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Jonathan Ansell - One of the best experts on this subject based on the ideXlab platform.
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time to profit scorecards for Revolving Credit
European Journal of Operational Research, 2016Co-Authors: Luis Javier Sanchezbarrios, Galina Andreeva, Jonathan AnsellAbstract:This paper defines and models time-to-profit for the first time for Credit acceptance decisions within the context of Revolving Credit. This requires the definition of a time-related event: A customer is profitable when monthly cumulative return is at least one (i.e. cumulative profits cover the outstanding balance). Time-to-profit scorecards were produced for a data set of Revolving Credit from a Colombian lending institution which included socio-demographic and first purchase individual characteristics. Results show that it is possible to obtain good classification accuracy and improve portfolio returns which are continuous by definition through the use of survival models for binary events (i.e. either being profitable or not). It is also shown how predicting time-to-profit can be used for investment planning purposes of Credit programmes. It is possible to identify the earliest point in time in which a customer is profitable and hence, generates internal (organic) funds for a Credit programme to continue growing and become sustainable. For survival models the effect of segmentation on loan duration was explored. Results were similar in terms of classification accuracy and identifying organic growth opportunities. In particular, loan duration and Credit limit usage have a significant economic impact on time-to-profit. This paper confirms that high risk Credit programmes can be profitable at different points in time depending on loan duration. Furthermore, existing customers may provide internal funds for the Credit programme to continue growing.
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monetary and relative scorecards to assess profits in consumer Revolving Credit
Journal of the Operational Research Society, 2014Co-Authors: Galina Andreeva, Luis Sanchez Barrios, Jonathan AnsellAbstract:This paper presents for the first time a relative profit measure for scoring purposes and compares results with those obtained from monetary scores. The suggested measure is the cumulative profit relative to the outstanding debt. It can also be interpreted as the percentage coverage against default. Monetary and relative measures are compared with both being estimated using direct and indirect methods. Direct scores are obtained from borrower attributes, while indirect scores are predicted using the estimated probabilities of default and repurchase. Results show that specific segments of customers are profitable in both monetary and relative terms. The best performing indirect models use the probabilities of default within 12 months on books. This agrees with existing banking practice of default estimation. Direct models outperform indirect models. Relative scores would be preferred under more conservative standpoints towards default because of unstable conditions and if the aim is to penetrate relatively unknown segments. Further ethical considerations justify their use in an inclusive lending context.
Galina Andreeva - One of the best experts on this subject based on the ideXlab platform.
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time to profit scorecards for Revolving Credit
European Journal of Operational Research, 2016Co-Authors: Luis Javier Sanchezbarrios, Galina Andreeva, Jonathan AnsellAbstract:This paper defines and models time-to-profit for the first time for Credit acceptance decisions within the context of Revolving Credit. This requires the definition of a time-related event: A customer is profitable when monthly cumulative return is at least one (i.e. cumulative profits cover the outstanding balance). Time-to-profit scorecards were produced for a data set of Revolving Credit from a Colombian lending institution which included socio-demographic and first purchase individual characteristics. Results show that it is possible to obtain good classification accuracy and improve portfolio returns which are continuous by definition through the use of survival models for binary events (i.e. either being profitable or not). It is also shown how predicting time-to-profit can be used for investment planning purposes of Credit programmes. It is possible to identify the earliest point in time in which a customer is profitable and hence, generates internal (organic) funds for a Credit programme to continue growing and become sustainable. For survival models the effect of segmentation on loan duration was explored. Results were similar in terms of classification accuracy and identifying organic growth opportunities. In particular, loan duration and Credit limit usage have a significant economic impact on time-to-profit. This paper confirms that high risk Credit programmes can be profitable at different points in time depending on loan duration. Furthermore, existing customers may provide internal funds for the Credit programme to continue growing.
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monetary and relative scorecards to assess profits in consumer Revolving Credit
Journal of the Operational Research Society, 2014Co-Authors: Galina Andreeva, Luis Sanchez Barrios, Jonathan AnsellAbstract:This paper presents for the first time a relative profit measure for scoring purposes and compares results with those obtained from monetary scores. The suggested measure is the cumulative profit relative to the outstanding debt. It can also be interpreted as the percentage coverage against default. Monetary and relative measures are compared with both being estimated using direct and indirect methods. Direct scores are obtained from borrower attributes, while indirect scores are predicted using the estimated probabilities of default and repurchase. Results show that specific segments of customers are profitable in both monetary and relative terms. The best performing indirect models use the probabilities of default within 12 months on books. This agrees with existing banking practice of default estimation. Direct models outperform indirect models. Relative scores would be preferred under more conservative standpoints towards default because of unstable conditions and if the aim is to penetrate relatively unknown segments. Further ethical considerations justify their use in an inclusive lending context.
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Modelling profitability using survival combination scores
European Journal of Operational Research, 2007Co-Authors: Galina Andreeva, Jake Ansell, Jonathan CrookAbstract:Abstract The paper presents the first empirical investigation of the relationship between present value of net revenue from a Revolving Credit account and times to default and to second purchase. The analysis is based on the data for a store card which is used to buy ‘white’ durable goods in Germany. It is demonstrated that there exists a relationship between the above given measures. It appears that there is a scope for improving profit if an application for a store card is assessed by using a model which estimates the revenue and includes the survival probability of default and the survival probability of second purchase (a survival combination model) rather than merely a static probability of default predicted by a logistic regression.
Douglas J Lamdin - One of the best experts on this subject based on the ideXlab platform.
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does consumer sentiment foretell Revolving Credit use
Early Childhood Education Journal, 2008Co-Authors: Douglas J LamdinAbstract:The rising level of consumer debt in the U.S. is well documented. Revolving Credit (Credit cards) has experienced this growth, with the level of outstanding Revolving Credit increasing by over 600% in inflation-adjusted dollars over the past three decades. The goal here is to gauge the extent to which consumer sentiment; namely, the University of Michigan Survey Research Center Index of Consumer Sentiment, has predictive power in explaining the aggregate use of Revolving Credit using time-series data. The results generally show that changes in the consumer sentiment measure are related to subsequent changes in Revolving Credit use.
Kyle F Herkenhoff - One of the best experts on this subject based on the ideXlab platform.
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The Impact of Consumer Credit Access on Unemployment
National Bureau of Economic Research, 2020Co-Authors: Kyle F HerkenhoffAbstract:Unemployed households' access to unsecured Revolving Credit (Credit cards) nearly quadrupled from about 12 percent to about 45 percent over the last three decades. This paper analyzes how this large increase in Revolving Credit has impacted the business cycle. The paper develops a general equilibrium business cycle model with search in both the labor market and in the Credit market. This generates a very rich and empirically plausible level of heterogeneity in work and Credit histories while at the same time permitting a tractable model solution. Calibrating to the observed path of Credit use between 1974 and 2012, I find that the large growth in Credit access leads to deeper and longer recessions as well as moderately slower recoveries. Relative to an economy with Credit fixed at 1970s levels, employment reaches its trough about 1 quarter later and remains depressed by up to .8 percentage points three years after the typical recession in this time period (e.g. employment is depressed by 2.8% rather than 2%). The mechanism is that when borrowing opportunities are easy to find, households optimally search for better-paying but harder-to-find jobs knowing that if the job search fails they can obtain Credit to smooth consumption. Despite longer recessions and slower recoveries, increased Credit card use enhances welfare by reducing consumption volatility and improving job-match quality.
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The Impact of Consumer Credit Access on Unemployment
The Review of Economic Studies, 2019Co-Authors: Kyle F HerkenhoffAbstract:Unemployed households’ access to unsecured Revolving Credit more than tripled over the last three decades. This article analyses how both cyclical fluctuations and trend increases in Credit access impact the business cycle. The main quantitative result is that Credit expansions and contractions have contributed to moderately deeper and more protracted recessions over the last 40 years. As more individuals obtained Credit from 1977 to 2010, cyclical Credit fluctuations affected a larger share of the population and became more important determinants of employment dynamics. Even though business cycles are more volatile, newborns strictly prefer to live in the economy with growing, but fluctuating, access to Credit markets.
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The Supply Side of Jobless Recoveries
SSRN Electronic Journal, 2013Co-Authors: Kyle F HerkenhoffAbstract:The fraction of unemployed households with Revolving Credit more than tripled between the late 1970s and the early 1990s, and new evidence suggests that close to 20% of unemployed households use Revolving Credit to replace lost income while as much as 40% default in response to job loss. Moreover, research by Chetty (2008) suggests that access to liquid assets is an important determinant of job finding. The natural question is, how has access to 'on-demand' Credit changed the way labor markets respond to downturns? After exploring the interaction between job loss/Credit markets in the data and describing the innate endogeneity associated with any reduced form answer, I build a new model that features risk averse agents who face both search frictions in the labor market (Menzio and Shi, 2011) and the Credit market (Eaton and Gersovitz, 1981). The model mechanism is that easy Credit conditions provide a safety net which incentivizes agents to search for better-paying but scarcer jobs. While this is welfare improving, the side effect is joblessness. Following a downturn, I find that an economy with easy Credit access experiences a 10% larger drop in employment per capita compared to an economy in which Credit is tight (e.g. a 2.2% drop in employment per capita with easy Credit access versus a 2% drop with tight Credit access). I argue that the model rationalizes a portion of jobless recoveries via supply side phenomenon.
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jobless recoveries and the Revolving Credit revolution preliminary
2013Co-Authors: Kyle F HerkenhoffAbstract:Access to Revolving Credit more than doubled between 1983 and 1992 among both employed and unemployed households, and new evidence suggests that close to 20% of unemployed households use Revolving Credit to replace lost income. Labor markets have also experienced sluggish recoveries following the 1991, 2001, and 2007 recessions. These two facts motivate the question posed in this study: how has access to 'on-demand' Credit changed the way labor markets respond to downturns? To answer this question, I build a model with risk averse agents who face both search frictions in the labor market and search frictions in the Credit market. In the model, easy Credit conditions provide a safety net that incentivizes agents to search for better paying jobs. Following a downturn, I find that an economy with easy Credit access experiences a 10% larger drop in employment per capita compared to an economy in which Credit is tight (e.g. a 2.2% drop in employment per capita with easy Credit access versus a 2% drop with tight Credit access).
Luis Javier Sanchezbarrios - One of the best experts on this subject based on the ideXlab platform.
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time to profit scorecards for Revolving Credit
European Journal of Operational Research, 2016Co-Authors: Luis Javier Sanchezbarrios, Galina Andreeva, Jonathan AnsellAbstract:This paper defines and models time-to-profit for the first time for Credit acceptance decisions within the context of Revolving Credit. This requires the definition of a time-related event: A customer is profitable when monthly cumulative return is at least one (i.e. cumulative profits cover the outstanding balance). Time-to-profit scorecards were produced for a data set of Revolving Credit from a Colombian lending institution which included socio-demographic and first purchase individual characteristics. Results show that it is possible to obtain good classification accuracy and improve portfolio returns which are continuous by definition through the use of survival models for binary events (i.e. either being profitable or not). It is also shown how predicting time-to-profit can be used for investment planning purposes of Credit programmes. It is possible to identify the earliest point in time in which a customer is profitable and hence, generates internal (organic) funds for a Credit programme to continue growing and become sustainable. For survival models the effect of segmentation on loan duration was explored. Results were similar in terms of classification accuracy and identifying organic growth opportunities. In particular, loan duration and Credit limit usage have a significant economic impact on time-to-profit. This paper confirms that high risk Credit programmes can be profitable at different points in time depending on loan duration. Furthermore, existing customers may provide internal funds for the Credit programme to continue growing.