Need for automation and a robust credit appraisal system in Indian banking
The banking sector in India has been in the midst of a churn over the last few years. Asset quality, especially of public sector banks had deteriorated drastically; a significant chunk of banks’ high-rated corporate business had switched to more cost-effective sources of funds such as bonds; the banks have shifted their focus to the retail segment; and non-banking financial companies have seen their balance sheet expand considerably on the back of credit expansion. However, the Reserve Bank of India recently found that recovery and resolution of bad loans showed a significant increase during the year ended March 2018, aided by the Insolvency and Bankruptcy Code and other recovery methods.
The question we need to ask ourselves is have the banks learned some lessons from this cycle of asset quality deterioration? The cycle has certain distinctive features in that apart from cyclical slowdown, structural and sector-specific issues have worsened the asset quality of the banks. Several investment projects, especially in infrastructure space, have got stuck for want of environmental or forest clearances or due to constraints on the resources front. Banks clearly lacked expertise in evaluating these projects.
A disturbing fact is the quality of equity brought in by the promoters. Very often, it is debt raised elsewhere by the promoter, either in the holding company or in an SPV, which is used to fund their portion of the equity. Effectively, promoters do not have much stake in the projects. Further, banks’ credit appraisal processes very often fail to differentiate between promoter’s debt and equity and over time, promoters’ equity contribution significantly decline and leverage increase. In particular, there has been a significant increase in the indebtedness of large business groups in recent years. A study of ten large corporate groups in India had revealed that the share of these groups in total banking sector credit more than doubled between 2007 and 2013 even while, the overall debt of these groups rose six times (from under Rs. one trillion to over Rs. six trillion). Hence, these are the area where the banks need to focus more closely in future.
The banks /financial institutions would also need to keep themselves abreast of the latest developments in the area of sustainable environment. Further, the banks need to beef up their market intelligence and economic analysis, so that they can catch demand-supply gaps, such as those in minerals and mining space, better than they have.
KYC is a critical component of a bank’s risk management framework. A customer-centric business needs to know its customer, the nature of his business and the inflows/ outflows into the accounts, if it is to provide customised business products and solutions. The banks further need to understand the risks associated with customer’s business to manage risks arising from potential delinquency, fraud and consequent losses as also legal and reputational risks arising from exposure to customers having links to multi-level marketing/business/terrorist activities/ hawala transactions, etc, which is another manifestation of KYC.
Therefore, commercial banks in India must revamp their conventional credit appraisal processes to minimize credit delinquency, rein in bad debts and reduce costs and can address these challenges in two ways:
- a) Move from manual interventions to automation for greater accuracy.
- b) Deploy analytics to improve credit decision;
The complexities around data acquisition can be simplified to a large extent by opting for automation over manual processes. The effective deployment of automation — specifically, document exchange protocols and standards — OCR (Optimal Character Recognition) technologies and mark-up language applications, particularly XBRL (eXtensible Business Reporting Language) can truly transform the credit appraisal process.
It is high time banks come up with a mix of manual and automated credit decision skills where each and every action is captured, monitored, tracked and recorded. A dependable MIS and robust analytical models come to the aid of banks and help them make informed decisions on limit setting, risk management, budgeting and assessing propensity to default.
Analytical models can be effectively deployed at multiple levels of the credit appraisal cycle. Reporting analytics from financial spreading sheets of potential borrowers can equip the bank to arrive at accurate risk ratings thereby reducing the risk of delinquencies. Additionally, by tracking and analyzing rate movements, banks can effectively design interest rates and pricing models. Even after the loan has been disbursed, banks can continue to keep a tab on borrowers and minimize the risk of bad debts by analyzing client information on financials, business and industry performance.
—————————————————————————————————————————–The writer is a retired banker and a commentator on contemporary issues