Credit Risk Aversion Model (CRAM)During Economic Downturns and Recovery (original) (raw)

Forecasting and explaining aggregate consumer credit delinquency behaviour

International Journal of Forecasting, 2012

We model aggregate delinquency behaviour for consumer credit (including credit card loans and other consumer loans) and for residential real estate loans using data up until 2008. We test for cointegrating relationships and then estimate short run error correction models. We find evidence to support the portfolio explanations of declines in credit quality for consumer and for real estate loans, but support for the reduced stigma explanation was restricted to real estate loans. Evidence supportive of household-level explanations of irrational borrowing and unexpected net income shocks was found for consumer and real estate loans, but evidence of strategic default was restricted to the volume of consumer loans and real estate loans, and not for credit cards. We also found that the error correction model gave forecasts of the volume of delinquent consumer debt which were of an accuracy comparable to that of an ARIMA model.

Estimating the utility value of individual credit card delinquents

Expert Systems With Applications an International Journal, 2009

Excessive issue of credit cards has contributed to increased credit card delinquencies, which have become a burden for credit card companies. In such a negative situation, companies should build and use models to estimate maximum profits from credit card delinquents. However, traditional classification models used to classify customers into good or bad groups are not useful in estimating profits from credit card delinquents. Therefore, this paper suggests two models to estimate the utility value of individual credit card delinquents. After showing that the best classification model does not necessarily result in the best utility model, we explain a model that could be used to estimate utility value of individual credit card delinquents. Such models are expected to give much more value to the credit card companies than the traditional classification models.

Time will tell: behavioural scoring and the dynamics of consumer credit assessment

IMA Journal of Management Mathematics, 2001

This paper discusses the use of dynamic modelling in consumer credit risk assessment. It surveys the approaches and objectives of behavioural scoring, customer scoring and profit scoring. It then investigates how Markov chain stochastic processes can be used to model the dynamics of the delinquency status and behavioural scores of consumers. It discusses the use of segmentation, mover-stayer models and the use of second and third order models to improve the fit of such models. The alternative survival analysis proportional hazards approach to estimating when default occurs is considered. Comparisons are made between the ways credit risk is modelled in consumer lending and corporate lending.

Establishment of the Credit Risk Database

Routledge eBooks, 2019

The views expressed in this paper are the views of the author and do not necessarily reflect the views or policies of ADBI, ADB, its Board of Directors, or the governments they represent. ADBI does not guarantee the accuracy of the data included in this paper and accepts no responsibility for any consequences of their use. Terminology used may not necessarily be consistent with ADB official terms. Working papers are subject to formal revision and correction before they are finalized and considered published.

Anatomy of the Credit Score 1

2013

This paper addresses the question of what determines a poor credit score. We compare estimated credit scores with measures of impulsivity, time preference, risk attitude and trustworthiness, in an effort to determine the preferences that underlie credit behavior. Data are collected using an incentivized decision making lab experiment, together with financial and psychological surveys. Credit scores are estimated using an online FICO credit score estimator based on survey data supplied by the participants. Preferences are assessed using a survey measure of impulsivity, with experimental measures of time and risk preferences, as well as trustworthiness. Controlling for income differences, we find that the credit score is correlated with measures of impulsivity, time preference, and trustworthiness.

Intensity models and transition probabilities for credit card loan delinquencies

European Journal of Operational Research, 2014

We estimate the probability of delinquency and default for a sample of credit card loans using intensity models, via semi-parametric multiplicative hazard models with time-varying covariates. It is the first time these models, previously applied for the estimation of rating transitions, are used on retail loans. Four states are defined in this non-homogenous Markov chain: up-to-date, one month in arrears, two months in arrears, and default; where transitions between states are affected by individual characteristics of the debtor at application and their repayment behaviour since. These intensity estimations allow for insights into the factors that affect movements towards (and recovery from) delinquency, and into default (or not). Results indicate that different types of debtors behave differently while in different states. The probabilities estimated for each type of transition are then used to make out-of-sample predictions over a specified period of time.

Office of the Comptroller of the Currency- Credit Risk Analysis Division

2012

Mounting foreclosures and recent disclosures of abusive lending practices have led many states to adopt new anti-predatory lending laws. Researchers have examined the impact of such laws on credit flows and the cost of credit. This research extends the literature by examining if the market responded to these laws by substituting different mortgage products for those restricted by antipredatory lending provisions. The evidence indicates that the new laws were effective in restricting loans with targeted characteristics and that the market substituted other product types to maintain affordability in the face of these restrictions.

What Explain Credit Defaults? A Comparative Study

SSRN Electronic Journal, 2000

The paper argues that although key improvements in credit risk modelling have been made -motivated by Basel-II capital adequacy standard -yet the current turmoil in the global credit markets couldn't be forecasted and subsequently avoided. The aim of the study is to investigate the cyclical implications of aggregate defaults in an economy. The approach used here is to construct a macroeconomic credit model that provides a basis to perform scenario analysis. Within this framework, investigation is based on comparing two countries, a relatively immune economy from the current global crisis -Australia and the worst affected economy -USA. The key questions to solve are which macroeconomic variables are important for each country and the impact adverse macroeconomic shocks will induce to it. The analysis is based on quarterly data from 1995Q1 to 2009Q2 for both the countries. The results show that the same set of macroeconomic variables indicates different default rates for the two countries and that the US economy is much more susceptible to adverse macroeconomic shocks than Australian economy.