Time-consuming manual process in creating reports in simple and easy to interpret language and deriving insights
To improve the personal loan collection process for their clients, the company’s debt solutions team monitors the risk performance indicators of customers such as Loan EMI Bounce, Risk Bucket, Total Outstanding Amount of the various customer demographics pertaining to salary, customer segmentation, region, employer at an all India and state level. The company then uses its text and voice bot solutions to reach out to the customers and evaluate the tools’ efficiency in the recovery process.
These reports mainly contain complex charts to display the debt collection performance indicators. The collection team has to undergo the time-consuming process to interpret the visuals, perform monthly indicator comparison and draw inferences, and manually draft the reports for their clients. This also led to the fragmented insights across multiple indicators and demographics.
- Debt collection team spent an excessive amount of time to interpret the complicated charts
- Disparate evaluation and monitoring of the collection tool performance
- Difficulty in integrating risk parameters with demographics to find anomalies in the customer loan repayment behaviour
- Mapping the right tool - Smart Text and Voice Bot to the right set of customers to reduce the EMI bounce rate
This company is a global pioneer in Collection Technology Platform that uses big data and AI to improve the debt recovery process. It has analyzed over 350+ million customer touch-points sourced from 850+ Data Sources for customer demographics. In the BFSI sector, it has a clientele of eight out of the top 10 private banks in India and is also present in other industries such as FMCG, Properties, Retail, e-commerce.