1. Predictive Delinquency Analytics @ Leading Financial Services Company
Business Drivers
Background
The credit card company wanted to develop pre-delinquency prediction techniques and apply pre-emptive remediation actions through financial advisors.
Client partnered with Cognizant to deliver an analytics solution which would provide actionable insights that would iteratively improve collections & recovery effectiveness and lower collection costs.
Designed a Total Customer Visualization platform capable of improving payments by predicting possible delinquency for customers and improving the pre collection process into a co-operative partnership with clients.
Optimize payment collection process and save millions in recovery costs by effectively predicting potential delinquent accounts
To ensure optimal balance between recovery efficiency and customer satisfaction and customer retention
To reduce the operational costs of employing additional collection agents
To reduce outbound communication attempts and inbound servicing volumes
Solution Highlights
Cognizant’s Total Customer Visualization platform enabled the client to operationalize the automated execution of actionable analytic insights by utilizing the proprietary framework Sight Prism and implementing predictive modeling for collection channel optimization.
Sight Prism’s Predictive Risk Score (PRS) was employed to predict customer delinquency before it occurred and was used to take preventive measures including targeted educational campaigns
Outreach channels (Dialer, IVM, SMS and ) were analyzed for past two years and predictive models were developed for channel optimization in collections
Business Outcome
Predictive models generated an optimized next best action for customers currently in collections and provided key characteristics and segmentation analysis.
Achieved reduction in outbound dialer volume resulting in cost savings of £2million
Reduced ineffective communications, improved collections efficiency and minimized negative customer experience
 Reduced IVM leading to savings of £290k