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Assessing affordability using random effects models of income and consumption growth

Assessing affordability using random effects models of income and consumption growth
Assessing affordability using random effects models of income and consumption growth
In many countries, regulations put affordability assessment at the centre of responsible lending. In banking practice, though, an applicant’s affordability (ability to repay a loan) is often checked using a simple, static approach based on their current income and consumption as well as their existing debts. Introducing dynamics into consumer risk models is one of the current challenges in credit scoring. In this research, a theoretical framework for dynamic affordability assessment is proposed. Affordability is defined here as a function that assigns to each possible instalment amount a probability of the applicant defaulting over the loan repayment period. Consequently, affordability assessment means estimation of this function. Both income and consumption are allowed to vary over time and their changes are described with random effects models for panel data. The model formulas are derived from the economic literature. Consumption is described with a log-linearized version of the Euler equation. On the basis of the models a simulation is run for a given applicant. In each iteration of the simulation, the predicted income and consumption time series are generated. For each pair of the generated time series, the applicant’s ability to repay is checked over the life of the loan and for all possible instalment amounts. As a result, a probability of default is assigned to each amount and thus, affordability is assessed. Subsequently, the maximum affordable instalment can be identified. It can be determined as the highest possible amount for which affordability is less or equal to the adopted cut-off. The proposed dynamic approach is illustrated with an example based on artificial data. Assessing affordability over the loan repayment period as well as taking into account variability of income and expenditure over time are in line with recommendations of the Office of Fair Trading (OFT) and the Financial Services Authority (FSA).
Bijak, Katarzyna
5130b6b9-fbf1-44e8-9106-1dd69c6692a6
Thomas, Lyn C.
a3ce3068-328b-4bce-889f-965b0b9d2362
Mues, Christophe
07438e46-bad6-48ba-8f56-f945bc2ff934
Bijak, Katarzyna
5130b6b9-fbf1-44e8-9106-1dd69c6692a6
Thomas, Lyn C.
a3ce3068-328b-4bce-889f-965b0b9d2362
Mues, Christophe
07438e46-bad6-48ba-8f56-f945bc2ff934

Bijak, Katarzyna, Thomas, Lyn C. and Mues, Christophe (2013) Assessing affordability using random effects models of income and consumption growth. Credit Scoring and Credit Control XIII Conference, United Kingdom. 28 - 30 Aug 2013.

Record type: Conference or Workshop Item (Other)

Abstract

In many countries, regulations put affordability assessment at the centre of responsible lending. In banking practice, though, an applicant’s affordability (ability to repay a loan) is often checked using a simple, static approach based on their current income and consumption as well as their existing debts. Introducing dynamics into consumer risk models is one of the current challenges in credit scoring. In this research, a theoretical framework for dynamic affordability assessment is proposed. Affordability is defined here as a function that assigns to each possible instalment amount a probability of the applicant defaulting over the loan repayment period. Consequently, affordability assessment means estimation of this function. Both income and consumption are allowed to vary over time and their changes are described with random effects models for panel data. The model formulas are derived from the economic literature. Consumption is described with a log-linearized version of the Euler equation. On the basis of the models a simulation is run for a given applicant. In each iteration of the simulation, the predicted income and consumption time series are generated. For each pair of the generated time series, the applicant’s ability to repay is checked over the life of the loan and for all possible instalment amounts. As a result, a probability of default is assigned to each amount and thus, affordability is assessed. Subsequently, the maximum affordable instalment can be identified. It can be determined as the highest possible amount for which affordability is less or equal to the adopted cut-off. The proposed dynamic approach is illustrated with an example based on artificial data. Assessing affordability over the loan repayment period as well as taking into account variability of income and expenditure over time are in line with recommendations of the Office of Fair Trading (OFT) and the Financial Services Authority (FSA).

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More information

e-pub ahead of print date: 2013
Venue - Dates: Credit Scoring and Credit Control XIII Conference, United Kingdom, 2013-08-28 - 2013-08-30
Organisations: Centre of Excellence for International Banking, Finance & Accounting

Identifiers

Local EPrints ID: 361322
URI: https://eprints.soton.ac.uk/id/eprint/361322
PURE UUID: a4abdbce-8290-41e4-84cd-5d726fea39f8

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Date deposited: 22 Jan 2014 15:00
Last modified: 18 Jul 2017 03:04

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