In the world of delinquency management, using a single analytical risk scorecard to evaluate and mitigate risk is no longer sufficient. The complexity of modern risk management requires a suite of risk scorecards that take into account a wide range of factors and provide a more comprehensive understanding of potential risks.

In this blog, we will explore the concept of “Supercharged Collections” – a term used to describe the use of multiple analytical risk scorecards – and why it is critical for businesses to adopt this approach to effectively manage their risks. We will examine the advantages of using multiple risk scorecards and explain how they can help organizations gain a more accurate and complete picture of their risk landscape.

When we look at risk scorecards within the credit lifecycle, we primarily look at Application Scorecards and Behavioural Scorecards.

Application Scorecards are used in the new account initiation process and credit application process, and Behavioural Scorecards used within the account management cycle.

For the purposes of this blog, we will focus on Behavioural Scorecards within the Collections lifecycle (including pre-delinquency collections).

Some organisations still believe that a single scorecard will be sufficient for collections strategy purposes, but this is however not correct. Delinquency levels is probably one of the highest predictable indicators of risk in an organisation, so if one scorecard is designed over all delinquency levels, the weighting of the delinquency level will far outweigh any other indicator, and for that reason drive the risk classification.

So, what should be the approach?

Dependent on appetite, companies either drive “bad” rates (bad rate definition could be different from company to company) or try to ensure clients don’t go into delinquency, and for that reason predelinquency strategies driven by analytically derived scorecards has become a necessity.

It is not enough to segment based on time since delinquency (for predelinquency scoring), even though it is highly predictable, as the pockets of accounts will be extremely small. Therefore, we rather segment accounts as “clean” and “dirty”, where the clean refers to client’s which has never been delinquent and the “dirty” referring to clients who has been delinquent in the past, but currently in a current state.

Collections behavioural scorecard will typically include a suite of scorecards which include Predelinquency Scorecards (Clean and Dirty), one cycle delinquent scorecard, two cycle delinquent scorecard, Payment Projection Scorecard (PPS typically over 6 months) which typically covers three and four cycles delinquent (but linked to an organisation’s “Bad” definition) and Recoveries Scorecard (12-month prediction).

So, what should be the minimum required risk scorecards to drive an efficient collections strategy?

The bare minimum should be at least 3 scorecards, one driving cycle one and two delinquency, one driving three and four cycles delinquency and one driving recoveries. These however depend on an organisation’s definition of “bad” accounts as well as their write-off and outsourcing policies.

A more comprehensive suite will be predelinquency, one cycle delinquent, two cycle delinquent, cycle three and four delinquent, cycle five and six delinquent, and cycle seven+ delinquent. These could differ somewhat based on an organisation’s definition of “bad” accounts as well as their write-off and outsourcing policies.

Monitoring and Realignment

Analytical scorecard monitoring and realignment is the process of regularly reviewing and assessing the performance data captured by the scorecards, identifying any areas of underperformance or overperformance, and then making necessary adjustments to improve overall results. Realignment is necessary when the population shifts from the development population so a different weighting is needed within the scorecard as the scorecard is based on the premise that your future will be based on your past data.

The process involves reviewing trends and patterns in performance data and assessing the impact of external factors on performance. It also includes identifying areas of improvement and potential root causes of underperformance.

Analytical scorecard monitoring and realignment is important because it allows organisations to:

• Ensure that business processes and initiatives are aligned with organisational goals and objectives.
• Identify areas of underperformance and overperformance and take corrective actions in a timely manner.
• Improve overall performance and achieve desired outcomes.
• Ensure accountability and transparency in performance reporting.
• Foster a culture of continuous improvement and learning within the organization.

It is therefore clear that risk scorecards on their own is not enough to ensure a supercharged collections strategy, but require constant monitoring and realignment to ensure that they are meeting their goals and objectives, improving performance, and making data-driven decisions.