the AI model enhanced financial inclusion for the underserved population by simultaneously increasing the approval rate and reducing the default rate. Further analysis attributed the enhancement in financial inclusion to the use of weak signals (i.e., data not conventionally used to evaluate creditworthiness) by the AI model and its sophisticated machine learning algorithms. Our findings are consistent with statistical discrimination theory, as the use of weak signals and sophisticated machine learning algorithms improves prediction accuracy at the individual level, thus reducing the reliance on group characteristics that often lead to financial exclusion. We elaborated on the development process of the AI model to illustrate how and why the AI model can better evaluate members of underserved populations. We also found the impacts of the AI model to be heterogeneous across subgroups, and those with missing weak signals saw smaller improvements in the approval rate. A simulation-based analysis showed that simplified AI models were also able to increase the approval rate and reduce the default rate for this population. Our findings provide rich theoretical and practical implications for social justice by documenting how an AI model designed for improving prediction accuracy can enhance financial inclusion. [ABSTRACT FROM AUTHOR]

The article "An Introduction to the Law of Private Pawnshops - a Trade with Tradition" deals with the trade of private pawnshops, which grant loans against collateral. It discusses the background of the pawnbroking industry, the significance of the pawnbroker regulation, and the legal transactions in the pawnshop business. Additionally, the role of (model) terms and conditions in the pawnbroking industry is explained. Pawnshops fulfill an important niche function for small loans and are regulated by the pawnbroker regulation. [Extracted from the article]

AbstractBetween the 1880s and 1950s, national mortgage markets were created in the United States and Canada. The formative role of institutions and federal governments are well understood. Personal (individual or ‘private’) lenders have been omitted from the narrative although, in the late 1940s, they still provided a quarter of residential mortgages in the United States and two fifths in Canada. Rarely targeted, they were collateral damage, especially, of state initiatives. The distinctive nature of mortgages, secured on real estate, made the creation of national markets difficult. The character of personal loans – local, non-standard, non-amortized, and often informal -- made their assimilation into any supra-local market especially challenging. Their significance declined in waves: the 1900s, 1920s, and then, under government influence, after 1945. They persist in the reduced gaps left by institutions. We should pay them more attention. [ABSTRACT FROM AUTHOR]

We investigate how local deposit shocks affect bank lending in nonaffected markets for the case where banks mostly neutralize that shock. Colombian banks in oil-producing municipalities experienced deposit outflows after the collapse of oil prices in 2014–2015. Following the shock, we observe that the affected banks increased their credit to non-oil-producing markets by reducing the price of consumer loans and by using market power in both commercial and consumer loans. This paper contributes to understanding how multimarket banks transmit local deposit shocks to other geographic markets to mitigate deposit outflows. [ABSTRACT FROM AUTHOR]

Using a novel combination of mortgage datasets, we analyze the effects of two policy levers influencing the scope of Fannie Mae and Freddie Mac's (Government-Sponsored Enterprises, GSEs) involvement in the U.S. residential mortgage market. First, we find that small changes in mortgage guarantee fees charged by the GSEs were essentially fully passed through to consumers, with limited effects on mortgage demand. This implies that small fee changes are primarily transfers between mortgage consumers and taxpayers while the GSEs remain in federal conservatorship. Second, the data suggest that marginally lowering maximum conforming loan size limits would cause most affected consumers to reduce their loan amounts to the new maximum. Our findings provide new detailed evidence on how GSE policy shapes mortgage availability and contrast the differing effects on consumers of two potential policy levers to reduce (or increase) the scope of GSE lending. Additional survey data indicate that borrowers' shopping behavior and incomplete information may also influence the effects of GSE policy changes. [ABSTRACT FROM AUTHOR]

This article examines the impacts of traditional and digital finance on the financing of small and micro family businesses (SMFBs) in China. Based on a comprehensive sample of 8625 SMFBs from China Household Financial Survey (CHFS) data, our results from Tobit regressions showed that traditional finance did not reduce the financing constraints of SMFBs, while digital finance significantly promoted SMFBs' access to credit. Further analyses revealed that additional credit from digital finance helped SMFBs increase their business scale and operational capability, but decreased their profitability due to the high loan cost associated with digital finance. Our findings imply on the one hand that government policies aiming at encouraging commercial banks to provide loans to small and micro enterprises in China have been producing very limited effects. On the other hand, digital finance is an effective micro-loan provider for SMFBs thanks to its strong ability in collecting and integrating individuals' credit history data, although more measures are needed to take for turning this financing enhancement of SMFBs into their profit growth. These findings enrich the literature on family business by comparing the effectiveness of different financing sources for SMFBs in China. It provides important insights for future policy design on how to ease financial constraints in SMFBs and support the development of SMFBs. Plain English Summary: This study investigated the effects of traditional finance and digital finance on the financing of SMFBs in China. Tobit regression results indicated that traditional finance did not alleviate the financing constraints experienced by SMFBs. Despite the use of advanced financial technologies and the encouragement from government policies, commercial banks are still unwilling to extend credit to SMFBs. Digital credit, by contrast, enhanced the financial accessibility for SMFBs. Moreover, increased financing from digital finance was positively associated with SMFBs' business expansion and operational ability, although it did not enhance the profitability of SMFBs in a short run. To effectively promote the financing and business success for SMFBs, efforts from multiple agents need to be taken. The owners of SMFBS should involve more in-depth in business operation and take greater responsibility for enterprise management. Policymakers should consider commercial banks' objectives and interests, when encouraging them to lend to small and micro businesses, and monitor the true interest rate of digital financial services. [ABSTRACT FROM AUTHOR]

A randomized encouragement design yields null average effects of a credit builder loan (CBL) on consumer credit scores. But machine learning algorithms indicate the nulls are due to stark, offsetting treatment effects depending on baseline installment credit activity. Delinquency on preexisting loan obligations drives the negative effects, suggesting that adding a CBL overextends some consumers and generates negative externalities on other lenders. More favorably for the market, CBL take-up generates positive selection on score improvements. Simple changes to CBL practice, particularly to provider screening and credit bureau reporting, could ameliorate the negative effects for consumers and the market. Authors have furnished an Internet Appendix , which is available on the Oxford University Press Web site next to the link to the final published paper online. [ABSTRACT FROM AUTHOR]

A mathematical description of the economic behavior of a representative household in an imperfect market of consumer loans and deposits is studied. The model is formalized as a finite-horizon optimal control problem. A classification of the behavior of social layers depending on market condition parameters is obtained. An infinite-horizon optimal control synthesis is constructed. [ABSTRACT FROM AUTHOR]

We experimentally study the impact of relatively large enterprise loans in Egypt. Larger loans generate small average impacts, but machine learning using psychometric data reveals " top performers" (those with the highest predicted treatment effects) substantially increase profits, while profits drop for poor performers. The large differences imply that lender credit allocation decisions matter for aggregate income, yet we find existing practice leads to substantial misallocation. We argue that some entrepreneurs are overoptimistic and squander the opportunities presented by larger loans by taking on too much risk, and show the promise of allocations based on entrepreneurial type relative to firm characteristics. (JEL C45, D22, G21, G32, L25, L26, O16) [ABSTRACT FROM AUTHOR]

Purpose: The purpose of microcredit is to offer small loans to people who are not covered by traditional financial channels. It can facilitate entrepreneurship, boosting local socio-economic development and improving environmental and political factors. Design/methodology/approach: This paper aims to analyse microcredit in Italy, focusing on a project based in Rione Sanità, Naples. Rione Sanità is one of the poorest areas of Southern Italy, displaying high rates of criminality and unemployment, especially among youth, women, migrants and the vulnerable. The district is renowned for its fine and ancient handicrafts, food, trade and historical heritage – potential drivers for boosting tourism in the area. Qualitative methodologies were used to collect primary data through field visits and interviews with project bankers, local businesses, artisans, associations and religious representatives, project volunteers, as well as participation at local meetings. These data were corroborated by budget analysis based on the project's accounting. Findings: The study shows encouraging results for the project and policy prospects. Despite the tiny starting numbers, there emerges a significant potential for microcredit to spread in the district, as in Southern Italy, providing an effective strategy to combat unemployment, usury and criminality, yielding community development and favoring broad societal challenges. Originality/value: With this evidence, the paper attempts to shed some light and verify the potential of microfinance projects as a driver of sustainable development and ethical finance in poor areas of developed countries. [ABSTRACT FROM AUTHOR]

Native Community Development Financial Institutions (Native CDFIs) have become an increasingly important source of credit and financial services in the areas on or near American Indian reservations in the United States. Guided by a conceptual framework developed on the basis of the related finance literature and drawing on loan‐level data from eleven Native CDFI loan funds, we offer the first systematic quantitative analysis of lending in the Native CDFI industry. As hypothesized, Native CDFIs on average give out small loans but support borrowers in varied circumstances with diverse loan products. Important predictors of delinquency include both conventional, hard information‐based, measures of client risk, and alternative, soft information‐based, community‐informed and character‐based measures. Overall, these findings lend strong support to holistic approaches for assessing client creditworthiness for Native CDFI operations. More generally, our analysis contributes new insights into the operations of an industry that plays an instrumental role in removing barriers to socioeconomic development in Native communities. [ABSTRACT FROM AUTHOR]

The study examined the effect of bank loans on entrepreneurial productivity in Nigeria. Based on an ex-post facto research strategy, secondary data were gleaned from the bulletins of the Central Bank of Nigeria and National Bureau of Statistics, covering the period from 2008 to 2022. Descriptive statistics was applied to summarize the key variables under study. In addition to the descriptive analysis conducted, Jarque-Bera test of normality, Breusch-Godfrey Serial Correlation LM Test, Harvey test of heteroskedasticity and Ramsey RESET test for linearity were conducted to assess the validity of the ordinary least square (OLS) regression used in hypothesis testing. The findings from the validated OLS estimates revealed that entrepreneurial productivity in Nigeria is significantly fueled by bank loans to small and medium scale enterprises (ß = N115.16; p-value = 0.006672). In conclusion, banks play a pivotal role in enhancing the productivity of entrepreneurial ventures by facilitating easier access to credit. Therefore, we recommend that the government should implement policies that reduce barriers to credit for SMEs, such as lowering interest rates on loans and providing loan guarantees. This will help more entrepreneurs access the financing required to enhance their productivity. [ABSTRACT FROM AUTHOR]

This study investigated a network of financial institutions in Korea using the Korea Consumer Credit Panel (KCCP). It is assumed that each consumer borrows from multiple institutions, so those institutions share risks from the same consumers regardless of the quality or type of loan. We constructed a financial network comprising those institutions and computed a contagion index based on their interconnections using a weight of probability of default for the individual borrowers. We found strong connection between banking institutions and credit card firms because of the convenience of making small loans using credit cards. However, with a weighted probability of default to the linkages among institutions, the connections between banking institutions and savings banks, non-credit card finance corporations and merchant banks are stronger than others, while banking institutions hold a central position and are exposed to the largest amount of loans individually. The contagion index hit a peak in 2013Q1 and then fell rapidly, before fluctuating at a relatively low level from 2016 to 2017Q2. The results enabled authorities to monitor systemic risk from the level of consumer credit, while accounting for specific types of consumers and their probability of default. This paper's main contribution is its construction of a network of financial institutions from the level of consumer credit. [ABSTRACT FROM AUTHOR]

The Two-Wheelers are the most common street commuters seen on the Nepalese narrower roads because of the purchasing capacity of the Nepalese riders, road conditions of Nepal, fuel consumption and availability, government-levied road taxes, and the small amount of loans made available by the financial institutions. Keeping all these conditions and increasing the use of two-wheeled bikes by Nepalese riders, research was conducted to find the best bike for Nepalese Two-wheeled users. For this study purpose, 215 samples were collected visiting the sales outlets, garages and Two-wheeler workshops in Nepal. Data were analyzed using SPSS and other suitable statistical tools. The research result showed that the most sold Two-Wheelers sold in Nepal was Bajaj and in the Scooter section the Honda Dio was the most sold ones. The Hero brand is also found popular in Nepal. Yamaha and TVS also have a good market share. [ABSTRACT FROM AUTHOR]

This study aims to determine the affecting factors of repayment performance in Small Medium Enterprises (SMEs) in Indonesia for individual loan program. The data in this study is gathered by credit active during 2023 which contain of 300 samples from several region in Indonesia that came from one of Non-Banking Financial Institutions (NBFIs). The data is analyzed by logit regression model by Stata software version 18. The study indicates that the borrower’s income and amount of loan disbursements have significantly affected the repayment of the borrower’s outstanding loan for both principal and interest in time. Furthermore, the study shows that the higher amount of loan disbursement might affect the lower probability of defaulting due to high assessment of credit appraisal. Since the loan programs are delivered for individual for owner or management of Small Medium Enterprises (SMEs) in Indonesia. A prudent procedure is needed to establish for newer borrowers of the individual loan programs. The screening process consists of income cash flow analysis and how long the cash flow will be generated for repaying the programs. the novelty for this result enhances the current research for SMEs financing program in Indonesia for individual loan credit program. Specially credit loan program is delivered and sponsored by Indonesia government. Not much research focused on individual loan programs for SME’s owner or management. [ABSTRACT FROM AUTHOR]

We explore the potential outcomes for financial stability when using peer‐to‐peer lenders to finance economic activity. Combining Random Regression Forests, a machine‐learning process, with an agent‐based model, we perform simulations on artificial economies with various degrees of adoption of peer‐to‐peer lending. We find that as peer‐to‐peer lenders proliferate, there is increased financial instability, lower GDP and higher unemployment. On the other hand, peer‐to‐peer lending increases the total volume of loans given out but demonstrates a preference towards consumer loans (over corporate loans), which has a negative effect in the long run. Finally, introducing peer‐to‐peer lenders increases the access of the unbanked to services which conventional banking is not able to offer within the extant regulatory framework. Our results can help policymakers as they address the issue of regulation in the peer‐to‐peer finance industry. [ABSTRACT FROM AUTHOR]

This study examines design principles for how to display financial information about a consumer loan that supports locating a value (e.g., What is the annual percentage rate (APR) for an 18-month loan?), comparing two values (e.g., Is the APR for a 24-month load greater than for an 18-month loan?), or subtracting two values (e.g., What is the difference in the APR for a 24-month load and an 18-month loan?). One hundred and thirty-three college students carried out these three types of tasks at a banking site that displayed information as a list (e.g., listing the value for interest rate, monthly payment, insurance cost, APR, amount financed, and total cost for a given duration ranging from 6 to 48 months) or as one of three types of tables or matrices (containing values for each of six variables across one axis and each of eight loan durations across the other). Accuracy and response time on each of the three types of tasks was tallied for each of the four groups. Consistent with the principle of distraction minimization, the list was the best display for locating a value. Consistent with the principle of conjoint alignment, a vertical matrix (with loan duration across columns) or horizontal matrix (with loan duration across rows) was the best for comparing two values, but an interactive matrix was less effective. Consistent with the principle of canonical form, a vertical matrix (with loan duration across columns) was the best for subtracting two values. Overall, the best information display depended on the type of task, consistent with cognitive theories of information processing. [ABSTRACT FROM AUTHOR]

The paper evaluates the outcomes of the borrower-based macroprudential policy measures that were introduced in Estonia in 2015. The core of the analysis is the response of the credit market in 2016–2021 to the upper limit on the debt service-to-income ratio for new housing loans. The paper employs a novel data-driven approach based on the distribution of loan-level data, which does not need to account for the changes in the macroeconomic environment, and which allows the analysis to be made under assumptions that are more flexible than those usually used in the literature. The average number of borrowers affected, meaning those who were rejected or got a smaller loan than they wanted, is estimated to be on average around 11 per cent of the total number of new loans, which translates into roughly 10 per cent of the volume of new loans. The effect is fairly stable over the whole period despite the volume of housing loans growing in recent years. [ABSTRACT FROM AUTHOR]

Macroprudential regulation of the banking system is a significant instrument for ensuring the financial stability of the state. Unsecured consumer lending is growing at a steadily high rate (in August-October 2022, the average monthly debt growth was 0.9%), and it remains a priority segment for banks because of its high margins. The share of unsecured consumer loans provided to borrowers with debt burden indicator (DBI) of more than 80% amounted to more than 32% in the third quarter of 2022 (28% in the second quarter of 2022). The share of consumer loans for a term of more than 5 years remains at a high level (15% in July-September 2022). The share of MFO loans issued to borrowers with a DBI of more than 80% was 41% in the second quarter of 2022 (38% in the first quarter of 2022). A further increase in the citizens' debt burden in the context of the economy restructuring may create additional macroeconomic risks. Problems of citizens with servicing loans and borrowings can lead to a reduction in demand in the economy, and losses of banks as a result of writing off "bad" loans can lead to a decrease in their ability to lend to the economy. To limit the risks associated with an increase in the citizens' debt burden, since the first quarter of 2023, the Bank of Russia has established direct quantitative restrictions on the issuance of certain types of credits (loans) and the application of increased buffers to risk coefficients if creditors exceed established limits. This article discusses the main approaches to implementation of the macroprudential policy of the Central Bank of the Russian Federation, its goals and instruments, and peculiarities of application in the current conditions. [ABSTRACT FROM AUTHOR]

Certain predominant Banks astride across India stayed esoterically stable while graphing nascent opportunities in retail banking sectors to intensify their financial values. And concomitantly, Money lending facilities i.e., Consumer Loan services are one of those offerings which are supposed to meet the customer's needs and requirements. But due to a lack of proper 'customer education', customers are made to purchase third-party financial products like mutual funds or insurance policies as mandatory at the time of disbursement of loans by the bank officials, which results in financial losses to the customers. The study is carried out to explore various loan facilities provided by major banks so that customers can avail of the loan facilities as per their requirements. We have studied and surveyed all consumer loan services available, and on the basis of certain parameters such as Interest Rates, Equated Monthly Installment (EMI), Processing Fee, Pre- Payment Charges, Charges for Late Payments of EMI, Cheques/ Electronic Clearing Service (ECS) Return Charges, Mandate Life Insurance Policies, etc. The study concluded that customers should be exposed to all types of terms and conditions regarding third-party financial products at the time of loan disbursement so that every customer can be protected from mis-selling third-party financial products. Therefore, this study will enhance the literature towards' customer education' and will spread awareness of certain terms and conditions to the customer at the time of disbursement of loans in their account. [ABSTRACT FROM AUTHOR]

The development of financial technology (Fintech) in emerging economies such as Indonesia has been rapid in the last few years, opening a great potential for loan businesses, from venture capital to micro and personal loans. To survive in such competitive markets, new companies need a robust credit-scoring model. However, building a reliable model requires large stable data. The challenge is that datasets are often small, covering only a few months (short-period datasets). Therefore, this study proposes a modified binning method, namely changing a variable's values into two groups with the smallest distribution differences possible. Modified binning can maintain data trends to avoid future shifting. The simulation was conducted using a real dataset from Indonesian Fintech, comprising 44,917 borrower-level observations with 396 variables. To match the actual conditions, the first three months of data were allocated for modeling and the remaining for testing. Implementing modified binning and logistics regression to testing data results in a more stable score band than standard binning. Compared with other classifier methods, the proposed method obtained the best AUC results on the testing data (0.73). In addition, the proposed method is highly applicable as it can provide a straightforward explanation to upper management or regulators. It is practical to use in real-case financial technology with short-period problems. [ABSTRACT FROM AUTHOR]

Copyright of Zeitschrift für Bankrecht und Bankwirtschaft is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We conducted a randomized, controlled trial with small- and medium-sized enterprises in Kenya to estimate the causal impact of an electronic payment (e-payment) technology on business finance. Using an encouragement design, we exogenously increased e-payment usage among a random subset of firms by relaxing adoption transaction costs and information barriers. Sixteen months after the intervention, we find that the e-payment technology increased access to mobile loans (in the number of loans as well as in the amount borrowed) by at least 50% (0.17 standard deviation), likely because of the reduction of information asymmetries brought by an increase in digital transactions. We find no effect of the e-payment technology on sales and profits, but we do find a reduction of sales volatility and precautionary investment, especially for smaller firms. This suggests that mobile loans help smaller firms cope with short-term negative shocks. We provide a stylized model of business finance that rationalizes these findings. This paper was accepted by Bruno Biais, finance. Funding: This paper was produced under the framework of the "Enabling Innovation and Productivity Growth in Low Income Countries (EIP-LIC/PO5639)" project, funded by the Department for International Development (DFID) of the United Kingdom and implemented by Tilburg University. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4821. [ABSTRACT FROM AUTHOR]

We present results from a randomized field experiment in Da Nang in Central Vietnam. We assess the take-up and impacts of a microcredit program that aims to increase the adoption of climate resilient housing among low-income urban households. Households were randomly assigned offers of either a loan and technical assistance package or a cash transfer with a smaller loan and technical assistance. We find large and significant impacts on the resilience of the new or retrofitted houses due to being offered the more generous incentive package. Households that were offered the cash transfer and a smaller loan, are three times as likely to accept. The difference in uptake, and therefore impact, of the two packages shows that there is a need for a subsidy in addition to the technical assistance in order to reach near-poor households. Previous public spending on typhoon relief indicates that such a subsidy could be covered by re-allocating funds from typhoon repairs to damage prevention through resilient housing. [ABSTRACT FROM AUTHOR]