Debt collection is one of the oldest standing practices in the world, considered older than the history of money itself. It existed during the barter system, going as far back as 3000 BC. Today credit products have evolved drastically to cater to spending economy and covering a vast segment of customers. Though the market segment has increased for credit players, this has put banks and financial institution at risk of growing non-performing assets. With innovative credit products growing, there is also an increase in outstanding debt. For instance, in a developed economy like the US, credit card debt is at its highest, rising to $1 trillion recently.
Traditional methods of debt recovery, such as reminders of invoices, aggressive calls, door-to-door collections are proving unsuccessful. Inefficient collection processes, based on poor strategies and imperfect models, increases operating costs and impacts liquidity. Static classification of accounts and traditional collection models have failed in recovering funds. Stricter regulation and the upsurge in complaints is encouraging organizations to re-evaluate their debt collection strategies and improve their invoicing systems. After all, they don’t want to end up with unhappy customers or hefty penalties for violating the legislation.
Rescue via Digitization
Many of the delinquencies can be avoided if companies can identify consumers who are susceptible to non-payment and prevent these circumstances before they occur. Digital collection system help lenders predict the default patterns in advance and minimize payment declinations. Skip tracing tools, which assist in the collection of vital customer data such as credit score, address, and assets held speed up the process of recovery by locating hard-to-find debtors. Such insights will allow businesses to create personalized digital plans for specific clients including automated reminders and repayment options through preferred channels.
Debt collection based on the technology will also lead to greater customer engagement. The debt collection industry is not a favorite among people for obvious reasons. In addition to abuse by under-trained professionals, debt information is sometimes inaccurate or even exaggerated. AI’s predictive analysis will not only improve forecast numbers, but it will also be able to analyze client communication patterns and suggest the actions to be taken for effective recovery.
One of the main reasons banks are unable to collect on larger debts is because customers feel that debt payment is a Sisyphean task. When you make it easier for them to pay, for instance, by breaking down the payments into smaller chunks, you are less likely to see defaults. Also, in case of hardships, an application should effectively identify and provide space to customer and then recover the debt effectively by showing empathy. In summary, the beginning of the new decade will see a shift towards digitized collection practices and technologies enabling user friendly options available across multiple channels for debt recovery. Collection strategies will also likely shift from aggressive methods to a more pre-emptive approach based on 360-degree view of customers digital data points, making it a win-win for both parties.
Views expressed in this article are the personal opinion of Rajendra Awasthi, Co-Founder, EPIKInDIFi