AI And ML Helps In Improving Debt Recovery Rates – BW Businessworld

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  • July 24, 2020
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Technology helps implement various debt recovery strategies.

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It is imperative for lenders to formulate prudent and well-considered strategies to resolve and recover a debt. A careful and well-planned debt collection strategy, aided by technology, will save time and will help in cost reduction as well as maximize efficient utilization of resources. Technology helps implement various debt recovery strategies. The strategies that are required to be focused on are: Lenders need to maintain and regularly update their existing customer database. Requesting co-borrowers for surety from potential customer helps to mitigate the risks in unsecured lending.  Sending an automated payment reminder via telephonic modes (email/text message/IVR) besides emails is critical in improving the recovery rate. Using intelligent automation tools, it is possible to automate all defaulter communication.  Most of the lenders run an application that makes it easier for the customer to remain updated with payment information. The company needs to remain up to date with the customer’s payment pattern and filter out the delinquent customers. Behaviour analysis helps in better forecasting of recovery schedules.  An AI/ML-driven platform to strategize the debt resolution process, vetted by a legal expert, helps to bring about a major improvement in debt recovery rates.  Most of the issues of handling NPA Management can be handled using AI and Big Data Analytics, which will help in strengthening balance sheets of banks and further enhance credit quality. In the global context, many banks have already started using AI and Data Analytics for Risk management and fraud detection, which has not only reduced the level of rising NPAs but also improved identification of creditworthy customers to create a foundation of a good loan profile.  Data analytics to estimate the chances of recovery using advanced profiling would help. Deploying a dedicated machine learning data-driven model helps you to not only improve the resolution rates but also in predicting the best strategies keeping into account all the variables for resolution of debts. Though the accuracy of the strategies suggested by the model may be on a higher side but they should be vetted by legal experts before execution.  Lenders need to consider and implement well-thought and goal-oriented strategies which will help in debt recovery. Debt recovery primarily depends on using technology to devise customized collection strategies using a blend of amicable settlement methods and imperative litigation models even as lenders must also ensure that the strategies which are being used do not have any legal pitfalls which may backfire at a later stage. Debt recovery is a major issue for the financial institutions and the tools and techniques used by them needs to be properly strategized.  

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About the author

Rishabh Goel
The author is the Co-founder and CEO of Credgenics, a leading company in the debt recovery and technology-enabled collections platform space
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Source: http://bwcio.businessworld.in/article/AI-And-ML-Helps-In-Improving-Debt-Recovery-Rates/24-07-2020-301059