“Nothing endures but change”. – said Heraclitus. If credit policy fails to evolve it soon becomes a burden, cutting deep into lending profitability.

With the convenience of decision automation tools, risk managers can evaluate efficiency of any given credit policy, thus identifying the most efficient loan application processing work flow.

Applying Champion/Challenger or A/B Testing for Credit Risk Management

You can compare the effectiveness of alternative credit risk management strategies using champion/challenger approach .  KPIs of the different credit policies can be examined to gain insights into possible changes. For example, you can enhance decision logic, adjust an interest rate, or set a different score cut-off parameter. Once the challenger decision flow is specified, you can compare KPIs for alternative credit policies by running them in live or virtual environments.

Selecting Key Performance Indicators

You may select any KPI in line with your current business challenges. For instance, you can take the following operational or business characteristics as KPI:

Operational KPIs:

  • Delinquency ratio, LGD ratio;
  • Average loan application processing time, average time spent on a certain user workplace, average time of server data requests.

Business indicators:

  • Proportion of approved and turned down loan applications;
  • Key account characteristics.

Recommendation on Setting up Champion/Challenger Testing

In the beginning, we suggest processing the majority of loan applications using the current credit policy (the Champion). The rest of the loan applications (for instance, 10-15%) should be evaluated using the Challenger approach.

champion_challenger

Click on the image to learn more about Champion/Challenger approach in our online learning center

Once you compare the KPIs, you can consider further improving the credit policy, or you can decide to employ the new credit policy.

Scorto’s tools allow you to set up and customize rules for automatic migration of the applications that are currently processed. Once the most optimal credit policy is identified, these applications automatically shift into the new processing mode. A wizard based interface will prompt you to specify necessary details of the migration, should this prove to be necessary.

For instance: you will be able to set certain parameters to be calculated automatically, re-calculated, or set by default.

Conclusions

In order to create an environment that supports great decision making and execution, institutions should embed analytics into every business decision, make informed decisions quickly and execute them smartly. Champion/challenger approach helps risk managers go beyond automating decisions according to corporate strategy, and to constantly maintain the high level of effectiveness of lending strategies and policy rules.

Author: Anna Zelenskaya | Google+