Lending Market Research Articles

A multi-agent simulation of investment choice in the P2P lending market with bankruptcy risk

ABSTRACT A challenge for investors in P2P lending marketplaces is to find an effective allocation of their funds across different loans by assessing the widespread collapse of lending platforms and each loan’s default risk. This paper investigates risk-averse/risk-tolerant/risk-neutral investors’ and borrowers’ transaction behaviours, as well as P2P lending platforms’ operating mechanism. A Heterogeneous Investors Multi-Agent Model (HIMAM) is built to simulate agents’ reactions to variance in platform’s bankruptcy risk. This enables an assessment of changes in investors’ average return rates and investment decisions. This study finds that platform bankruptcy risk influences total investment amounts and average return rates. The correlation between the transaction fee and total investment amount presents as an inverted U-shape. Furthermore, there is a negative correlation between two-part tariffs and both investors’ average return rates and the number of investors. This is because two-part tariffs are dependent on investors’ transaction volumes. High two-part tariffs increase investors’ transaction costs. Additionally, considering bankruptcy and default risk, credit E are the most popular type of borrower because such borrower tradeoff higher risk for higher return; credits B and C are the least popular type of borrower.

Information Spillover through Private Lender Reports

This paper examines private information spillover from the lending market to markets for public securities. We find that information from private monthly reports to institutional lenders gradually spills over to the public equity market. We observe positive abnormal stock returns after firms provide favorable private reports. After unfavorable private reports, we find negative abnormal returns, as well as increased short interest. This private information leakage is striking and previously undocumented. We demonstrate how traders benefit from private information, as we show that they do not trade immediately upon receiving the private information. Instead, they time their trades to manage both the price impact and the risk of additional information arrival before the scheduled public release of their private information.

Information disclosure and the default risk of online peer-to-peer lending platform

• we extend the discussion of the role of information disclosure to P2P online lending market. • Higher level of disclosure is associated with lower default probability • The disclosure on audit information has highest influence on reducing default risk. • Longer loan maturity is related to lower probability of default. • The influence of interest rate and platform size is insignificant.

Pricing analysis of interconnected markets of housing, mortgage lending and insurance

Purpose This paper aims to investigate the problem of searching for the equilibrium in the housing market, the mortgage lending market and the insurance market in the process of selling the residential property. Three classes of markets are established in three modes, which reflect the interdependence of the firms’ interests in these markets through the parameters of their integration. The paper aims to determine the prices in these markets on the basis of the compromises among the conflicting interests of the related firms, and, in addition, to assess the rationality of integration for firms, which are participants in the process of selling the residential property. Design/methodology/approach On the basis of the revenue sharing contracts and the supply chain coordination methods, the optimization models of the housing realtor, the mortgage bank and the insurance company are developed. The models consider the interdependence of the firms’ interests, the monopolistic competition in these markets and the conditions of the firms’ individual rationality in the interaction process. Findings The results of the study are as follows. First, as a consequence of a decrease in the demand curves in monopolistic competition, the housing market, the mortgage market and the insurance market are interconnected, therefore, the optimization models of the firms in these markets are interdependent through the revenue sharing parameters. Second, in these markets the individual firms’ sales optimums are not identical, therefore, the interests of the firms are contradictory. Third, in the realtor-bank-insurer system, the equilibrium satisfies the condition of zero revenue sharing payments between the agents; additionally, the equilibrium prices in these markets are mutually independent. Fourth, in the disequilibrium, the prices in these markets are interrelated, i.e. the price in one market increases with the price in another market, if the payment is directed from the former to the latter, and vice versa. Research limitations/implications The results of the study are applicable in practice, if the markets demonstrate the decreasing demand curves and if the needs of buyers in related markets are interconnected. Practical implications The interaction between the realtor and the mortgage bank enables the realtor to raise its sales and the bank to increase in the number of loans, i.e. it leads to growth of their profits. The interaction between the insurer and the mortgage bank enables the insurer to increase in the number of policies and the bank to reduce the risk of lending, i.e. it leads to an increase in their profits. The identification of the individual firms’ sales optimums enables agents to determine the terms of the contracts of these interactions, which are compromises from the positions of each transaction participants. In addition, the firms’ optimums indicate the predictions of the equilibrium market prices. Originality/value In comparison with the studies in the contract theory framework, first, the mathematical description of the complicated (three-agent) system of interactions is proposed; second, the optimal choice non-linear models are developed, which take into account the non-linear demand functions in the monopolistic competition markets; third, the equilibrium of the agents with contradictory interests is investigated. In the later item, the authors establish that the revenue sharing contracts in the complimentary demands functions systems do not require the payments between the participants. Fourth, the authors prove that, in the equilibrium of these markets, the housing prices, the mortgage interest rates and the insurance rates are mutually independent and equal to the prices in the isolated markets.

Market discipline on bank bond issues through the lens of a new forward‐looking measure of loan quality

AbstractUsing unsecured bond spreads over the 2007 to mid‐2014 period, we test investors’ ability to price bank loan risk. We use a new measure of loan risk that incorporates forward‐looking information embedded in ratings assigned by external rating agencies to bank loan portfolios. Only Italian banks are required to systematically disclose this specific information. We find that investors do price forward‐looking information inherent in bank loan portfolios. This finding reflects the increase in risk perception following the sovereign debt crisis, which had the strongest effects on peripheral countries, with tensions in the lending market. Overall, these results suggest that our new forward‐looking measure provides an additional channel through which market discipline can operate.

Bank misconduct and online lending

We introduce a high quality proxy for bank misconduct that is constructed from Consumer Financial Protection Bureau (CFPB) complaint data. We employ this proxy to measure the impact of bank misconduct on the expansion of online lending in the United States. Using nearly complete loan and application data from the online lending market, we demonstrate that bank misconduct is associated with a statistically and economically significant increase in online lending demand at the state and county levels. This result is robust to the inclusion of bank credit supply shocks and holds for both broader and more narrowly-defined bank misconduct measures. Furthermore, we show that this effect is strongest for lower rated borrowers and weakest in states with high levels of generalized trust.

Bounded rationality in a P2P lending market

PurposeThis study seeks to provide a systematic analysis of bounded rationality expressed by individual lenders in a Peer-to-peer (P2P) lending market.Design/methodology/approach26,383 personal loan listings collected from Moneyauction in Korea, were analyzed with binary logit regression. 6 hypothesis based on bounded rationality theory were constructed and tested. Binary logit regression was employed as both dependent variables have binary characteristics and can thus be assigned values equal to 0 or 1.FindingsThe results confirm that individual P2P lenders make their funding decisions based on bounded rationality, arousing from cognitive limitations, incomplete information, and time constraints.Research limitations/implicationsBy adopting the theory of bounded rationality, this study attempts to prepare the theoretical background for an explanation of the decision behavior of individual lenders in a P2P lending market.Practical implicationsThe findings of this research emphasize the importance of the platform provider's role to facilitate the sustainable market growth of P2P lending as an alternative form of finance. As the rationality of individual lenders is bounded during their decision-making process according to the research findings, the platform provider must continuously adjust their decision criteria by referencing the cumulative loan repayment data.Originality/valueThis study attempts to identify for the first time the suboptimal decision making by individual lenders in a P2P lending market on the basis of bounded rationality theory.

How Credit Run Affects Asset Correlation and Financial Stability

This paper analyses the effect of soaring demand in the lending market shortly before a fi nancial crisis (hereinafter run). A credit run affects the asset correlation, which is one of the main parameters in the Internal Ratings-Based Approach (IRBA) of the Basel III framework. In the framework, these coefficients are predetermined and have not been recalibrated since their introduction in the Basel II Accord. This paper not only questions the assumption of a constant asset correlation, which is a fundamental part of the theoretical foundation of the IRBA, but also shows that a credit run increases the asset correlation value through a new approach. Thereby, this paper offers evidence that the asset correlations given in the IRBA are underestimated. In contrast to other asset correlation studies, this paper provides a new approach which is compatible with the foundation of the IRBA. Assuming asset correlations are calibrated correctly in the IRBA, a 2% downturn add-on may be adequate.

Retail Lending at Year-end 2019

At year-end 2019, high rates of the retail lending market were registered. This growth demonstrated increased accessibility of loans to households amid moderate inflation and stable financial state of households. Excessive banking sector’s liquidity was an additional trigger for this growth. Meanwhile, the excessive level of the debt burden can lead to losses in the banking sector, pose risks for the real sector of the economy, provoke adverse social consequences.

CREDIT MARKET DEVELOPMENT DIRECTIONS IN MODERN UKRAINIAN CONDITIONS

The article is devoted to the review of the current state, problems and directions of improving the activities of banking and microfinance organizations (MFIs) in the lending market. The methods of attracting customers to obtain loans are analyzed and the international experience of banking and non-banking organizations in the field of lending to the population is investigated. It was concluded that the economic development of the state not only implies, but also requires the development of market lending mechanisms that can not only provide banking institutions with a profit, but also ensure stable economic growth. In addition, it should be noted that there is a different focus on research in this area, as well as the lack of a unified approach to determining directions for improving lending competitiveness, and the mismatch between the chosen strategies for the real situation that has developed in Ukraine. It has been established that the largest share in the lending market belongs to consumer loans, classic loans to individuals, when borrowed funds are taken to pay for various necessities of life. At the same time, the presence of negative trends and factors affecting the stability and stability of the banking system has been identified, which makes it necessary to study and constantly monitor the status of consumer lending in order to identify potential problems. It is stated that at present, to expand the client market of credit institutions, it is necessary not only to expand the range of items provided under credit, but also to disseminate information and promote these services on the market. The main ways to attract customers to obtain loans and events that are actively used by credit institutions around the world are identified. The opinion of leading experts on the need to address a number of tasks to ensure the rights and legitimate interests of borrowers in the field of consumer lending is recorded. The principles of building a hierarchical system for working with loan applications are outlined. Keywords: lending, banking institutions, macro-financial organizations, borrower, money market, profitability, interest.

Price Transparency in OTC Equity Lending Markets: Evidence From a Loan Fee Benchmark

We study the effects of a price transparency shock in the Brazilian equity lending market, an over-the-counter market. Previously, the available loan fee benchmark was the mean loan fee of the past 15 trading days. On March 1, 2011, this interval was reduced to 3 days, significantly improving short-sellers' ability to predict current loan fees. We find that after the benchmark change, loan fees fell, lending volume increased, total lending revenue remained stable, high-cost lenders lost market share, and price efficiency increased. Our results suggest implementing price benchmarks in OTC markets can improve market quality.

The Failures of Peer-to-Peer Lending Platform Finance and Politics

We investigate the influence of financial and political factors on Peer-to-Peer (P2P) platform failures in the online lending market in China. Using a competing risk model for platform survival, we show that large platforms, platforms having listed firms as large shareholders and platforms with better information disclosure are less likely to go bankruptcy or run off with investors’ funds. More importantly, falling platforms are much less likely to run off in advance of important political events, but more likely to go bankruptcy or run off after these events. These effects are more pronounced, among platforms that are more politically connected, and platforms operating in provinces where local officials have close central-local political ties, and when there is a better local financial condition. Our study highlights the role of political incentives on government regulatory intervention of platform failures.

Does Geographical Discrimination Exist in Online Lending in China: An Empirical Study Based on Chinese Loan Platform Renren

Background: Online lending has developed rapidly in China in recent years, into a typical Internet financial model. China’s online lending related issues have received widespread attention from scholars. Methods: This study used 396,634 order data-points (935,037 original order data-points) from the Renren Loan website since its inception in January 2017. We used ordinary least squares (OLS) regression to study the problem of geographical discrimination in online lending in China, and we conducted two robust tests. Results: Studies have shown that significant geographical discrimination exists in China’s online lending market. From the perspective of the lender, different investment intentions exist for borrowers from various regions, thereby leading to variations in the success rates of loans. From the perspective of the borrower, the belief exists that borrowers from different regions will have varying interest rates because of the effect of geographical discrimination. Conclusion: We believe that geographical discrimination is due to the effects of the economic, financial, educational, and ethnic conditions of the borrower’s location on willingness to invest and the success rate of borrowing. However, borrowers’ self-discrimination is primarily related to economic and ethnic differences among provinces.

Regulatory Arbitrage in the Retail lending Market

The aim of the article is to analyze the features of regulatory arbitrage between credit and microfinance organizations in the retail lending market in Russia and to develop proposals to improve existing regulations on the activities of professional lenders. The work employed the methods of analysis, synthesis, generalization, as well as comparative legal research. The author found that regulatory arbitration might aim to get benefit from imperfect legislation. Signs of regulatory arbitration may indicate the inefficiency and redundancy of current legislation concerning the regulation of consumer lending. The author developed the following recommendations : to reduce redundant regulation regarding the limits of the full loan value for point-of-sale loans and installment loans; to switch to licensing system of financial organizations, considering the scale of their activities and the produced risks.

A Revolution in Progress: Regulating P2P Lending Platforms

Peer-to-peer (P2P) lending, defined broadly as the use of non-bank online platforms that match borrowers with lenders, is arguably one of the most important innovations in the area of alternative finance. It changes the way lenders and borrowers interact, reconstructs the credit market by driving massive disintermediation, and reshapes our general understanding of financial systems. This Article analyzes the current state of the P2P lending market with the goal of developing policy recommendations to facilitate the safe growth of this important market segment. It starts by providing an extensive overview of the P2P lending market from four different perspectives: the financial intermediary role of the platforms, the characteristics of the market, benefits and risks faced by market participants, and its regulation in leading jurisdictions. This descriptive analysis demonstrates how the P2P lending market has changed over time and identifies recent trends, risks, and challenges that require regulatory attention. In light of this analysis, the Article then proceeds to develop three policy recommendations. First, it shows that P2P lending platforms, originally designed to serve as online marketplaces that only match lenders with borrowers, have gradually evolved into new financial intermediaries that perform various brokerage activities and provide tools intended to help lenders manage their credit risks. It then argues that regulation should be modified to better suit this new financial intermediary role and discusses key considerations. Second, the Article proposes imposing consistent disclosure standards tailored to the characteristics of different types of P2P lending platforms. It presents specific examples of such disclosure requirements and provides justifications for imposing them. Finally, the article outlines key concerns related to the increasing involvement of institutional actors in P2P lending platforms — adverse selection among different types of lenders and growing financial stability risks — and discusses their regulatory implications.

ТЕНДЕНЦІЇ РОЗВИТКУ ІПОТЕЧНОГО КРЕДИТУВАННЯ В УКРАЇНІ

У статті висвітлено результати аналізу сучасного стану, ключові проблеми та перспективи розвитку іпотечного кредитування в Україні. Представлено порівняльну характеристику умов надання іпотечних кредитів в Україні та країнах Європейського Союзу, основні показники ринку іпотечного кредитування в Україні, динаміку змін іпотечного банківського кредитування за період з 2013 по 2018 роки. На основі окреслених проблем, запропоновано конкретні ефективні заходи їх подолання для зміцнення позицій перспективного розвитку іпотечного кредитування в Україні.

A multi-objective instance-based decision support system for investment recommendation in peer-to-peer lending

Peer-to-peer (P2P) lending has attracted many investors and borrowers since 2005. This financial market helps investors and borrowers to invest in or get loans without a traditional financial intermediary. Investors in the P2P lending market are allowed to invest in multiple loans instead of financing one loan entirely, so investment decision-making in P2P lending can be challenging for lenders because they are not usually expert in loan investing. The goal of this paper is to propose a data-driven investment decision-making framework for this competitive market. We use the artificial neural network and logistic regression to estimate the return and the probability of default (PD) of each individual loan. The return variable is the internal rate of return (IRR). Moreover, we formulate the investment decision-making in P2P lending as a multi-objective portfolio optimization problem based on the mean-variance theory by the use of the non-dominated sorting genetic algorithm (NSGA2). To validate the proposed model, we use a real-world dataset from one of the most popular P2P lending marketplaces. In addition, our model is compared with a single-objective model and a profit-based approach. Throughout the experiment, the empirical results reveal that our multi-objective model in comparison with the single-objective model can improve a lender's investment decision based on both objectives of investments. It means that while the return increases, the risk decreases, simultaneously. On the other hand, it is concluded that the profit scoring model leads to a more profitable investment but with a high level of risk. Finally, a sensitivity analysis is done to check the sensitivity of our model to the total investment amount.

Dynamic Equilibrium with Costly Short-Selling and Lending Market

We develop a tractable model of costly stock short-selling and lending market within a familiar dynamic asset pricing framework. The model addresses the vast empirical literature in this market and generates implications that support many of the empirical regularities. In the model, investors’ belief disagreement leads to the presence of stock lenders and short-sellers. To borrow stock shares, short-sellers pay shorting fees to lenders. Our main results for a costly-to-short stock in equilibrium are as follows. The shorting fee increases in belief disagreement. The stock price is positively, while its risk premium is negatively related to its shorting fee. The stock volatility is increased due to costly short-selling. More notably, the short interest increases in shorting fee and predicts future stock returns negatively. Higher short-selling risk can be associated with lower stock returns and less short-selling activity. We further apply our model to the recent GameStop episode and consistent with observed patterns, we find the shorting fee and stock price to increase and short interest to reduce significantly in response to a new large stock demand.

Why does regional information matter? evidence from peer-to-peer lending

In this paper, we study regional discrimination in a peer-to-peer lending scenario and provide novel empirical evidence for theories of soft information collection and information cost. We find that the regional information matters for borrowers' funding probabilities and that discrimination is profit-oriented or taste-oriented depending on the specific region. Moreover, using borrowers' birthplace as an instrumental variable, we find no evidence of genuine discrimination based purely on region in the peer-to-peer lending market.

Combining multiple probability predictions in the presence of class imbalance to discriminate between potential bad and good borrowers in the peer-to-peer lending market

Credit risk scoring predictions represent an effective guide for lenders to discriminate between potential good (who will repay the loan) and bad (who will default) borrowers in the online social lending market. A common characteristic of such a market is a lower percentage of defaulted borrowers than non-defaulted borrowers; thus, the sample is class imbalanced. Class imbalance may affect the accuracy of default predictions, as classifiers tend to be biased towards the majority class (good borrowers). We analyse the default prediction performance when combining class rebalancing methods with different regression and machine learning techniques. We also propose to combine multiple probability predictions to improve the predictive performance. The analysis is based on a book of loans (with a three-year term) funded in the 2010–2015 period though the online platform of Lending Club. The results show that some measures of predictive accuracy tend to improve when the scoring models are trained using a rebalanced, rather than an imbalanced sample, except when the extreme gradient boosting approach is applied. Finally, we find that combining multiple probability predictions via regularised logistic regression may help to improve the predictive accuracy.