Asset reconstruction companies (ARCs) are facing new challenges with the rise of retail non-performing assets (NPAs). While ARCs have a proven track record in resolving corporate NPAs, they are finding it increasingly challenging to handle retail bad loans.
Absence of a widely-accepted pricing model for retail NPAs, high transaction costs, difficulty in asset valuation and limited ability to directly engage with borrowers at a granular level pose challenges in effective resolution of retail stressed assets. One of the major hurdles ARCs are facing is the absence of a standardised and widely acceptable pricing model for retail NPAs.
“The early offshoot of stress in unsecured retail is visible and likely to grow further. Unlike corporate NPAs, where valuation models are based on financial statements, collateral and future cash flow potential, retail NPAs lack similar metrics,” said Hari Hara Mishra, CEO of the Association of ARCs in India. “The fragmented nature of these loans, coupled with uncertainties in recovery, makes it challenging to determine a fair price.”
This pricing gap creates a disconnect between banks looking to offload retail NPAs and ARCs willing to acquire them, he said.
Several banks have recently announced plans to sell retail NPAs to ARCs. IndusInd Bank said last month it would sell over Rs 1,500 crore worth of retail bad loans, comprising more than 1 million microfinance accounts, to ARCs. Similarly, Utkarsh Small Finance Bank announced selling unsecured microfinance loans worth Rs 355 crore. In November, Ujjivan Small Finance Bank sold its stressed loan portfolio worth Rs 270 crore to an ARC.
ARCs are typically structured to handle large, complex corporate loan portfolios. Managing a large volume of small retail loans requires different operational capabilities, including robust technology infrastructure, a large network of recovery agents, and expertise in consumer debt management.
“Individual retail loans are typically smaller than corporate loans, making the cost of recovery efforts disproportionately high for ARCs,” said a senior official of private ARC. “Locating and contacting individual borrowers, especially in cases of loan defaults, can be challenging, requiring extensive groundwork and legal procedures,” he said, adding that ARCs need IT infrastructure and specialised call centres to follow up with borrowers.
Considering the challenges in resolving retail NPAs, several ARCs have already started taking efforts. According to experts, use of artificial intelligence will help ARCs in faster recovery from retail stressed assets.
“Resolving retail NPAs requires sophisticated data analytics and borrower profiling to prioritise recovery efforts. Many ARCs lack the advanced technological infrastructure needed to analyse retail borrower behaviour and repayment patterns,” said a senior official of public sector bank.
Experts say data analytics can play a transformative role in resolving retail NPAs. By leveraging advanced algorithms and machine learning models, ARCs can identify patterns in borrower behaviour, segment borrowers based on risk and prioritise accounts with higher recovery potential.
“ARCs should invest in advanced data analytics and AI-driven solutions to streamline borrower profiling and recovery strategies. These tools can help reduce operational costs and improve efficiency in dealing with retail NPAs,” said Mishra.