The FinTech way of solving India’s high NPA situation
Can FinTech avoid the accumulation of NPAs in the future?
Three FinTech founders talk about how technology can help manage the challenges posed by the mountain of Non-Performing Assets (NPAs) in the Indian banking sector.
In September, the Government of India approved the extension of a guarantee worth INR 30.6 billion (US$4.1 billion) to the National Asset Reconstruction Company Ltd. (NARCL), also called a bad bank.
A move to address the mountain of NPAs in the banking sector, bad banks may bring some relief to banks or rather defer the crisis. However, historically bad banks have not been successful for countries like Mexico, Greece, South Korea, Argentina and Italy.
Especially, as the International Banker says, “When the toxic assets have predominantly taken the form of industrial, corporate and conglomerate-level bad loans, as is the case for India’s NPAs, of which upwards of 75 percent are nonperforming corporate loans.”
This means caution is required going forward, and all might not yet be well.
Can FinTech avoid the accumulation of NPAs in the future?
The Tech Panda spoke to three FinTech founders about how technology can help manage the challenges posed by the mountain of NPAs in the Indian banking sector.
Blockchain for Transparency
Blockchain technology can significantly help in improving transparency between market participants. It helps all the participants to have access in real-time, says Abhishek Pandit, Executive VP of AISECT, an e-governance service provider involved in implementation of financial inclusion scheme in correspondence with three nationalised banks and two Regional Rural Banks.
A key advantage of blockchain in banking is that it improves efficiency and enhances security, quick transaction time, and there is no third-party involvement
“A key advantage of blockchain in banking is that it improves efficiency and enhances security, quick transaction time, and there is no third-party involvement,” he says.
Artificial Intelligence for Streamlined Processes
Artificial Intelligence (AI) too can play a critical role in fraud detection in the banking industry. AI can also help in online dispute resolution and less dependence on human intervention. With conversational AI based solutions, the banking process has become much faster, and engagement with customers is streamlined.
“Technology makes it possible for banks and NBFCs to personalise their collection strategy according to the traits of individual borrowers. This is done by evaluating data points from past repayment strategies that helped recover dues from borrowers with similar profiles,” says Pandit.
Emerging Tech for High Tech Banking
The banking industry is moving from its traditional methods of securities to high-tech securities. They have started experimenting with new-age technologies.
Technologies such as Machine Learning, AI, data sciences, and others can help in this direction through early identification of defaults, and also in creating a robust and efficient strategy for collections from defaulters
“COVID-19 has heightened the situation of NPAs in India. Technologies such as Machine Learning, AI, data sciences, and others can help in this direction through early identification of defaults, and also in creating a robust and efficient strategy for collections from defaulters,” says Atul Monga, CEO and Co-founder of BASIC Home Loan, a 2020 startup aiming to make home loans a faster and stress-free process.
Using these insights, banks can build a predictive model based on personas, an area where emerging tech can contribute well, says PT Suresh, Founder and Director of Paycraft Solutions, a FinTech company founded in 2013 with an aim to enable and ease urban mobility.
Big data, AI, and ML will play an important role in identifying critical factors and variables for improving these models and thus in tweaking existing strategies to keep processes effective
“Such models need to be continually updated and refined so that they keep working hard for the bank and constantly improving yields. Big data, AI, and ML will play an important role in identifying critical factors and variables for improving these models and thus in tweaking existing strategies to keep processes effective,” he says.
Biometrics for Authentication
Biometrics is another banking champion. Aadhar authentication has already made customer databases more secure. Digital technology lessens the burden of carrying important documents, so now customers are only using their Aadhar biometric authentication to access their key banking services.
“Banks are working with their technology partners to implement these new-age technologies for non-intrusive yet effective methods of interaction with delinquent customers. The attempt is not merely to bring down the NPAs but also to improve customer experience,” says PT Suresh.
Composite Credit Scoring
Most FinTech companies have complemented the standard credit rating scores with their own credit rating system modelled on consumer behaviour, non-traditional markers of credit worthiness and other indices, all modelled and analysed with complex algorithms.
“Banks should therefore look beyond traditional published indices of credit worthiness,” PT Suresh advises.
Digitising Transaction Data
The transaction data of all loans and advances should be digitised right from disbursement to collection and closure using traditional ERP like systems, says PT Suresh.
“Any time there is near real time data available at centralised location, diagnostic and warning tools should be used over this centralised data with user friendly dash boards for regulators and risk management teams inside banks to be given timely warning so as to take proactive action,” he explains.
In the last couple of years, several new players have adapted new technologies to empower the semi-urban and rural populations with digitised payment services and are creating an inclusive digital finance ecosystem.
Use of technology can make a marked difference in reducing instances of toxic assets.