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Naveed Chehrazi - The University of Texas at Austin, McCombs School of Business. Austin, TX, UNITED STATES

Naveed Chehrazi

Assistant Professor, Department of Information, Risk and Operations Management | The University of Texas at Austin, McCombs School of Business

Austin, TX, UNITED STATES

Information economics, system dynamics, and the banking and credit card industries

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Areas of Expertise (10)

Credit Cards

Information Economics

Probability and Statistics

System Dynamics

Pricing

Revenue Management

Optimal Control of Nonlinear Systems

Economics of Uncertainty

Stochastic Processes

Corporate Strategy

Biography

Assistant Professor Naveed Chehrazi joined the Department of Information, Risk, and Operations Management in July 2013 upon receiving his Ph.D. in management science and engineering at Stanford University. Chehrazi's doctoral dissertation and his current research focus on consumer behavior in the unsecured debt market.

Chehrazi's research combines tools from different disciplines including statistics, economics, and operations research to develop mathematical models that can explain and predict consumers' behavior in terms of their repayment pattern when they are in default.

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Education (3)

Stanford University: Ph.D., Management Science and Engineering 2013

Thesis: "Identification and Optimization of Stochastic Systems".

Stanford University: M.S., Management Science and Engineering 2008

Sharif University of Technology: B.Sc., Electrical Engineering 2005

Media Appearances (2)

New Model Predicts Delinquent Card Repayment

Banking Exchange  online

2015-05-26

University researchers claim to have identified a way to accurately predict which delinquent credit card accounts will repay an outstanding balance. This could help decisionmakers choose among methods of recovering past dues and chargeoffs.

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Model Predicts Which Delinquent Credit Card Holders Will Pay

UT News  online

2015-05-14

McCombs Assistant Professor Naveed Chehrazi and his co-author Thomas Weber from École Polytechnique Fédérale de Lausanne in Switzerland worked directly with a major credit card issuer to develop the Dynamic Collectability Score, which ranks delinquent account holders based on factors such as size of outstanding balance, mortgage status, past payment history, credit score, and external factors such as the performance of the stock market and the national unemployment rate.

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Articles (2)

Dynamic Valuation of Delinquent Credit-Card Accounts


Social Science Research Network

2015-02-15

This paper introduces a dynamic model of the stochastic repayment behavior exhibited by delinquent credit-card accounts. Based on this model, we construct a dynamic collectability score (DCS) which estimates the account-specific probability of collecting a given portion of the outstanding debt over any given time horizon. The model integrates a variety of information sources, including historical repayment data, account-specific, and time-varying macroeconomic covariates, as well as scheduled account-treatment actions.

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Monotone Approximation of Decision Problems


Operations Research

2010-07-07

Many decision problems exhibit structural properties in the sense that the objective function is a composition of different component functions that can be identified using empirical data. We consider the approximation of such objective functions, subject to general ...

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