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Optimising collection strategies with collection scorecards

How we leveraged data-driven insights, predictive modelling and customised tools to optimise a lender’s collection operations and deliver tangible improvements in efficiency and risk management.  

We worked with a lender that was facing a dual challenge - the scarcity of experienced collection staff and the need to enhance their collections strategy to improve collection rates and efficiency. The lender had already implemented a risk-based collection strategy, and engaged us to assist with further optimisation. 


Optimising the lender’s collection strategies and the implemention of collection scorecards and accompanying strategies yielded significant results for the lender. 

By implementing a combination of targeted approaches in early collection queues and the utilisation of predictive models for optimised resource allocation, the lender saw a 20% increase in the efficiency of their collections operations and they also saw a reduction in default rates. The negotiation tool developed for collection staff contributed to more positive interactions with clients, which not only improved the likelihood of successful payment arrangements, but also enhanced overall client satisfaction.

Key results


20% increase of the collections operations

5 % reduction in the default rate

Collections strategy aligned with lender's risk appetite

Our approach


We recognised the opportunity to leverage advanced analytics and predictive modelling to address both the resourcing and collections strategy enhancement simultaneously. 


Proposed solutions

We proposed the development of bespoke collection scorecards to fine-tune the existing collection strategy. The objective was twofold: predicting the likelihood of an account defaulting in the next six months and forecasting the probability of a payment arrangement being met. 


Implementation process

  1. We collaborated closely with the lender to analyse historical collection data, identifying patterns and trends that could inform the development of the collection scorecards. The scorecards were tailored to the lender’s specific business environment, considering the unique characteristics of their portfolio. 

  2. Advanced predictive modelling techniques were employed to create the collection scorecards. These models were designed to provide accurate and timely predictions, enabling the client to proactively manage accounts at risk.

  3. The collection scorecards were seamlessly integrated into the lender’s existing collection software. This integration ensured a smooth transition and allowed the client to continue utilising their current software infrastructure while benefiting from enhancing predictive analytics. 

  4. Based on insights from the collection scorecards, we collaborated with the lender to develop new and more effective collection strategies. These strategies were specifically targeted at the early collection queues, aiming to maximise the impact on default prevention. 

  5. We also developed a negotiation tool for collection staff to facilitate more effective interactions with clients. This tool was designed to enhance the negotiation process for payment arrangements, contributing to improved client satisfaction and increased collection rates.

Find out more

Our intervention in optimising collection strategies through the development and implementation of collection scorecards showcases the power of advanced analytics in the financial industry. This case study underscores the value of strategic risk consultancy in maximising the effectiveness of collections operations while aligning with organisational risk objectives. 


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