Eight Data-driven Strategies To Drive Loan Collections To Profitability!

Debt recovery has always perplexed NBFCs due to increasing bad debts or delayed outstanding payments. Underlying reasons for it are high dependency on human resources and a non-data driven strategy towards loan collections. Such a vague approach results in lost opportunities to receive timely returns and higher overhead costs. Add to it the high levels of consumer dissatisfaction as the entire cycle becomes lethargic for them due to manual processes. A rise of 52% in digital transactions in 2018-19 clearly indicates that consumers are ready for the change.

Not adopting a data-driven digital solution for your debt recovery might prove fatal for your business. While it begins with accommodating digital payment gateways in your collections process, it runs deeper.A data-driven approach helps you to analyse the underlying patterns of your consumer segments, finetune existing strategy to address individual consumer behaviour, fulfill compliances, and predict the probability of recovering loans from a customer by laying down a framework of actions you need to take to get assured returns. Apparently, research shows that such a data-driven approach in loan collections increases the loan recovery by 37% while decreasing the cost of collections by 28%!

We have a checklist of 8 simple solutions that the implementation of Machine Learning and Automation will make possible, to drive your loan collections towards profitability.

Customer ranking

A rich data-source, for example credit-card data, can determine the credit history of a person, and give him a rank based on historical data. The ranking will help you determine which customer is more likely to pay on time, and who will require preemptive follow-ups for recovery.

Customer batches

Batch customers with certain underlying similarities for profitability analysis and implement the same course of action for the entire batch as they are most likely to exhibit similar behaviours. Working with a batch, rather than going after an individual customer is bound to cut down overhead costs.

Special groups.

Certain debt recovery cycles demand exclusive actions. For eg, death of a customer, bankruptcy, incarceration, fraud, etc. Make special groups of such customers to study their behaviour for future predictive analysis, and work-out a cost-effective solution to tackle such cases.

Exclusive collections management team

While the majority of your data-analytics shall be handled by advanced Machine learning, have a dedicated team in place to monitor and study the progress or failure of your strategies.

Data acquisition plan

A certain batch of customers might be more valuable compared to other batches. Hence, spending on acquiring further data about them to increase your consistency of debt recovery will strengthen the core of your business, and help you efficiently allocate budget across various batches.

Communication strategy

The most critical part in your debt recovery is your communication. A solid communication strategy helps you prioritize customers, determine the most cost-effective mode of contact, analyse the responses, and most importantly engage with customers for brand recognition and retention.

Assign workforce

Debt recovery has two parties - a customer, and an agent dealing with the customer. Data analytics is not only to understand and predict customer behaviour, but also determine the skills of your employees, so that their strengths and drawbacks are optimally utilized.

Record the facts

Data can be overwhelming, and can lead to vague assumptions. A record of the facts increases the data-bank of organisations for research. It is the anchor point and a reminder for organizations to base their decisions and strategies on facts, and not on conjectures.

Loan collections tell a lot about your customers if you are willing to listen. With the help of Machine learning, Artificial Intelligence, and Automation, your data analytics can make or break your business. AutoCloud Debt Recovery System is your one-stop solution to optimize your current loan collections for profitability, and data analytics. You can check it out here.