scispace - formally typeset
Search or ask a question
Proceedings ArticleDOI

Credit limit management using action-effect models

18 Jun 2010-pp 112-115
TL;DR: In this article, a new type of model (termed action-effect model) is proposed to study the effect of credit limit increase/decision making on the profitability of the portfolio.
Abstract: Management (i.e. initial allocation and subsequent increase / decrease) of credit limits is one of the most critical decisions related to credit card accounts. It affects a number of variables that have direct or indirect influence on the profitability of the portfolio. This paper proposes the use of a new type of model (termed action-effect model) to study the effect of credit limit increase / decrease actions. Complex interactions between conflicting variables like credit risk, probability of attrition, credit limit utilization and revenue generated are studied. The possibility of using simulation along with action-effect models to arrive at an ‘optimum’ credit limit for each credit card account in a portfolio is discussed.
Citations
More filters
Journal ArticleDOI
TL;DR: A dynamic reinforcement learning system that constantly adapts the threshold in response to live data feedback in order to maximize a company’s profits is developed.

15 citations

Posted Content
TL;DR: A data-driven approach to manage the credit limit intelligently by incorporating the diminishing marginal effect and a well-designed metric is proposed to properly measure the performances of compared methods.
Abstract: Nowadays consumer loan plays an important role in promoting the economic growth, and credit cards are the most popular consumer loan. One of the most essential parts in credit cards is the credit limit management. Traditionally, credit limits are adjusted based on limited heuristic strategies, which are developed by experienced professionals. In this paper, we present a data-driven approach to manage the credit limit intelligently. Firstly, a conditional independence testing is conducted to acquire the data for building models. Based on these testing data, a response model is then built to measure the heterogeneous treatment effect of increasing credit limits (i.e. treatments) for different customers, who are depicted by several control variables (i.e. features). In order to incorporate the diminishing marginal effect, a carefully selected log transformation is introduced to the treatment variable. Moreover, the model's capability can be further enhanced by applying a non-linear transformation on features via GBDT encoding. Finally, a well-designed metric is proposed to properly measure the performances of compared methods. The experimental results demonstrate the effectiveness of the proposed approach.

5 citations


Cites background from "Credit limit management using actio..."

  • ...[Dey, 2010] discussed the possibility of using simulation along with action-effect models to set the optimum credit limit for each account....

    [...]

Journal ArticleDOI
TL;DR: In this paper, the combined effects of credit limit management, and pricing actions on profitability using asystem of empirical behavioral models for the individual factors are investigated. But the authors focus on the combined effect of credit risk, probability of attrition, propensity to revolve, credit limit utilization and revenue generated.
Abstract: The profitability of any credit card portfolio is influenced by complex interactions between several conflictingfactors like credit risk, probability of attrition, propensity to revolve, credit limit utilization and revenuegenerated In this context, the allocation and maintenance of appropriate credit limits, and optimum pricing arethe most critical parameters, as they affect a number of these factors Going beyond previously reported workdealing with pricing and revenue optimization, and credit limit management in isolation, this paper proposes amethod of studying the combined effects of credit limit management, and pricing actions on profitability using asystem of empirical behavioral models for the individual factors; and discusses how simulation can be used toarrive at ‘optimum’ pricing and credit limit combinations for each credit card account in a portfolio

4 citations


Cites background from "Credit limit management using actio..."

  • ...on credit scoring have been reported by Chen et. al (2008), Yang and Duan (2008), Twala (2009), Lin (2009), Strokov (2009), Tebboth and Gadi (2009), Malik and Thomas (2009), and Dey (2009a)....

    [...]

  • ...Dey (2009b) proposes the use of a set of interacting models to study the effect of credit limit changes on profitability....

    [...]

Dissertation
01 Jan 2018
TL;DR: This document summarizes current capabilities, research and operational priorities, and plans for further studies that were established at the 2015 USGS workshop on quantitative hazard assessments of earthquake-triggered landsliding and liquefaction in the Central American region.
Abstract: .................................................................................................................................... 4

1 citations

References
More filters
Journal ArticleDOI

14,009 citations


"Credit limit management using actio..." refers methods in this paper

  • ...Though the concept of recognizing groups in a population was introduced in statistics by [1], [2] was the first to propose that the technique could be used to distinguish between good and bad loans....

    [...]

Journal Article
TL;DR: A wide range of statistical methods have been applied, though the literature available to the public is limited for reasons of commercial confidentiality as discussed by the authors, and particular problems arising in the credit scoring context are examined.
Abstract: Credit scoring is the term used to describe formal statistical methods used for classifying applicants for credit into "good" and "bad" risk classes. Such methods have become increasingly important with the dramatic growth in consumer credit in recent years. A wide range of statistical methods has been applied, though the literature available to the public is limited for reasons of commercial confidentiality. Particular problems arising in the credit scoring context are examined and the statistical methods which have been applied are reviewed.

791 citations

Journal ArticleDOI
TL;DR: Credit scoring is the term used to describe formal statistical methods used for classifying applicants for credit into ‘good’ and ‘bad’ risk classes, and particular problems arising in the credit scoring context are examined.
Abstract: SUMMARY Credit scoring is the term used to describe formal statistical methods used for classifying applicants for credit into 'good' and 'bad' risk classes. Such methods have become increasingly important with the dramatic growth in consumer credit in recent years. A wide range of statistical methods has been applied, though the literature available to the public is limited for reasons of commercial confidentiality. Particular problems arising in the credit scoring context are examined and the statistical methods which have been applied are reviewed.

786 citations


"Credit limit management using actio..." refers background in this paper

  • ...Much of the details of past research can be found in [3], [4], [5], [6] and [7]....

    [...]

Journal ArticleDOI
TL;DR: In this paper, the authors survey the techniques used to support credit scoring and behavioural scoring and discuss the need to incorporate economic conditions into the scoring systems and the way the systems could change from estimating the probability of a consumer defaulting to estimating the profit a consumer will bring to the lending organisation.

770 citations


"Credit limit management using actio..." refers background in this paper

  • ...Much of the details of past research can be found in [3], [4], [5], [6] and [7]....

    [...]

Book
16 Aug 2017
TL;DR: Lyn C. Thomas as discussed by the authors is a Professor of Management Science at the University of Southampton, UK and David B. Edelman is Credit Director of Royal Bank of Scotland, Edinburgh.
Abstract: From the Publisher: About the Author Lyn C. Thomas is a Professor of Management Science at the University of Southampton. Jonathan N. Crook is Reader in Business Economics at the University of Edinburgh. David B. Edelman is Credit Director of Royal Bank of Scotland, Edinburgh.

585 citations