Delegated monitoring in crowdfunded microfinance: Evidence from Kiva

We study the role of delegated monitoring in crowdfunded microfinance. We use data from Kiva, a crowdfunding platform, where crowds lend to borrowers through microfinance institutions (MFIs) instead of lending directly. These MFIs monitor debt contracts on behalf of crowds. We find that borrowers who are more intensely monitored by MFIs are more likely to repay crowdfunded loans on time. Monitoring is particularly important in reducing repayment problems of individual loans rather than group-based loans. Monitoring has a stronger impact in less competitive lending markets. We also find that when lending to borrowers, crowds are attentive to the loan-administering MFI's ability to monitor loans.     

Provisioning over the business cycle: Some insights from the microfinance industry

This paper investigates the drivers of provisioning in MFIs and their provisioning behaviour over the business cycle. Based on an international sample of MFIs extracted from the MIX database over the 2001–2014 period, we uncover a negative relationship between MFIs' provisioning and the business cycle. Our finding corroborates the fact that MFIs do not build their loan loss provisions (LLP) during economic booms when profit and earnings are high. Since they provision more during downturns, they are more likely to suffer from unexpected losses and experience failure. This is in sharp contrast with the current Basel III countercyclical buffer requirement suggesting that financial institutions, especially banks, should build sufficient buffer in booms so that they can avoid costly capital adjustment when the economy contracts. Deeper analyses suggest however that this behaviour mainly concerns profit-oriented and deposit-taking/regulated MFIs, with business model and target close to conventional banking. This suggests that bank-like and regulated MFIs' loan loss provisions follow similar behavioral patterns to those of the conventional banking sector during the boom-and-bust cycles.     

Morgan Stanley's Approach to Assessing Credit Risks in the Microfinance Industry

Growing investor interest in microfinance combined with strong demand from microfinance institutions (MFIs) for capital have caused the financial industry and rating agencies to seek more reliable and precise methods for assessing the risks of MFIs. Drawing on the work of various industry leaders as well as its own experience, Morgan Stanley's Microfinance Institutions Group has created a comprehensive internal credit analysis and rating methodology—one that, by producing global (foreign and local currency) scale ratings, enables its analysts to assess and compare risks both within the growing microfinance sector and relative to other sectors.     

Predicting SME loan delinquencies during recession using accounting data and SME characteristics: The case of Greece

The objective of this paper is the comparison of various credit‐scoring models (i.e. binomial logistic regression, decision tree, multilayer perceptron neural network, radial basis function, and support vector machine) in evaluating the risk of small and micro enterprises' (SMEs') loan delinquencies based on accounting data and applicants' specific attributes. Exploiting a representative large data set of SMEs' loans granted by a large Greek commercial bank in the expansion period, we track the evolution of SMEs' delinquencies over the recession period August 2010 to July 2012. This time frame encompasses a period of manageable levels of delays (early recession period: August 2011–July 2012) and a period when delays were increased to a very high degree (deep recession period: August 2011–July 2012). Comparison of the employed credit‐scoring models during the early recession period shows that the multilayer perceptron neural network produces the highest predicting capacity, followed by the support vector machine model. As the crisis deepens, the support vector machine model presents the highest predicting accuracy, followed by the decision tree and then the multilayer perceptron model. Generally, the predictive performance of all credit‐scoring models seems to be substantially reduced as the recession escalates. Our paper has important implications for the proper financing of SMEs given their importance for the European economy.     

Promoting Entrepreneurship at the Base of the Social Pyramid via Pricing Systems: A case Study

Historically, microfinance institutions (MFIs) have played a significant social role by helping people at the base of the socio‐economic pyramid escape from social exclusion through the creation of microenterprises. However, international banks have recently started competing in the microfinance sector. In this adverse environment, MFI management tools should be more innovative and technologically advanced to increase efficiency, solvency and profitability and to compete with commercial banks on equal terms. This study therefore strives to develop a credit‐risk management tool based on a multilayer perceptron (MLP) credit‐scoring model for a Peruvian MFI, and to calculate the capital requirements and microcredit pricing on both internal ratings‐based (IRB) and standardized approaches, analysing the impact of these models on the management of the MFI. Our findings show that the implementation of an IRB approach with default probabilities obtained from an MLP credit‐scoring model produces the best benefit by the MFIs in terms of higher accuracy (reduction of misclassification costs by 13.78%), lower capital requirements (in the range of 8.5–78%) and the best risk‐adjusted interest rates. Furthermore, with the establishment of interest rates adjusted to the real risk of each client, MFIs are fairer and more socially engaged by preventing economically viable low‐risk projects from becoming unviable due to excessive interest rates. This leads to the creation of more small businesses by people from the base of the socio‐economic pyramid and greater economic development and social cohesion. The IRB model should therefore be implemented to improve MFI solvency, profitability, efficiency, survival, management and social performance.     

Cheap Credit,Lending Operations,and International Politics: The Case of Global Microfinance

The provision of subsidized credit to financial institutions is an important and frequently used policy tool of governments and central banks. To assess its effectiveness, we exploit changes in international bilateral political relationships that generate shocks to the cost of financing for microfinance institutions (MFIs). MFIs that experience politically driven reductions in total borrowing costs hire more staff and increase administrative expenses. Cheap credit leads to greater profitability for MFIs and promotes a shift toward noncommercial loans but has no effect on total overall lending. Instead, the additional resources are either directed to promoting future growth or dissipated.     

微型金融机构使命漂移的实证分析——基于对湖北省恩施土家族苗族自治州的调研数据

本文利用SPSS17.0分析软件对恩施土家族苗族自治州的198份样本数据进行统计学分析和回归分析的结果表明,我国的微型金融机构(MFIs)出现了使命漂移的趋势。但MFIs使命漂移既有MFIs"利润驱动"的因素,也有贫困农户"主动放弃"和贷款给农户带来累积正面效应的因素。     

International diversification and Microfinance

International commercial banks, institutional investors, and private investors have become increasingly interested in financing microfinance institutions (MFIs). This paper investigates whether adding microfinance funds to a portfolio of risky international assets yields diversification gains. By using mean-variance spanning tests with short-sale constraints, we find that investing in microfinance may be attractive for investors seeking a better risk-return profile. Specifically, the analysis suggests that investing in MFIs from Latin America, or microfinance and rural banks yields more efficient portfolios. In contrast, adding MFIs from Africa or microfinance NGOs to a portfolio of international assets is not beneficial for a mean-variance investor.     

The determinants of MFIs’ social and financial performances in sub-Saharan Africa: has mission drift occurred?

This paper studies the determinants of microfinance institutions’ (MFIs) financial performance (FP: self-sustainability and profitability) and social performance (SP: depth of outreach), and examine the FP/SP tradeoffs they face. Based on a sample of 120 MFIs over the period 2000–2009, we use the random effects method to isolate the effect of fixed-time factors such as loan lending technique, legal status and location (sub-region) on MFIs’ behavior. We find that financial expenses, wages and portfolio quality, mainly influence MFIs’ financial performance whereas social performance is mostly influenced by lending methodology and institutional form, and to a lesser extent by location. The analysis of FP–SP shows that mission drift is a concern primarily for banks, mutual/cooperatives and individual lenders. The results question the trend toward microfinance commercialization since it weakens outreach without improving significantly self-sustainability and profitability.     

Religion of Islam and Microfinance: Does It Make Any Difference?

This study is the initial attempt to investigate first whether microfinance institutions (MFIs) perform differently in the OIC countries where Islam is the prevailing religion and second, how Islamic microfinance institutions are different (if any) from the conventional MFIs. To accomplish these objectives, we employ a dynamic difference and system-generalized method of moments estimators. Our findings tend to indicate that there are significant differences in the way Islamic MFIs performed and operated as compared to that of the conventional MFIs in certain regions. However, in other regions, there were no significant differences in operation and performance between the Islamic MFIs and Conventional MFIs. The study presents important insights for the Islamic microfinance managers and donors as well as the policy makers.     

Loan recommender system for microfinance loans: Increasing efficiency to assist growth

A majority of the world's population does not have access to basic financial services. Therefore, financial inclusion is gaining attention from different governments, Non-governmental Organizations and private institutions. Microfinance Institutions (MFIs) have made a significant impact in the field of financial inclusion. But this impact is just the tip of the iceberg and these institutions need to grow exponentially and have efficient processes to have a more meaningful impact. In this article we discuss the design and implementation of a decision support system to help the MFIs achieve that target. We discuss an adaptive loan recommender system that assists the MFIs in making a more informed decision and help them grow with minimum resources. The article also discusses the implementation of this system in one MFI in India and the observed impact and limitations of the system.     

Which Governance Mechanisms Promote Efficiency in Reaching Poor Clients? Evidence from Rated Microfinance Institutions

This paper evaluates the effectiveness of several governance mechanisms on microfinance institutions' (MFI) performance. We first define performance as efficiency in reaching many poor clients. Following the literature on efficiency in banks, we estimate a stochastic cost frontier and measure output by the number of clients. Therefore, we capture the cost minimisation goal and the goal of serving many poor clients, both of which are pursued by MFIs. We next explore the impact of measurable governance mechanisms on the individual efficiency coefficients. The results show that efficiency increases with a board size of up to nine members and decreases after that. MFIs in which the CEO chairs the board and those with a larger proportion of insiders are less efficient. The evidence also suggests that donors' presence on the board is not beneficial. We do not find consistent evidence for the effect of competition, and we find weak evidence that MFIs in countries with mature regulatory environments reach fewer clients, while MFIs regulated by an independent banking authority are more efficient.     

Scale economies and input price elasticities in microfinance institutions

We evaluate the efficiency of microfinance institutions (MFIs) using a structural approach which also captures these institutions’ outreach and sustainability objectives. We estimate economies of scale and input price elasticities for lending-only and deposit-mobilizing MFIs using a large sample of high-quality panel data. The results confirm conjectures that improvements in efficiency can come from the growth or consolidations of MFIs, as we find substantial increasing returns to scale for all but profitability-focused deposit-mobilizing MFIs. Our results support the existence of a trade-off between outreach and sustainability. All inputs are inelastic substitutes, but we find differences in own-price elasticities in lending-only and deposit-mobilizing MFIs.     

Climate transition risk in U.S. loan portfolios: Are all banks the same?

We examine banks' exposure to climate transition risk using a bottom-up, loan-level methodology incorporating climate stress test based on the Merton probability of default model and transition pathways from the Intergovernmental Panel on Climate Change (IPCC). Specifically, we match machine learning predictions of corporate carbon footprints to syndicated loans initiated in 2010–2018 and aggregate these to loan portfolios of the twenty largest banks in the United States. Banks vary in their climate transition risk not only due to their exposure to the energy sectors but also due to borrowers' carbon emission profiles from other sectors. Banks generally lend a minimal amount to coal (0.4%) but hold a considerable exposure in oil and gas (8.6%) and electricity firms (4.6%) and thus have a large exposure to the energy sectors (13.5%). We observe that climate transition risk profile was stable over time, save for a temporary (in some cases) and permanent (in others), reduction in their fossil-fuel exposure after the Paris Agreement. From the stress testing, the median loss is 0.5% of US syndicated loans, representing a decrease in CET1 capital of 4.1% when extrapolated to the whole balance sheet. The loss is twice as large in the 1.5°C scenarios (1.4%–2.1% of loan value, 12%–16% of CET1 capital) compared to the 2°C target (0.6%–1.1% of loan value, 5%–9% of CET1 capital) with significant tail-end risk (7.7% of loan value, 62% of CET1 capital). Banks' vulnerabilities are also driven by the ex-ante financial risk of their borrowers more generally, highlighting that climate risk is not independent from conventional risks.     

Effect of Corporate Governance on Performance of Microfinance Institutions: A Case from Pakistan

ABSTRACT

We aim to assess the effect of corporate governance on the financial, economic, and social performance of microfinance institutions (MFIs) in Pakistan. The sample comprises twenty-five MFIs and covers their performance over five years, 2005–09. The results of the study indicate that governance variables do have an influence on the performance (economic and social) and productivity of the MFIs in Pakistan. Larger boards inversely affect the economic performance but have a positive effect on outreach and productivity. Presence of female directors does not play any role in improving economic performance but positively affects outreach. Duality of chair with CEO is a negative contributor to performance, outreach, and productivity. Firm size, experience, regulation of MFIs, and nonprofit activities in lending have positive effects on performance outreach and productivity.     

Mortgage Lending,Default, and the Community Reinvestment Act

The Community Reinvestment Act (CRA) encourages banks to lend to low- and moderate-income individuals. This paper estimates the effect of the CRA on mortgage lending, exploiting variation in the set of banks whose lending performance is assessed in a given neighborhood due to redefinitions of Metropolitan Statistical Areas in 2003. Incorporating a typical tract into one additional banks' assessment area increased mortgage lending there by approximately 2%. Lending to low-income borrowers was particularly affected. While income-conditional default risk was little changed, CRA-induced loans were riskier than average, due to their borrowers' lower incomes.     

Syndicated Loan Announcements and Borrower Value

Announcements of syndication loans increase borrowers' shareholder wealth if they are revolving credit agreements but not if they are term loans. Share price responses to revolving credit announcements are positive and significant, whereas the wealth effect for term loans is negative and significant. The results show that announcements from both the financial press and commercial information providers can affect borrower share price reaction. Overall, single syndication announcements appear to be more newsworthy than multiple announcements reported in the financial press, and we find evidence of information leakage, post‐announcement drift, or both.     

Profit status of microfinance institutions and incentives for earnings management

We theorize that for-profit microfinance institutions (MFIs) have higher incentives to use earnings management techniques when compared to their not-for-profit counterparts. Indeed, we show empirically that, when facing a distress period, for-profit MFIs are more likely to recognize impairment loan loss provisions than not-for-profit ones in about 0.8% of assets. This is consistent with the notion that those institutions are employing “big bath” accounting practices. Finally, using the 2008 crisis as an exogenous shock and country-level recessions as an exogenous measure of distress, we replicate our results.     

Correlated Default and Financial Intermediation

Financial intermediation naturally arises when knowing how loan payoffs are correlated is valuable for managing investments but lenders cannot easily observe that relationship. I show this result using a costly enforcement model in which lenders need ex post incentives to enforce payments from defaulted loans and borrowers' payoffs are correlated. When projects have correlated outcomes, learning the state of one project (via enforcement) provides information about the states of other projects. A large correlated portfolio provides ex post incentives for enforcement. Thus, intermediation dominates direct lending, and intermediaries are financed with risk‐free deposits, earn positive profits, and hold systemic default risk.     

Is there an optimal microcredit size to maximize the social and financial efficiencies of microfinance institutions?

Financial intermediation theory posits that a smaller loan size triggers a higher cost per dollar lent. This leads to question whether microfinance can become a self-sustainable industry. Hence, in microfinance innovations like loans without collateral, progressive loans, solidarity groups and relational lending are employed to reduce asymmetric information costs, adverse selection, and moral hazard while serving the poorest people. Crucially, we find a non-linear U-shaped effect of loan size on financial and social efficiencies. This reconciles the two opposite strands of the literature, aligning microfinance and banking central principles. The major implication of this study is that, unlike banking, microfinance institutions can grant small size loans while simultaneously obtaining high levels of financial and social efficiency. Indeed, our findings do not support the widely debated mission drift assumption since loan size does not generate a trade-off between financial and social outcomes. Therefore, loan size is a core management variable.