Symptomatic Performance Diagnosis

Remotely assess operational risk and evaluate issues across the customer lifecycle 


Credit risk is simply the assessment of the risk that a customer will default on payment for a product or services that has been provided.

In many businesses controlling this risk is a critical element in profitability. 

Accept too much risk, revenue loss increases; too little, growth is constrained.  It has to be just right, finding the ideal balance helps maximise profitability.


In order to manage this risk there are a couple of key control points within the credit risk lifecycle to be mindful of.

  1. Customer acquisition
  2. Existing account management
  3. Defaulting accounts

At each point various strategies can be designed and employed to balance risk and optimise profitability.

Examples include; credit availability levels, risk based pricing or deposit policy.

Determining and executing effectively on these strategies is where this process starts to become incrementally complex. 

  • Strategies do not act on customers in isolation, there are interdependencies that will affect outcomes
  • By nature statistical analysis is not a perfect predictor at an individual customer level, these variances need to be understood in detail
  • Strategies affect individual customers and require interaction at the customer level.  Controlling this interaction to maintain overall risk, yet provide customer specific treatment is a challenge.
  • There is business pressure to drive results quicker than the natural rhythm of the portfolio or to eliminate costs, resulting in partial or sub-optimal implementation.

This quickly becomes an extremely complex process and micromanaging each and every aspect of the process can become a herculean task.

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Typically for complex systems a symptomatic approach can also be useful in determining and maintaining process health. This approach is one familiar to most of us from another field –  Medicine.

Complex processes with multiple frequent interactions between all of the parts, where not all are understood, nor measured can be a challenge to manage. The approach taken is to observe the external symptoms. Some are subtle and some not, however they can be used to diagnose potential root causes, which are confirmed by later more detailed tests.

The objective, to efficiently narrow in on root causes, by not spending resources measuring indicators that do not add value.  This speeds diagnosis and hopeful recovery.

Just like in medicine this approach can also be applied within Credit risk and across the Risk Operations Lifecycle.


This approach can be somewhat different to the one typically used in many organisations.

Often there is a reliance on either high level financial measures, such as write off rates or DSO/AR ageing, or detail monitoring of all aspects of the business, contact rates, delinquency rates by segment etc. Solely relying on these measures can result in serveral issues.

  • Summary level measures tend to over simplify the business and are often lagging indicators.  This can result in control issues not being identified until it is too late.
  • Detailed measures are more effective at catching issues early however require considerable manpower to support and it is easy to get lost in the detail and miss overall trends.
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Creating a symptomatic diagnosis infrastructure can help in providing additional, alternative measures to review performance and diagnose any new risks early.


There are a couple of important factors for consideration for the framework design and determination of each indicator.

  • Pick leading rather than lagging indicators – Identify issues early allowing for quick course correction and avoidance of significant expense.
  • Focus groups of symptoms rather than process steps – This identifies issues early allowing for quick course correction and avoidance of significant expense.
  • Ensure process completeness – Creating a holistic top down process model is helpful in ensuring measures are identified for key processes and gaps minimised.

A helpful exercise in selecting indictors can be financial function analysis.  Each element is broken its key functional components, with the mathematics used to ensure completeness. Whilst not perfect this exercise is useful in identifying key measures.


  • Low tenure default – review of acquisition strategy
  • Long tenure default – Economic stress
  • Average default balance – review of control actions and policy
  • Customer Complaints
  • Worklist Ageing – Operational Capacity
  • Cure rate – Operational effectiveness


These techniques can help facilitate a more efficient risk based approach in monitoring credit risk within the customer lifecycle. 

It does however require discipline, with measure reviewed and updated regularly, and it is not a substitute for day to day management. However used correctly however this can reduce cost of monitoring and enabling early identification of issues to improve overall long term performance.

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