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Using data to enhance SME credit decisioning

Lending to Small to Medium sized Enterprises (SME) has received an enormous amount of attention from bankers, economists and politicians over recent months.

Governments around the world are applying enormous pressure on banks to continue lending to SMEs as a way of reversing the shrinking Gross Domestic Product (GDP) of many of the world's developed economies as the global financial crisis continues to impact.

Banks are keen to lend to SMEs, however, there are a number of key challenges including the ability to manage credit risk, deleverage balance sheets and maintain adequate levels of capital.

Faced with a lending environment where the bulk of the lending appetite comes from riskier businesses in need of cash flow and newly-formed businesses rather than credit savvy and experienced businesses, the use of internal customer performance data, business and consumer external credit data allied with sound credit risk management practices enables lenders to meet those challenges.

The use of commercial and consumer credit data
In many markets around the world, SME lending practices still trail behind consumer lending practices not least because of a lack of reliable data on small businesses financial risk.

Many small business proprietors, particularly sole proprietor businesses use personal financial products for business use.

Personal data on the proprietors of a business is predictive of credit risk and helps to create a more comprehensive picture of the entity's risk profile and financial history. In particular, personal data adds significantly to business data for new relationships such as start-ups or weak relationships, such as secondary banking and proves powerful when predicting business failure.

Source: Experian Decision Analytics. The Gini coefficient measures the ability of a scorecard to discriminate between good and bad customers (range 0-100%) - a large Gini indicates strong discrimination.

However, data protection or confidentiality legislation often limits the extent to which a lender may consider personal data when making a decision about a different legal entity such as a business. Things are beginning to change, for example in the UK lenders must supply business credit data; both positive and negative to Credit Reference Agencies (CRAs) by March 2010. In return, lenders will be able to access a much wider level of both business and consumer credit data for small business credit decisioning.

The use of current account and cash flow data
The incorporation of internal data sources such as current account and cash flow data adds considerable predictive power to small business decisioning models.

Analysing the current account transaction data and incorporating it with a product-based performance indicator to create a customer risk grade, enables significant enhancement of granularity and discrimination to small business credit risk tools for new lending and customer management events.

Incorporating cash flow data to assess whether short-term financial commitments can be met by the business is paramount, taking into consideration the high number of insolvencies. Cash flow is often described as the lifeblood of a business, so negative cash flow without a bounce back into net credit when expected can prompt serious questions to be asked about the viability of a business and can lead to its ultimate demise.

The use of data in the deployment of a leading edge loan origination and customer management decisioning system

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In the diagram, credit bureau data and existing customer performance data is brought into the loan origination system. Checking against internal customer performance data sources is carried out in real-time to identify previously rejected applications, existing bad accounts or known high-risk profiles.

It is equally important to acknowledge established, good risk customers. This is to ensure the customer receives a good experience and their known good customer performance is taken into account.

Credit bureau checks are made in real-time and carried out for all the addresses supplied, partners (e.g. joint applicants) and guarantors that carry the liability of the debt.  The use of consumer and business credit bureau data should at least:

1. Verify and authenticate the identity of the applicant.
2. Check the entity's payment performance history with other lenders and suppliers (consumer and business if permitted).
3. Check the entity's financial statements, e.g. balance sheet, profit and loss and statement of cash flow. In addition, the use of ratio analysis: gearing, acid test etc.
4. Check for inconsistencies in personal details supplied, by matching to recent credit applications at the credit bureau.
5. Credit bureau score should also be returned summarising all or some of the above data.
6. The customer management system controls all aspects of on-going credit risk management. As in the loan origination process, consumer and business credit bureau data is used in conjunction with internal customer performance data.  A suite of customer level behavioural scores summarises all available data into key indicators of future behaviour and applied to key segments such as strength of relationship, time delinquent and product type.

In both the origination and customer management process, scoring, setting of limits and collection strategies should utilise a highly flexible, parameter driven system controlled by credit risk, with test/control facilities to enable lenders to maximise the value of both internal customer data and external credit bureau data in order to make profitable lending decisions.

Martin Soley
Global Solutions Consultant
Decision Analytics
Experian

 

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