Evaluating the default potential of small and medium-size enterprises (SME) can be difficult and lengthy, and can lead to undue risks for both the lender and borrower, says Nigel Rusby, a principal consultant on the global consulting team of Ireland-based Experian.
According to Rusby, there is a growing realisation among lenders that the manual processes typically used when lending to SMEs are harmful to both sides of the transaction, and that automation can offset those risks.
“Bad debt rates have risen sharply across most lending segments since the global financial crisis,” he said. “This illustrates two clear issues: loss forecasting is inadequate under these conditions, and secondly, reliance on customer-stated financials for small, unstructured SMEs is insensitive to these rapidly changing conditions.”
In a recent report, Experian found that the use of centralised loan decision solutions and scoring techniques enable lenders to automate credit risk decisions and increase operational efficiencies, while reducing bad debts. Automation would also speed up the process for borrowers, allowing them to move ahead with business without having to wait for a response to their loan applications.
The firm also identified four key sources of data for use by lenders when dealing with SMEs: business demographics, credit or public record information, financial data and data on the principals of the businesses.
“By blending internal and external customer data, and by automating decisions where possible, lenders are able to improve the quality of risk-based decisions, reduce service costs and improve the speed and consistency of decision making,” said Manu Panda, Asia-Pacific managing director of Experian decision analytics, in a statement. “It can also help to ensure that viable smaller businesses continue to have access to the financial services they need to play a fundamental role in the national economy and development of future wealth.”
Improving SME lending in the region is a big deal. SMEs represent about 99% of businesses in Asia, according to Experian, and as much as 99.6% of enterprises in China – or 40 million businesses. These numbers translate into 75% of total employment, a third of exports and critical links in numerous global supply chains.
These small businesses are riskier than their larger counterparts. Stephen Gildert, senior business consultant at Experian, says many small businesses are squeezed when the economy comes under pressure because larger firms often manage their cashflows by delaying payments to suppliers. In addition, consumers often use small business services less.
“Micro businesses, however, have proved to be very resilient in times of economic stress as they can adapt their cost infrastructures more readily, with less fixed overheads and fewer employees,” he said.
Rusby and Gildert argue that lenders need to invest in their risk infrastructure. These include, for example, tools that enable lenders to assess risk objectively at the outset, including automated origination systems, scoring and risk rating and customer risk management. In addition, appropriate early warning systems need to be put in place to ensure that as soon as a deterioration is identified, an intervention can be undertaken.
Finally, they point out that the current investment in risk infrastructure, spurred by the implementation of Basel II, creates an excellent foundation on which to build customer-orientated lending processes that manage risk well.
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