In the last 100 odd days, the microscopic organism, SARS-CoV-2, has sent the world running for cover. On an economic scale, COVID-19 is estimated to shave off 0.15-0.35% of Indian GDP and 0.1-0.4% of global GDP. Governments, global organisations, large industries, and central banks are frantically working on face-saving solutions, including fiscal stimuli, loan moratoriums, and forbearance of asset qualification norms.
The world is currently witnessing multiple “black swan” events, most prominent among these being the COVID-19 pandemic, which wasn’t even taken seriously a few months ago. Such black swan events are unpredictable, yet may have catastrophic consequences. The average risk practitioner uses historical frameworks and data for decision-making. In this context, black swan events pose a significant challenge, as they are neither have any historical reference frame nor are utterly benign.
Predicting black swan events accurately is a tall order. But, their negative fallout on financial institutions’ credit risk profiles can be managed through technology-based interventions, such as Early Warning Systems.
Identifying Sector-based risks through Early Warning Systems
- Once an event like COVID-19 occurs, risk management professionals can tap into the power of Early Warning Systems to identify potential risk areas, based on drivers including customer/industry sectors, geographies, and associated linkages.
- A sectoral impact analysis of COVID-19 by the Confederation of Indian Industry lists the following:
- Stress on topline in the auto industry due to severe fall in demand from China for luxury cars, and an impact on working capital management due to stoppage of import of components, especially EV batteries, from China
- Complete production shutdown for pharma and chemical companies depending on China for the bulk of their raw materials
- Negative impact on technology companies, including electronics and renewable energy, which source most raw material and finished goods from China
- Logistics, shipping and transportation sectors reeling from multiyear low demand due to stuck shipments and increased shipment costs
- Spinning mills facing lack of orders due to closure of textile factories in China – a key market for India
- Tourism, aviation and hospitality sectors seeing close to zero activity with voluntary/enforced travel bans globally
Early Warning Systems can be used to keep a close tab on companies and industries, and their associated credit risks to the financial sector, as described below:
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Supply chain disruptions
For manufacturing industries, the stability of their forward and backward supply chain is a good risk indicator. Credit risk may arise as a consequence of glitches in material supply (from higher costs to outright business closure) or in sale of finished goods due to forced demand shortage from traditional customers. This is also why bankers perceive vertically integrated conglomerates as safe bets.
An Early Warning System can capture critical information from sources internal to the bank (including debtors/creditors statements, monthly operational statements) as well as those external to the bank (including financials, industry analysis of companies involved in the value chain, channel checks, media information on borrowers, related industries and countries involved in the supply chain), giving bankers an early indicator of potential stress areas for pre-emptive action.
Receivables/payable analysis
For service industries like IT, contractors or financial institutions, the impact may be felt immediately on collections/receivables due to delays or disputes which an Early Warning System could detect by monitoring abnormal hikes in debtors holding levels, litigations, BG invocations, etc.
Account turnover analysis
Any fluctuations in sales or collections from debtors would quickly get reflected in the turnover of the borrower account, which can be monitored using metrics like credit summations or debit/credit summation ratios for warning signs.
Analysis of borrower delinquency with other banks
Credit Bureaus provide vital information on the behaviour of a borrower with all the financial institutions. By scanning their loan portfolios for elongated past dues, banks can pick up early warning signals utilising information at a consolidated level from the banking industry.
Starting with such analyses, a systematic, in-depth assessment of credit risk through early warning signals can be performed, and be used to score specific customers or segments to ascertain riskiness on an aggregated basis. This can aid in calibrated, targeted action for each large borrower account or customer segment, rather than employing a one-size-fits-all approach.
While it may not be possible to forecast extreme events in this dynamic environment, impacts of these on a financial institution can be measured, monitored and mitigated in a targeted manner, through careful channelling of resources; using technology-based solutions like Early Warning Systems. An organisation must utilise measures like portfolio diversification and technology-led risk mitigation to stay financially viable and protected when uncertainty strikes.
Views are personal.
The author is CEO at BCT Digital.