Ways Business Intelligence Can Help Lenders Optimize Their Collection Network
Lenders have always used data points to make consumer-centric decisions, but now data technology has the power to get them an enterprise-wide, 360-degree view of their collections network. This explains why more and more lenders are now becoming data-driven and using sophisticated Business Intelligence (BI) tools.
Data can help lenders engage the right collection vendors at the right time, ultimately driving improved debt repayment. They can now move to a deeper, more nuanced understanding of their customers and collection network alike, to understand and act on data in ways that were unthinkable before. Let’s learn how.
Segregation of consumers
Lenders often assemble data from many sources to serve their collections goals. These data sources include customer demographics, collections and account activity, and risk ratings. Business intelligence and analytics for lenders can automate data collection from these disparate systems to help lenders gain insight into propensity-to-pay data, all within a single dashboard.
This way, lenders can segregate consumers into a few risk categories based on delinquency buckets and set different contact strategies for each. Low-risk customers can be allotted to the newly contracted collection while agencies with moderate experience can be assigned to medium-risk customers. High-risk customers can then also be assigned accordingly to the most skilled contracted partners.
The data collected from BI platforms can be used to automate key vendor auditing processes and put important internal controls in place. This can, in turn, help lenders keep a close eye on the performance of their collection network to forecast vendor productivity and profitability while managing inventory and reporting status. Having the ability to visualize data, help one see how the current and projected performance of each vendor compares to their overall collection goals. This way, lending institutes can easily map out individual vendor goals and track their collection performance.
Data from BI solutions can help lenders with predictive scoring models that allow them to create vendor scorecards. Using a vendor scorecard, lenders can identify those contacted agencies within their network who require less interaction or support to prompt debt re-payment. These are generally the ones that need to be preserved for a long-term contract. Vendor scorecard also gives lenders the insight to either collaborate with their agencies for better collection yield or remove them from their collection network (in case of performance and non-compliance issues) for cost optimization.
It is always better to understand the type and reason of delinquency from historic data and act proactively on the accounts showing similar characteristics. Predictive analytics powered by BI can help lenders segment the customers thus can help distinguish between self-cures and potential long-term delinquent accounts only to maximize the collection.
Test and learn
Custom dashboards or visual data imported from business intelligence software can empower lenders to “test and learn” and assign cases to different contracted agencies and run a test. For instance, they can run 70% of their cases under existing collection strategies, 20% cases under one alternate strategy, and 10% of cases under another strategy. With all other factors kept constant, the BI can then measure the impact of the changes from each strategy. Intuitive yet data-rich visuals can always give them a clear view of their whole collection funnel and network, enabling lenders to understand what is working and what is not, and where they should focus on.