There was a global turmoil in the socio-economic environment from the beginning of the financial year 2020-21 due to COVID-19. Everything got impacted due to that, and the banking industry is not an exception. However, one more reason that made economists more worried was the increase in NPA or Non-Performing Asset.
Due to the reduction of interest, profitability and shareholder value damaged the viability of banks. It forced creditors, borrowers, industrialists, and the entire economy on the backfoot. Banks decided to play safe by investing in government or similar risk-free securities.
However, there has been a silver lining around the dark cloud. Due to technical advancement and bitterly enforced npa management methodology, there was an improvement in the situation.
Early detection and better analytical ability
Whether it is NPA assessment or npa loan takeover, technology became more instrumental in everything. The advanced risk management process suggested that lending institutions should do risk identification, monitoring, and curtailment.
By using predictive tools, it was possible to interpret and analyze huge data in real time using AI-based tools.
It gave necessary indications to banks on loan servicing and production.
Better insights
Banks started doing inhouse-led credit profiling instead of depending on external agencies. Also, they enabled an improved verification process for loan documents.
Income documents were validated more effectively.
Moreover, banks performed a proper market valuation of an asset that is to be mortgaged or pledged. Clean transfer of mortgaged assets was ensured.
The most important help of advanced analytics is to get real-time tracking of micro and macroeconomics risk indicators. Inclusion of diverse risk indicators in analysis resulted in better npa management.
Experts say that COVID-19 crisis wiped out trillions of dollars from the global economy. All countries, including India, got affected by it. When the whole world is struggling, it is all the more important to take proactive steps to save the losses. It includes cutting down loan production, lowering credit disbursement, and extending the payback period of borrowers. It is to ensure that fewer assets fall in the category of Non-Performing Asset.
Prescriptive analysis
When the asset goes into NPA category, financial institutions check the probability and percentage of the recovery. Automated algorithms can be implemented to warn against depreciating asset quality. Remedial measures can be taken to control the situation.
It reduces human intervention and frauds. When system-generated reports and segmented analysis give an insight on NPA, the actions of writing-off, recovery, or compromise become easy.