The need for tech capabilities to drive loan collections

By Avadhut Thali

The internet has knocked on the door of every sector by now. It is a proven fact that the right technology introduced at the right time improves efficiency and creates a better experience for all stakeholders.

One such technology that is being gradually introduced to each sector is Artificial Intelligence and Machine Learning. These technologies are helping companies and businesses evolve by leveraging a large chunk of data that is already available.

The shift in the financial service sector
Banks and financial institutions have traditionally relied on mails and phone calls to derive payments from customers. These methods are considered to be intrusive and tend to have an adverse impact on customers. The solution, therefore, lies in the practice of incorporating alternative communication channels. Banks and financial institutions have thus switched to mobile apps, online portals, social media platforms, and automated chatbots to communicate with their customers.

How AI and ML can help derive loan collections:
Machine learning and artificial intelligence is being extensively used to optimize debt collection. Banks and financial institutions are incorporating cutting-edge debt collection software to increase collections while enhancing the customer experience. A report by Markets and Markets states that the debt collection software market size is growing at a CAGR of 9.6%. The market is expected to reach from $2.9 Billion in 2019 to $4.6 Billion by 2024.

The many benefits of using tech capabilities in deriving loan collection include:

Identifying the potential defaulters
Debt collection software combines the insights from the customers’ accounts and their online as well as social activities. This combination of data lends banks and financial institutions an accurate view of the customers’ situation. It helps them in identifying potential defaulters. A timely update about the customers that can turn defaulters help banks initiate timely action beforehand. Artificial intelligence and machine learning can be used to analyze the customers’ interaction with banks and gauge their financial situation. For instance, if the customer’s bank account shows a fall in his income and the account holder’s digital activity indicates job loss, then banks can offer credit counseling support to such customers. Such actions help increase customer loyalty in the long run.

Defining customised collection strategies
Banks are switching from following standardised collection strategies to designing customised collection strategies. The collection strategies are personalized for an individual after analyzing his past repayment behavior. This brings those negligent customers with high chances of becoming defaulters to the mainstream. Predictive models can be used on a regular basis to find out the collection strategies that failed for an individual and thus design a new and effective strategy.

 Automated reminders
Using AI and ML algorithms helps bank offer automated reminders and follow-up calls. This helps the banks and financial institutions in meeting the compliance requirements. AI-enabled self-service chatbots can also be used, allowing customers to reach out to the bank as per their convenience. A more automated process with reduced human interference will also help optimize strategies regarding when to contact an individual customer.

Setting recovery strategies
Processing data with the help of AI algorithms and other technologies will help banks in assessing the costs associated with each default account. It will further help banks in coming up with a recovery strategy. Banks can decide whether to opt for an in-house recovery process, or it needs to be delegated to some recovery and collection agency. Effective recovery strategies, when used at an appropriate time, will help reduce the NPA in banks.

Why Digital collection is the way forward:

Customers have moved on while the lenders have not: As per a recent survey conducted by Spocto, the Big Data Analytics Company, 75% of the customers are ready to pay the dues via digital mediums. The banking sector has to take note of this and bridge the gap that exists between communicating and resolving queries if any, so that the customer is easily directed to an array of payment options and can choose to make a payment from the method he/she is comfortable with.

It will improve customer experience: Resolution of NPA’s has gone up from 20 to 40% via digital collections as the tele-communication and field collection tends to leave a bad taste among customers. The customer experience can be enhanced by incorporation of digital collection methods that are consistent and provide a seamless experience.

During the current times when tele-collection is limping its way out and field collection of dues has come to a halt, digital collection has proven to be a boon for the lenders. It is easier for the lenders to get in touch with the customers and help them collect dues. Digital collection has also reduced the overall cost of collection impacting minimum of 30% and maximum of 80% lenders.

Bottom line
Debt collection has always been the most significant pain point of banks and financial institutions. AI and ML-powered solutions help these institutions in real-time tracking of the payment status, the integration of payment across gateways, and in customizing regional communication. Automation improves efficiency, thereby reducing bad debts. Financial services are continuously seeking novel ways to implement various technologies to optimize the debt collection processes, which will benefit them and the customers.

(The author is Executive Director, Spocto)

Artificial Intelligencefinancial servicesLoan Collectionmachine-learning
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