Barriers to Developing an SME Credit Risk Expert Judgement Model

Building an Expert Judgement Credit Rating Tool for SME and Corporate Banking Customers

One of the key elements in improving the quality, consistency and efficiency of SME, and wider commercial and corporate banking, is the application of credit analysis and assessment tools. Sometimes called 'credit decisioning systems', these include a wide range of statistical and qualitative approaches. Increasingly these tools are also often demanded by regulators looking to implement improved capital management practices in their jurisdiction. In this case, we are going to take a deep dive into the expert judgement scorecard approach, in its many variations the most popular and practical approach for most commercial banks operating in most markets.

Barriers to Developing an SME Credit Risk Expert Judgement Model

customer site visit

You're an SME or Commercial Banking Relationship Manager driving home from a team building event which finished early. Your spouse is still at work, and your kids not back from school yet. So rather than sneaking home early, you decide to get a head start on things. You pull over into a lay-by, fire up your tablet computer, login to your bank's CRM app, and check on your work flow.

You notice that Johnson’s Widgets, a long-standing customer of yours, is due a ‘Business Risk Review’ and, as it happens, they are just around the corner. You place a call to their Financial Director and luckily he’s in. Actually, he’s been meaning to call you because he’s interested in applying for an extension of their trade finance credit line in advance of a big order. Before you set off, you notice that the most recent set of accounts has been updated, and the app has neatly calculated the relevant ratios and trends. Interestingly you note that a significant improvement in debtor collection has resulted in a boost in the ‘Financial Assessment’ score.

When you get to the factory headquarters, rather than sitting in the FD’s office, you both take a stroll around the facilities. Along the way, you use your tablet to dynamically update the ‘Business Risk Review’ based on the structured questionnaire which underpins it. You note that while business is growing, Johnson’s is becoming increasingly dependent on a single customer, which is reflected in the ‘Business Risk’ score. The FD counters that they are developing several new products which should expand their range of potential customers.

Back at the office, the FD enquires about the potential increase in the trade finance credit line. Without leaving, you immediately discuss and add some basic product parameters and pricing, and test them against the model. With a little tinkering, you find a solution which meets the customer’s needs and is comfortably within the risk/ reward tolerances of the bank. You give the FD a provisional, positive response and promise to follow-up with a formal application tomorrow.

The FD is delighted, and you sleep soundly having not only completed some risk management administration, but also closing another deal which brings you closer to your targets.

While there are no doubt some banks in emerging markets which operate at this level, there are far too many which do not. Why not? I often hear complaints in emerging markets about relationships between bankers and SMEs which seemed to be based on obfuscation and avoidance. That is not an excuse for avoiding change, rather it is a compelling reason for banks to proactively adopt more objective and transparent approaches (both internally and externally) to credit assessment.

We all have our personal theories on the barriers to achieving a seamless relationship between risk and relationship management, especially in relation to credit assessment and rating. Here are some of mine:

» Some Relationship Managers resist implementation of changes in credit risk assessment methodologies because of the potential loss of personal influence in approving and pricing credit, or the status of their customer set.

» Some Relationship Managers worry about the competitive impact of a credit risk model, the impact on favoured customers, and the potential upheaval in the pecking order of customers.

» Some banks may lack the confidence and perhaps some of the in-house skills required to take an independent approach and are rather dependent on vendors.

» Some banks seem to be driven by solutions from technology vendors which often drive up costs and complexity massively, thus killing any project in its infancy.

» Some ratings agencies are pushing statistical solutions based on data and models which are not fully understood or trusted by banks in emerging markets in particular.

» Many banks have poor historical data, which can be used as a ‘straw man’ by opponents of change. Sometimes the inadequate financial reporting environment is also used.

» Some banks do not seem to have sufficient trust in the basic analytical skills of their staff, and are biased towards a pure statistical solution at the expense of a blended heuristic approach.

This post aims to be a launch pad for a longer running series on the practical implementation of credit rating models, particularly expert judgement solutions for MSME customers. However, before we do so I think it useful to flush out as many challenges and issues as possible, so comments are greatly appreciated. What do you think are the most compelling reasons for the lack of progress in what seems to be a very surmountable challenge?