Financial innovations are a common explanation of the rise in consumer credit and bankruptcies. To evaluate this story, we develop a simple model that incorporates two key frictions: asymmetric information about borrowers' risk of default and a fixed cost to create each contract offered by...

We develop an empirical framework for the credit risk analysis of a generic portfolio of revolving credit accounts and apply it to analyze a representative panel data set of credit card accounts from a credit bureau. These data cover the period of the most recent deep recession and provide the...

We propose a new approach to studying the pass-through of credit expansion policies that focuses on frictions, such as asymmetric information, that arise in the interaction between banks and borrowers. We decompose the effect of changes in banks' cost of funds on aggregate borrowing into the...

Neural networks have risen in popularity for a number of applications, also in quantitative finance. However, the low interpretability of their ‘black box' representation has always been a common criticism. Previous literature has attempted to provide a better understanding and visualisation...

The Current Expected Credit Loss (CECL) framework represents a new approach for calculating the allowance for credit losses. Credit cards are the most common form of revolving consumer credit and are likely to present conceptual and modeling challenges during CECL implementation. We look back at...

Over 80 percent of securitized loans consolidated back onto banks' balance sheets as a result of FAS 166/167 are revolving consumer loans, primarily credit card loans. In this paper, we examine the impact of FAS 166/167 on the credit card loan securitization. First, we document that the affected...

We propose a new approach to studying the pass-through of credit expansion policies that focuses on frictions, such as asymmetric information, that arise in the interaction between banks and borrowers. We decompose the effect of changes in banks' cost of funds on aggregate borrowing into the...

Using account level credit-card data from six major commercial banks from January 2009 to December 2013, we apply machine-learning techniques to combined consumer-tradeline, credit-bureau, and macroeconomic variables to predict delinquency. In addition to providing accurate measures of loss...

We examine the ability of policymakers to stimulate household borrowing and spending during the Great Recession by reducing banks' cost of funds. Using panel data on 8.5 million U.S. credit card accounts and 743 credit limit regression discontinuities, we estimate the marginal propensity to...