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Behavioural Segment Based Stress Testing Using Markov Chain

ABSTRACT

Stress testing involves assessing a bank’s ability to stay solvent in case of ‘stressed’ macro-economic scenarios. Banks are expected to create a response mechanism in case an economic distress were to occur.

The current approaches to stress testing are applied with more focus on capital requirement. The primary approaches to stress testing are Sensitivity Analysis and Scenario Analysis. Application of both these approaches, under capital computation focus, captures and quantifies movement of portfolio across risk grades.

There is a gap between regulatory requirements and outcomes of existing approach to stress testing. This gap relates to the ability to make stress testing output actionable for the bank from a customer life-cycle management perspective.

The paper discusses how behavior based risk transition model can be built to overcome the above challenge based on a 3 step approach:

  • Segment customers on the basis of their behavior
  • Record the transitions in customer behavior and assign probabilities using Markov chain
  • Model relationship of these transitions to capture impact of relevant macro-economic variables

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