While COVID-19 has the general population extremely worried, India’s Banking system is losing sleep over a connected worry; Non Performing Assets or NPA.
This RBI data could put things into perspective -
Briefly, NPAs’ impact could be summarised as -
A reduction of interest spread, profitability and shareholder value that jeopardizes banks’ viability.
Putting the economy, borrowers, creditors, industries etc. on the backfoot.
Forcing banks to play safe by investing in risk-free government securities and similar.
However, the good news is that the NPA mess seems to be responding well to technological interventions. Here’s an overview of how -
Detection: Advanced data analytics
Risk management processes suggest that lending institutions begin with Risk Identification, followed by Monitoring and Risk Curtailment. Here, Predictive Analytical tools powered by AI and Machine Learning, ML crunch through enormous data in real time and provide advance signals on the necessary action during loan production and servicing.
Additional insights derived include -
Inhouse-led credit profile evaluations that are apart from what credit rating agencies provide.
Forgery detection by verifying submitted loan documents.
Accuracy in validation of income documents.
Proper market valuation of assets to be pledged or mortgaged, to avoid inflation.
Ensuring clean transfer of mortgaged assets’ title deeds.
Advanced analytics also help with real time tracking of macro and micro economics risk indicators. The tools’ intuition keeps increasing with inclusion of diverse risk indicators that account for environmental and demographic factors - excessive rains, demonetisation etc.
For effect, the COVID-19 crisis has wiped the world GDP of 2.5 trillion US dollars. And, when entire world economies are at stake, like now, proactive steps such as cutting down loan production, lowering credit disbursement and prolonging borrowers’ payback period through repayment holidays can ensure that fewer assets morph into NPAs.
Let’s look at what’s happening in India today. NPAs have been a looming threat for quite some time in the country and according to an article in The Economic Times, the RBI very recently decided to intervene and minimise corona-crisis related damage to the banking sector.
The regulatory body announced a host of measures - increasing liquidity in the system and deferring EMI payments by 3 months for home loans. These measures will ease loan recovery timelines and give borrowers the breathing space they need to pay back. All while large swathes of the economy are choked by the mandated COVID-19 lockdown. These steps will prevent existing good assets from becoming bad due to such external changes.
What RBI is trying to achieve is not eliminate NPAs because of obvious risks in lending. The preventive measures are mainly to slash acceptable limits of the same.
Another example of proactive action is how SBI successfully leveraged predictive analytics when it mined through 170 TB of inhouse data from 38 systems, including CBS, RTGS, NEFT, AML. SBI overlaid this data with information from its group companies like SBI Life and SBI Mutual Fund. The result; a scorecard that bracketed customers based on their transactions and risk profiles. SBI offers products and pricing to its customers based on that scorecard.
However, banks cannot trump NPAs with risk identification alone. There is a further need for -
Risk quantification based on probability of occurrence and scale of impact.
Risk classification based on low probability with high impact and high probability with low impact.
Prioritization of top risk profiles.
Remedies: Prescriptive analytics
Once an asset becomes an NPA, financial Institutions identify the probability and percentage of recovery from said bad asset. Automated algorithms can warn against depreciating asset quality and take remedial measures. This lowers human intervention and subsequent fraud. Insights gathered from system-generated and segment wise reports on NPA accounts like write-offs, compromise settlements, recoveries and restructured accounts will be extremely helpful.
Additional tech-led approaches
Blockchain can be used to design an Intra-Bank lending platform that exchanges borrower’s information - credit worthiness, defaults, limits availed etc. This can help enforce credit discipline and reduce NPAs.
Automated workflow tools can ensure transparency in loan production and servicing. Audit and transaction trials can fix accountability and traceability when loans default.
Robotic Process Automation, RPA can capture appropriate information from original documents and eliminate human errors. This reduces costs associated with NPA recovery.
Technological interventions are successful only when the regulators themselves are agile in the face of violations. This approach puts a high price on non-compliance and goes a long way in enabling an NPA free banking system.
Mint newspaper printed a version of this article in March, 2020.
Disclaimer: The statements and opinions expressed in this article are those of the author(s) and do not necessarily reflect the positions of Thoughtworks.