The client is a leading credit card provider headquartered in the United States. Established over 150 years ago, the client has over 100 million active cards and currently features amongst the top 100 companies in the ‘Fortune 500’ list.
The client was facing issues of low collections from defaulting credit card accounts and was looking at partnering with an analytics expert for a reliable and effective solution. Post deliberations with several analytics firms, they reached out to Firstsource to improve collections from the top decile through better predictions of propensity-to-pay.
A very basic prioritization model was in use to identify accounts that had highest propensity-to-pay and a shift to a more robust system was therefore an urgency.
The process, analysed a year of data and identified a number of segments within defined groups along with necessary variables for the model. It also fleshed out certain proxy variables such as number of days since last payment and CPS score among others. In terms of methodology, it performed clustering using the elbow method.
New prioritization model
After using logistic regression on all groups, the solution identified deciles for outstanding amount, number of card holders that had paid and the amount paid. The next phase then successfully created a prioritization model that could assign propensity to pay for each account leading to optimized sequencing.
The new prioritization model can result in improved potential collections with deployment of fewer resources. Some conspicuous tangible benefits include:
100% increase in potential collections in top decile
60% increase in collection potential in the top 50% decile
60% more can be collected with a 50% reduction in calls
Firstsource is a leading provider of customised Business Process Management (BPM) services. We specialise in helping clients stay ahead of the curve through transformational solutions in order to reimagine business processes and deliver increased efficiency, deeper insights and superior outcomes.
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