Obtaining payments from severely delinquent consumers can be very challenging. Some customers may never pay, while others may pay without a reminder or may need to be pursued. Optimizing collections operations to provide the right treatment to the right customer results in fewer accounts receivable and cost savings from operational efficiencies.
Angoss predictive analytics software and solutions allow organizations to:
- Profile payers, non-payers and self-cures
- Segment applicants by repayment patterns
- Create models based on promises to pay or funds obtained
- Build strategies to balance payments and operational efficiency
Angoss software and solutions capabilities for collections operations include, among others:
- Data visualization makes it easy to determine which factors differentiate customer profiles by addressing questions:
- How do non-payers differ from payers?
- What factors influence customers to provide payment?
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Predictive decision tree algorithms are used to segment customers by payment profile. Flexible decision trees allow you to incorporate your policies and best practices into the generated decision trees for optimal segmentation.
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Regression models score the portfolio, analyze the effectiveness of models and quickly predict payment. New models can be easily compared and validated against existing models to identify which customers should not be pursued.
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Strategy Trees allow all of your fraud analytics to be stored in a complete suite of predictive analytics software. Include Key Performance Indicators (KPIs) such as payment amount, number of contact attempts and type of contact directly within each branch of the strategy tree to balance “what-if” scenarios. Strategy Trees allow users to assign letter, phone call and no-action treatments to optimize payments and operational efficiency.