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Carol Byrne | 29 November, 2023

How to operationalize an algorithm

In collections, data and analytics are vital components to helping customers reach financial stability on a personalized level. Data represents the ingredients to a successful collections strategy, whereas algorithms and analytics are the recipe that helps you better understand the solutions individual customers need.

To bridge the gap between understanding and implementation, you need to take these algorithms and operationalize them into your collections process. With high-quality data, a configurable platform and reliable analytical models, you can efficiently cure more customers while reducing the workload for your team.

The importance of analytics in collections

In order to help any account cure, you first need visibility into a number of aspects related to their collections journey. You need to know their financial past, present and have a prediction of their future when it comes to their delinquency.

In terms of their past, you need access to their historical data, like if they have a history of delinquency or have filed for bankruptcy in the past two years. For present, you need to have a strong foundation of engagement with your customers so that any changes in their situation are recorded and applied to your processes. For predictions of their future, this is where analytics and algorithms come in. 

The connection between algorithms and analytics

Algorithms begin their life as an analytical model. These models are based on the historical data of a number of accounts, their situations and the outcomes of their collections journeys. From this model, algorithms can look at the characteristics of your current customers and make predictions based on comparisons between the two. These characteristics can range from debt outstanding, time since last repayment, repayment history, number of promises kept/broken and many more.

An algorithm is able to look at the past and present of your customers’ collections journeys and make accurate predictions of their likelihood to pay, shown as a score tied to their account. But on its own, this doesn’t really provide you with much to help customers reach financial stability. This is why they need to be operationalized.

Turning analytics into humanized processes with operationalization

Segmentation and treatment paths

One key way to operationalize algorithms is through segmentation. This is the process of separating customers into different groups based on their characteristics and prediction value that is provided by the algorithm. As a result, customers facing similar situations become grouped based on analytics.

From these groups, you can assign treatment paths that are unique for each and likely to lead to debt resolution. This process greatly enhances operational efficiency while maintaining a humanized approach through providing customers with personalized solutions.  By assigning treatment paths based on analytic input, you can ensure your teams can focus on customers who need a more human touch to help them resolve their financial difficulty.

Real-time capabilities with up-to-date data

Another way to operationalize algorithms is by incorporating them into real-time customer engagement with the foundation of up-to-date data. This is the process of determining suitable treatment for customers during phone calls or through respective channels based on analytically derived characteristics, such as their likelihood to pay.

Say a customer is on the phone and requests a repayment plan over an extended period. If they provide some new data, such as starting a new job, then they may need to be rescored as their likelihood to pay has changed. With the integrations of a configurable platform, algorithms can rescore customers in real-time via data-flows at the point of need. Then, your team can provide them with a repayment plan that is suitable for their updated situation and likely to help them reach financial stability.

Harness the potential of algorithms with Debt Manager

Operationalized algorithms provide a number of benefits for you and your team. Operational efficiency, improved customer experience and less workload for your team. In order to harness the full potential of these algorithms, you need a configurable platform that can seamlessly integrate a number of systems that both provide and enhance their capabilities.

C&R Software’s industry leading Debt Manager represents a fully configurable system that connects a wide number of systems into a single holistic interface. Algorithms can be implemented and utilized at multiple levels with up-to-date data flows with all necessary systems. The result is a better experience for your customers, strategies that lead to debt resolution and more time for your team to focus directly with those that need it.

To find out more about Debt Manager and its capabilities to operationalize algorithms, contact a member of our team today.

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What does it mean to Operationalize AI in debt collections

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