Local Concentration in the Small Business Lending Market and Its Relationship to the Deposit Market

This note analyzes competition and concentration in the small business lending market using data obtained from Community Reinvestment Act (CRA) disclosures and data on local branches from the Federal Deposit Insurance Corporation's (FDIC) Summary of Deposits (SOD). In 1963, the Supreme Court defined the product market for commercial banking.

Factors related to the failure of FDIC-insured US banks

Purpose This study aims to analyze the factors related to the failure of 535 Federal Deposit Insurance Corporation (FDIC)-Insured United States banks in conjunction with the 2008 financial crisis. Design/methodology/approach The research consists of an analysis of the following three five-year partitions: pre-crisis (2002–2006), crisis (2007–2011) and post-crisis (2012–2016). The main hypothesis is that the factors explaining bank failures vary by period. Using logistic regression analysis, the authors identify the desirable models by period based on three model selection strategies. Findings Liquidity and non-risk-based capital ratios are important explanatory factors in all three periods. As the authors can see from the results, when comparing the full period (2002–2016) and the three five-year period partitions (2002–2006, 2007–2011 and 2012–2016), the ratios change from period to period, but they measure the same financial areas of concern in different contexts as follows: liquidity, leverage/risk exposure and capital adequacy. Risk-based capital ratios are not effective predictors of bank failures. Originality/value Recent academic studies have analyzed bank failures during periods that cover the years before, during and after the crisis, but most of these studies discuss bank failures in the forecasting context only. This study includes an analysis of failure determinants during pre-crisis, crisis and post-crisis subperiods based on the FDIC monitoring system of bank failures and identifies what ratios are more relevant during each period and how they change from period to period.

Agricultural loan delinquency prediction using machine learning methods

The recent economic downturn in the agricultural sector that started in 2013 has caused some concerns for farmers’ repayment capacity, which raises the need for precise prediction of financial stress in the agricultural sector. Machine learning has been shown to improve predictions with large financial data, however, its application remains limited in the agricultural sector. In this study, we approximate financial stress by agricultural loan delinquency, and predict it by employing a logistic regression and several machine learning methods. The main datasets include the Call Reports and Summary of Deposits from the Federal Deposit Insurance Corporation (FDIC). Our results show that ensemble learning methods have the best performance in prediction accuracy, with improvement of 26 percentage points at most and that the Naïve Bayes classifier is the best method to maintain the lowest cost from false predictions when the failure of identifying potentially high-risk loans is very costly. From the perspective of banks, while there are important benefits to using machine learning, the bank-level costs are also important considerations that may lead to different choices of machine learning methods.

Examining the Relationship between Land Values and Credit Availability

Increased credit availability facilitates land acquisition, but higher land values also hinder it. We investigate the impact of credit availability on land values, after regulatory changes in the lending system. We build an index of increased credit availability using Federal Reserve and Federal Deposit Insurance Corporation data. County-level panel fixed effects estimations are performed controlling for land value determinants, credit availability, and county-level macroeconomic factors. We find that estimating the effects of credit availability separately masks its total effect. Results show a 0.1 change in the index for increased credit availability is associated with 1.64–1.96% increase in land values.

The Risk Assessment Enhancement Process at the Federal Deposit Insurance Corporation

Supervisory banking institutions are often daunted by the volume and complexity of the data received on a regular basis from filer banks. Chief technology officers and data strategists face challenges as they strive to implement a technology that could facilitate the data collection and processing to produce secure, timely and reliable information for decision making purpose. Technology selection might be a concern for adopting government agencies, but the methodology of developing and implementing technologies could present a bigger challenge. This is due to the fact that government agencies may not adapt easily to new technologies in a timely fashion or accommodate further developments to their current systems while operating under strict budget. To strengthen its bank supervisory role and develop its bank examination applications, the FDIC decided to adopt The Rational Unified Process System Methodology, known as the RUP®. The chapter examines how the FDIC followed the RUP® to develop an existing bank examination tool application to support its risk assessment process.

Who Determines Customer Property

Title II of the Dodd-Frank Wall Street Reform and Consumer Protection Act gives the government the Orderly Liquidation Authority (“OLA”) to seek the liquidation of failing financial companies with the appointment of the Federal Deposit Insurance Corporation (“the FDIC”) as receiver. When applied to securities broker-dealers, the OLA calls into question the incorporation of the Securities Investor Protection Act of 1970 (“SIPA”) that provides for the orderly liquidation of an insolvent broker-dealer under the oversight of the Securities Investor Protection Corporation (“the SIPC”). The result is a conflict of control between the FDIC and the SIPC in the event of an OLA broker-dealer liquidation and investor uncertainty regarding the incorporation of SIPA protections for customer property. Problematically, the OLA and its implementing rules leave the FDIC with discretion to modify SIPA protections for customer property.

Competitive aggressiveness, community banking and performance

PurposeThe purpose of this paper is to develop and empirically test a conceptualization of competitive aggressiveness (CA), a dimension of entrepreneurial orientation.Design/methodology/approachStructural equation modeling and hierarchical regression are employed on responses from 182 banks in the southwestern US Performance data on the banks are drawn from the US Federal Deposit Insurance Corporation's (FDIC's) Call reports.FindingsThe results indicate awareness, motivation and capability are antecedents of CA, which itself is positively related to increased market share and, in more dense markets, profitability.Practical implicationsAggressive firms exhibit certain routines that can lead to competitive actions, which assists performance in some contexts. Managers who wish to increase (or decrease) their firms' overall competitive posture can encourage (or discourage) employees from performing competitive routines such as monitoring their rivals or talking about their rivals' strategies.Originality/valueBy developing CA' conceptualization, the study advances the understanding of the antecedents of competitive behavior and makes it easier to study competition in smaller firms.

Origins of too-big-to-fail policy in the United States

This article traces the origin of too-big-to-fail policy in modern US banking to the bailout of the $1.2b Bank of the Commonwealth in 1972. It describes this bailout and those of subsequent banks through that of Continental Illinois in 1984. During this period, market concentration due to interstate banking restrictions is a factor in most of the bailouts and systemic risk concerns were raised to justify the bailouts of surprisingly small banks. Finally, most of the bailouts in this period relied on the Federal Deposit Insurance Corporation's use of the Essentiality Doctrine and Federal Reserve lending. A discussion of this doctrine is used to illustrate how legal constraints on regulators may become less constraining over time.

A case study of XBRL implementation and development at the Federal Deposit Insurance Corporation (FDIC)

Purpose The purpose of this paper is to examine the implementation and development of eXtensible Business Reporting Language (XBRL) at the Federal Deposit Insurance Corporation (FDIC). The investigation seeks to gauge the roles and experiences of the FDIC and its main stakeholders to determine their engagement in XBRL diffusion within their organizations. Design/methodology/approach This is an qualitative research approach that is driven by the use of an in-depth case study and supported by the use of semi-structured interviews. Findings The findings showcase the role played by the FDIC as the first US regulatory authority that implemented and developed Inline XBRL. In addition, the use of diffusion of innovation theory provides better understanding of each stakeholder’s issues, benefits and challenges based on their experience. Research limitations/implications The research does not examine the institutionalization of XBRL at the FDIC or its stakeholders. Therefore, future research could incorporate a different research design to capture the impact of the pressure resulting from the regulatory mandate. Practical implications The research offers practical insights into public information technology managers and policymakers at global government agencies which are either non-adopters of XBRL technology or current adopters and consider transitioning into Inline XBRL. Global stakeholders could learn from the US experience and develop better understanding of Inline XBRL applications and functionalities. Originality/value The originality of this research is driven by the FDIC’s experience as the first regulatory developer of Inline XBRL. As such, the case study is a best practice to future and current adopters who often navigate the nuisance of implementing new technologies and/or developing existing ones.

The US banking system: does the size of the institution matter to its economic-financial situation?

This paper analyzes the relationship between the size of the entities in the US banking system and their economic-financial situation. The objective of this study is to group different economic and financial variables of the entities together into factors that characterize the US banking system and identify and identify how the factors vary according to the size of the entities. To do this, we start from the values taken by 32 economic-financial and regulatory ratios, obtained directly from the Federal Deposit Insurance Corporation (FDIC), for a period between the first quarter of 1990 and the penultimate of 2016. With this data it is performed a factorial analysis that allows synthesizing the 32 variables in 7 factors and, at the same time, obtaining relationships between these variables and the size and between themselves. Finally, through a neural network, the previous factors are hierarchized according to the influence that the size of the entities exerts on them. Among the conclusions reached, it should be noted that the loan structure is the factor that best classifies the size. It also determines the existence of a negative ?profitability-solvency? relationship with larger entities, (Assets> $ 250 B.) and smaller ones (Assets <$ 100 M.), as well as demonstrating the existence of moral hazard and the need for regulation that limits said risk (because the largest entities are the least solvent and assume the most risks).