The issue of credit rating for MSMEs has come to the fore, with Nitin Gadkari, Union Minister for MSMEs, calling for a digital push and rating of enterprises on two parameters: prompt repayments and GST payments. Is this reliable and adequate?
Rating involves knowledge, cognitive and perceptive, of the enterprise, entrepreneur and environment. Credit rating agencies (CRAs) play an important role in assessing risk and its location and distribution in the financial system. By facilitating investment decisions, they can help investors in achieving a balance in the risk return profile and, at the same time, assist firms in accessing capital at low cost.
Rating as a tool for issuance of credit, particularly for manufacturing MSMEs, can be effective if the sector is organised and able to present reliable historical data. The digital data proposed to be captured is in terms of the repayment behaviour and turnover data from the GST portal. Benefits arising from such ratings need detailed analysis.
If a bank chooses to keep some of its loans unrated, it may have to provide, as per RBI instructions, a risk weight of 100 per cent for credit risk on such loans. As provided under Basel II, supervisors may increase the standard risk weight for unrated claims where a higher risk weight is warranted by the overall default experience in their jurisdiction. The supervisor may also consider whether the credit quality of corporate claims held by individual banks should warrant a standard risk weight higher than 100 per cent.
The MSME sector after the Fourth Census (2006-07) has no reliable and analytical macro data. Enterprise data currently fed to the Udyog Aadhaar portal needs re-check as it is one-time data and not dynamic. Periodic infusion of capital and shifts in markets and technologies are not captured. They should be captured from other secondary data.
This sector produces over 6,000 products and is governed by a host of product-related regulations and financial regulations. They are at the mercy of their vendees. Their supply chain to turn into value chain require counselling, mentoring, hand-holding and strategic management for being on the rising curve. However, the rating process involves assessment of business risk arising from an interplay of five factors: industry risk; market position, operating efficiency, financial risk and management risk. While industry risk and market position can be assessed from the macro level data, operating efficiency and management risk can be captured by observation, frequent interaction and experience. Information asymmetry is not adequately addressed through rating of MSMEs.
Let me take you through two industry perspectives in so far as data capture is concerned.
Take a sawmill, a partnership unit, with stocks as wooden logs of different types of wood: teak, B2teak, plywood, sal wood, sandal wood, etc.
The stock statement gives the volumes in cubic meters. Respective rates for each type are furnished in the stock statement. Logs are transported at least cost through navigable waters and lorry.
Transport cost and procurement cost add up to the invoice value of logs as raw material in stocks. Checking quality of the wooden logs stacked in terms of their weather proofing and value addition require knowledge of the industry. It is doubtful of the current bankers’ and credit rating agencies’ knowledge at the micro level and the way it can be embedded into the financial models to provide meaningful rating of the MSMEs.
The other sector is iron and steel. Secondary steel manufacturing units, forging units and machinery manufacturing units, steel of different gauges and types pose problems in measuring and valuation of stocks. They go by the sample measurement in terms of the weight of the types of materials stocked and length of the rods and strips.
In MSMEs, most working capital is provided on trust. If the entrepreneur is good and provides fair assessment of stocks periodically, and the unit is also running well in terms of compliances and maintaining the portfolio, there are no issues.
Repayment behaviour: Digital data comes from the lender and GST data, from the government portal. Both these are post disbursement of the limits. For a new unit, and a new entrepreneur, banks depend on CIBIL rating. A credit/debit card payment delay by a day/week, ATM decline due to system default get low rating. Multiple data sources should be available at a single point reference for tracking the behaviour of a client and rating given. Granular data on the enterprise behaviour is just not available digitally. Rating is paid for by the borrower. Rating technically should help both borrower through better terms of credit and lender through rectifying information asymmetry and avoiding adverse selection. But both are not happening, save exceptions. Viewed from one angle, somewhere a beginning should be made and if that is the intention, the two parameters cited by the MSME minister hold good. For the present, the ratings system has limited utility for the MSMEs.
The writer is an economist and risk-management specialist. He is an author of a book on MSMEs