Lending Technologies Research Articles

The Costs of Better Lending Technology: The Decline of Small Businesses Lending

This paper evaluates how information technology (IT) improvements contribute to the decline of small business lending in the US commercial banking market from 2002 to 2017. I estimate a general equilibrium dynamic model with banks that differ in sizes and choose the level of transaction (hard information intensive) and relationship (soft information intensive) lending. The model shows that banks’ costs of evaluating borrowers’ hard information declined over this period by 46%, and small business loans fell by 7% (12% in the data). I find that banks’ higher reliance on IT to issue transaction loans is responsible for 37% of the decline in the data, and the consolidation caused by IT improvements caused 22% of the decline. Contrary to previous work, I find that when general equilibrium is considered, policy protecting small banks cannot increase small business lending.

The Real Effects of Financial Technology: Marketplace Lending and Personal Bankruptcy

We examine how financial technology affects household hardship in terms of personal bankruptcy. We exploit an exogenous source of variation in marketplace lending, a court verdict rendering above-usury loans issued by banks to Connecticut and New York residents null and void if the loans are sold outright to non-banks. We document a persistent rise in personal bankruptcies following the verdict and a decline in marketplace lending, particularly among low-income households. Marketplace loan defaults and other consumer credit by banks and finance companies remain unaffected, suggesting that increases in personal bankruptcy arise principally from reversing access to new lending technology.

Lending Technologies and Lending Relationships

We examine banks' choice between two costly instruments used to identify good loan applicants: direct screening by acquiring borrower-specific information and collateral requirements. We show that with longer relationships the preference for screening increases both in initial and in later periods. Total welfare is enhanced as a result of more efficient selection, and access to credit can be improved. The model explains the reduced incidence of collateral, and potentially higher interest rates in later periods for safer borrowers. The results are stronger under more intense bank competition. Our findings support policies conducive to enduring lending relationships.

Predictive Strength of Lending Technologies in Funding SMEs

Using a proprietary database of lending decisions (N = 9,898) for small and medium‐sized enterprises (SMEs), the paper investigates how banks cope with the adverse selection dilemma. Based on an intertemporal framework, we qualify incorrect and correct lending decisions of banks and investigate the power of lending technologies to predict errors and correct choices. Findings suggest that adverse selection can be better controlled by a durable bank–firm relationship, as well as by an atomistic loan decision process, at the local level. By contrast, a loan decision‐making process based exclusively on hard financial information about SMEs may lead to adverse selection errors.

Can Relationship Lending Substitute for a Weak Legal Environment?

Do creditor rights influence the use of relationship lending? With data from EFIGE, gathered during a 2010 survey spanning seven European countries, this article addresses this question. First, it determines that banks and firms are more willing to implement relationship lending technology in weak legal environments. Second, to explain these results, the authors demonstrate that relationship lending technology can complement poor creditor rights and, by doing so, assure contract completion between creditors and debtors. These results are robust across several tests

Hierarchy of bank loan approval and loan performance

This paper analyzes data from a regional Italian bank to provide new evidence on the relationship between who, within a bank, approves a loan and the subsequent performance of the loan. The size of the bank and its pool of clients, who are primarily small- and medium-size firms, comprises characteristics of both relationship-based and transaction-based lending technologies. Our key finding is that the probability of loan default increases as the loan approval decision is made at higher levels of the lending-decision hierarchy. This evidence supports the primacy of relationship-lending technology relative to transaction-based lending technology.

Lending technology and credit risk under different types of loans to SMEs: Evidence from China

This paper analyses lending to small and medium-sized enterprises (SMEs), including the lending technologies used and the default risks for loans of different types using loan data on Chinese unlisted SMEs from 2010 to 2013. We find that both credit loans and third-party-guaranteed loans are examples of transaction lending. However, due to the risk-sharing mechanism, the lending technology used by banks for third-party-guaranteed loans is not a common transaction lending technology. In terms of default risk, there is no significant difference between credit loans and collateralized loans. In contrast, the default risk for third-party-guaranteed loans is higher.

Augmented and virtual reality technologies: Bridging practice and research in the academic library

ABSTRACTThis paper offers practical insights and lessons learned from over five years of direct experience provisioning and supporting augmented and virtual reality equipment as lendable technology. A pragmatic exploration of one academic library's experience in the development, sustainability, and evolution of augmented and virtual reality technology and associated services. Analyzed and critiqued in comparison to traditional library materials and services, the novel library collection is bridging the gap between learning, research, and practice. Library support is proving to be critical path: from the initial development of the lending technology collections, through the collaborative development of mixed reality equipment, spaces, and software. Specific details associated with the library's current state of practice are shared, including specifics as to working systems for both the HTC Vive and Oculus Rift equipment on dedicated mobile workstations available throughout the library. Collaborations with departments including Computer Science & Engineering, as well as the School of Journalism, have proven to be a natural outcome of the library's support: joint effort resulting in the development of numerous dedicated mobile augmented and virtual reality software development stations throughout the library, and resultant exhibit development.

IS RELATIONSHIP LENDING STILL A MIXED BLESSING? A REVIEW OF ADVANTAGES AND DISADVANTAGES FOR LENDERS AND BORROWERS

AbstractRelationship lending is a common lending technology that is assumed to bring several benefits to small‐medium enterprises (SMEs) and to financial institutions that adopt it. Notably, it could reduce information asymmetries, permitting banks to offer better credit terms to the borrower. However, it also entails some costs for both sides. The empirical evidence so far has not been conclusive in determining under what conditions relationship lending can be beneficial or harmful. Most of the studies suggest that SMEs that engage in relationship lending benefit from more credit availability (especially during a financial crisis), and lower interest rates. This occurs when they are served by small banks, are geographically close to the lender, when the bank is adequately decentralized and when it is the dominant creditor of the firm. However, under certain circumstances, banks can extract rents from the borrower or be captured by him. In addition, the consequences and the future of relationship lending will be remarkably affected by the level of competition among banks, their ownership structure, the regulatory framework and the business model that banks will have to adopt accordingly.

Lending Technologies, Banking Relationships, and Firms’ Access to Credit in Italy: The Role of Firm Size

This paper analyses the role of lending technologies and banking relationships on firms’ credit access in Italy. Using EFIGE firm-level data, we show that the depth and strength of firm-bank relationships have heterogeneous effects on credit demand and rationing probabilities depending on the size of the borrower. Multiple banking relationships alleviate financial constraints for small firms, while borrowing from a large number of lenders hinders access to credit for large companies. Small and medium firms with a higher share of debt with the main bank have a lower probability of being credit denied, as debt concentration contribute to overcome opacity problems typical of SMEs. Long-lasting relationships, by reducing information asymmetries, significantly improves access to credit for small and large firms. Conversely, we find that medium-sized enterprises are more exposed to financing constraints as relationship duration increases, due to possible lock-in effects. Finally, firms maintaining banking relationships based on transactional technologies are more likely to be credit denied, while the use of relationship lending technologies improves credit availability for both small and large enterprises.

Lending Technologies and Community Banks: What Are the Effects on Italian Households’ Default Risk During Financial Turmoil?

Using data from the Survey on Italian Households’ Income and Wealth gathered by the Bank of Italy, I test the effect of relationship and transactional lending technologies on the probability of households becoming insolvent during the crisis. I find that both technologies help in reducing defaults, but the effect of transactional lending is stronger. However, the selection and monitoring processes improve when relationship and transactional lending are combined. Furthermore, I also find that a higher presence of community banks in local markets increases bankruptcies. This outcome is mainly driven by households living in small towns, where the competitive pressure from medium‐large banks is lower.

Bank Size and Lending Specialisation

Using micro‐level data on the entire population of business loans of a bank‐based economy, we empirically test some of the core predictions of the small and medium enterprise (SME) financing literature, examining banks’ lending specialisations in firm size and lending technologies. Rejecting the conventional belief that smaller banks focus more on relationship loans than larger banks, we find that relationship lending is equally common for small and large banks. However, supporting the SME finance theories on the organizational advantages of small banks, we find that smaller banks provide more access to relationship loans to small firms, though such loans are usually more expensive.

BORROWER CHARACTERISTICS AND RELATIONSHIP LENDING ON LENDING DECISION MAKING: A SURVEY OF LITERATURE

The purpose of this article was to explore and analyze the earlier findings and latest research-related on lending decision making. The review focuses on the borrower characteristic information and relationship lending on lending decision making. Previous research revealed that the borrower characteristic information produced through the so-called lending technology, and the characteristics of the borrower can be classified into two categories; qualitative characteristic and quantitative characteristics. The results of this review also showed that there were inconsistencies findings on the effects of the characteristics of the borrower and relationship lending on lending decision making. These finding inconsistencies allegedly influenced by organizational factors and banks loan officer psychological factors as decision makers in the lending decision making.

Financing for Small and Medium Enterprises: Do All Banks Apply the Same Lending Technologies?

Financing for Small and Medium Enterprises: Do All Banks Apply the Same Lending Technologies?

The Impact of the Banking Competition in Funding and Lending Markets on Lending Technology

Le recours aux techniques de credit scoring dans les décisions d’octroi de crédit bancaire s’est largement accru, au détriment des méthodes traditionnelles basées sur la relation clientèle. J’analyse le lien entre cette évolution et la concurrence bancaire, et ses conséquences sur l’efficience, dans un modèle de double concurrence dans lequel deux banques disposant de technologies différentes d’octroi de crédit se concurrencent à la fois sur un marché de fonds et sur deux marchés de crédit hétérogènes. La concurrence peut générer une inefficience lorsqu’une banque surenchérit sur le marché de fonds pour jouir d’un pouvoir de monopole sur tous les marchés de crédit en éliminant son concurrent disposant d’une technologie plus efficiente sur un marché de crédit. JEL codes: G21, D43, L13.

Borrowing Challenges for Minorities: How Lending Technologies Affect Discrimination in the SME Credit Market

Can relationship-lending technology be used to overcome discrimination, as the Allport’s (1954) contact hypothesis suggests? Or should minorities stay away from the bank? Using a sample of SMEs from the Survey of Small Business Finances 2003, this article shows that though relationship-lending technology generally reduces the spread and probability of the need to provide collateral for a loan, use of such technology actually leads to greater discrimination against minorities. Asians are the most negatively affected by this effect, followed by Afro-Americans and Hispanics. However, this effect occurs only when the length of the relationship is short; it tends to disappear when relationships are longer. With regard to the area in which a firm is located, there is less discrimination in areas with high minority population rates than in areas with low minority population rates. These results are robust with regard to the self-selection problem.

Debt Restructuring and the Role of Banks’ Organizational Structure and Lending Technologies

While the literature on debt restructuring usually assumes that banks behave uniformly towards distressed firms, we demonstrate that banks follow different strategies when they decide whether to take part in the workout process or not. Using a survey of Italian banks, we link this heterogeneity to banks’ internal organization and lending technologies (transactional versus relationship lending). The probability of debt restructuring is higher when the bank is geographically closer to the borrowing firm, relies more on soft information than on credit scoring (except when credit scoring is used for monitoring purposes) or adopts a decentralized structure.

Spatial competition in the banking system: Alternative lending technologies and collateral assets

We design a geographical model of banking to examine the optimal use of alternative collateral types and lending technologies: transaction lending, asset-based lending and fixed asset lending. The optimal lending technology and collateral asset are shown to depend on the project quality and bank-borrower distance. Sometimes unsecured lending is optimal. Both loan interest and the share of secured loans may increase or decrease with the bank-borrower distance depending on the collateral type and lending technology. Finally we explore how credit scoring and deregulation intensify competition through distant multimarket banks. The change improves the welfare of borrowers. Asset-based lending with local firms offers a competitive advantage for small local banks.

Lending Technologies and Community Banks: What are the Effects on Italian Householdss Default Risk During Financial Turmoil?

Using data from the Survey on Italian Households’ Income and Wealth gathered by the Bank of Italy, I test the effect of soft and hard information on households’ probability of becoming insolvent during the crisis. I find that both help in reducing defaults, but the effect of hard information is stronger. However, the selection and monitoring processes improve when soft and hard information are combined. Furthermore, I find that a higher presence of community banks in local markets increases bankruptcies. This outcome is mainly driven by households living in small towns, where the competitive pressure from medium-large banks is lower.

Firm size, credit scoring accuracy and banks’ production of soft information

Research on SME bank financing generally assumes that smaller firms are more opaque from a lender’s perspective. We propose that the discriminatory power of credit scoring models can be thought of as a proxy for firm opaqueness, given that when these models perform poorly, lenders must invest in the production of ‘soft information’ to supplement the financial data used in these models. Measuring the discriminatory power of probit default models across quintiles of the Irish SME size distribution, we show that our proxy for firm opaqueness increases monotonically as firms get smaller. This finding supports an assumption that is the starting point to a wide strand of literature on SME bank financing. Our findings can also be interpreted as providing an insight to the literature on the determinants of banks’ choice of lending technology. While smaller banks may, as found in a substantial previous literature, produce larger amounts of ‘soft information’ due to their organizational advantages, they may also do so out of necessity: hard-information-based default modelling is less effective among smaller firms, thereby forcing banks that lend to these borrowers to invest more in relationship banking technologies to retain competitiveness.