Predict Portfolio Performance and Collections Revenue with Machine Learning Driven Insights
Debt collections is one of the most complex portfolios that needs multiple KPI iterations to recover lost revenue. Each iteration impacts decision time thus reducing the turnaround time of the collection process improves revenue margin. Machine learning driven analytics enables organizations to gauge the profitability and performance of a portfolio, even before they take it up.
Intellicus debt collection analytics solution has enabled businesses to formulate highly effective strategies to curb debts, predict collection and enhance overall portfolio performance. Businesses can reduce costs significantly, while increasing revenues and optimizing efficiency. You can identify which accounts are likely to have a higher probability of paying, plan operations accordingly and get maximum collections output in a short time span.
In a single dashboard get a complete glimpse of where your portfolio stands today. View loan accounts, risk assessment, strategy approach, decisioning, contact validation for each customer and more in one go. You can view the aggregate stats and then drill down to deeper details of any segment.
You can drive business impacted KPIs for your customers basis factors like age, principal outstanding amount, employment status, duration of credit, credit history, payment track record and more. These KPI helps drive risk score card which enables businesses to define custom strategies for different customers to pay and improve collection efficiency. The risk score for each customer will get changed in real time on basis of customer behaviour and tool will suggest next level recommendations based on past or recent outcomes.
Through risk score card and machine learning prediction businesses can predict what accounts are likely to pay sooner than others and can plan operations accordingly. User can compare the predicted values, versus the actual collections made for a given duration. This is an ongoing cycle which helps improve the portfolio conversion with each iteration. These insights are helpful to further improvise collections.
In addition, the same dashboards can be leveraged to monitor the quality and performance of team. All actions taken for a customer are auto updated and are also available for the leadership to review. On a single screen, Quality teams can view the complete life cycle followed for an account, listen to the call recordings right from the dashboard and input their suggestions for the agent in real time.
Intellicus debt collections use case automates all processes associated in collections life cycle, from data management to last level customer interactions. It enables an aggressive, proactive approach of debt collection while ensuring optimum operational efficiency.