SME CREDIT RATING GLOBAL EXPERIENCE, PRACTICAL EXPERTISE EXPERT JUDGEMENT APPROACHES FOR SME & COMMERCIAL CUSTOMERS

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1 EXPERT JUDGEMENT APPROACHES FOR SME & COMMERCIAL CUSTOMERS Credit assessment for SME and commercial customers can sometimes present a challenge for banks. It is often not costeffective to apply the intensive, bespoke credit analysis used for large and global corporate customers. Yet SME and commercial customers have often been quite impervious to purely statistical approaches to credit scoring, as is often applied to small loans for retail customers. In many cases, the optimum approach is to apply what is known as an Expert Judgement credit rating model. This should reduce costs, speed up decision-making, and improve the predictability and consistency of lending decisions. LONDON WASHINGTON DC SINGAPORE

2 Lending to SMEs and mid-size commercial customers is not easy, but it is a vital franchise for any serious universal bank with long-term ambitions. Large and global corporate margins can be wafer thin, and many retail banking markets are hyper-competitive. The income generated by individual SMEs does not warrant the individual attention bestowed on large customers through a full corporate credit analysis. By the same token, they are so diverse and sometimes opaque, that they are not appropriate for a totally automated credit scoring process, which is the case for some retail markets. However, in order to keep lending costs down and also improve the consistency and objectivity of credit decisions, the tactical application of a standardised model does offer considerable advantages. keep credit costs down, and also improve the consistency and objectivity of credit decisions GBRW Consulting has developed a specialist SME/ Commercial Credit Risk Expert Judgement System. In this paper we will outline the key principles and features underpinning our approach, which is highly customisable and, with suitable tailoring, can meet a range of rating challenges. APPROACHES TO SME CREDIT RISK RATING Traditionally credit to SME customers was allocated on the basis of purely subjective analysis and opinion of the likelihood or not of a customer paying back a particular facility. This opinion was offered by the Relationship Manager in consultation with Credit Risk, and overseen by the Credit Committee. The first SME rating systems were often built along similar lines. However, while they seemed to offer a more scientific approach to credit assessment, the fundamentals were still largely unstructured. In parallel, approaches were being developed to take a purely objective statistical approach to SME credit rating, for example, the Altman Z-Score and the Moody s KMV model. While these models have some plausibility in exceptionally data rich markets, they have found limited applicability to SMEs in most markets, whether emerging or developed. In most cases, the most pragmatic approach to SME credit rating is to apply an Expert Judgement model, which assimilates the knowledge and experience of SME credit experts into a highly structured assessment tool. Expert Judgement models come in many forms, depending on the extent to which data will support at least some statistical analysis. Also, models vary according to the type of customers, with complexity generally varying in correlation with the size of the target customers. 2

3 Expert Judgement models are also usually the foundation for more advanced capital measurement techniques for credit risk under Pillar 1 of Basel II/ III. This requires back-testing against previous default experience and/ or calibration against existing Probability of Default (PD) models. However, the first step is to make sure the model provides effective discrimination based on rank order. Expert Judgement rating models tend to be the most pervasive types for the following key reasons: The prerequisites for developing and implementing an Expert Judgement model include: A sound macro- and micro-economic research and analysis capability The ability to formulate credit strategies, and implement them effectively through robust policies and procedures Solid credit analysis skills in both frontline and credit risk staff Many banks lack the quantity and quality of data required to implement a purely statistical approach In many markets, financial statement reporting tends to be somewhat unreliable, which inhibits statistical modelling Subjective approaches proved slow, expensive, inconsistent, and/ or unreliable A desire to avoid being bound to expensive and untested data and technology solutions from vendors An Expert Judgement model allows a bank to take a truly distinctive view of the market, and to identify opportunities and threats which may be missed by competitors. While it is often not the easiest route, it is usually the more virtuous, compelling a bank to truly understand its portfolio and the associated credit risks in isolation, and as a whole. This addresses a number of key weaknesses attached to a black box from an external vendor. Fig. 1: a risk rating example illustrating how an Expert Judgement risk model derives a quantifiable solution from a partially subjective process. 3

4 OVERVIEW OF THE GBRW EXPERT JUDGEMENT MODEL In describing our standard system, we should emphasise that there is no right answer, and every bank will have a slightly different solution depending on their business environment, marketing strategy, and internal risk culture. We do believe, however, that GBRW s model is extremely sound, and provides an excellent illustration of the key principles. It has assimilated many of the best ideas and approaches we have seen used to address this challenge. Therefore it can prove to be a useful template; recycling, adapting or jettisoning components accordingly. Working with your team, GBRW consultants can support the development and implementation of your own Expert Judgement rating model. Merging our extensive experience of SME credit assessment around the world, with local insight, knowledge and experience, can lead to the optimum outcome. Our standard model consists of: Economic and Industry Analysis Customer Profiling Business Risk Reviews Financial Statement Analysis With more advanced solutions potentially including: Peer Grouping Cash-flow Forecasting Facility (Loss Given Default) Rating The result is quite a sophisticated tool, which is not necessarily appropriate for all customers. However, it is a possible to devolve the model into a more simplified form. Indeed, you may wish to operate several variations of the model, customised to the precise needs of particular customer segments or economic sectors. Fig. 2: the building blocks of a credit rating. 4

5 ECONOMIC/ INDUSTRY SECTOR RISK ANALYSIS One of the core factors in assessing the risk of an SME is their industry sector. It is therefore vital to group customers into suitable classifications, and to carefully consider and assign a risk profile. The GBRW model adopts a methodical though intuitive approach which addresses sector risk through a series of ratings reflecting key macro- and micro-economic factors. The benefit of investing the time in developing a compound rating is highlighted when using the model data for active portfolio management. For example, how might your portfolio respond in the event of a particular major economic event (e.g. a currency crisis or public spending cut)? What customers might be most affected and what remedial measures might we undertake? Fig. 3: screenshot of Industry Sector risk assessment template. COMMERCIAL PROFILING In terms of risk segmentation, we prefer to add a second dimension to our model. Most banks tend to use customer size as a proxy for financial durability. Typically customers which have larger balance sheets are perceived as less risky. While there is certainly a correlation, this tends to break down for smaller SMEs. Our approach is more flexible and includes factors such as customer longevity, ownership structure, and even aspects of social or business culture which we believe are relevant. ensure harmony between risk and market segmentation wherever possible. When assessing a Customer Profile, our risk model emphasises five key perspectives: Corporate Governance, Financial Durability, Management Stability, Process Excellence, and Operational Risks. This approach also allows to dovetail the risk segmentation model with the market segmentation strategy much more easily. In our experience, it is extremely useful and effective to ensure harmony between risk and market segmentation wherever possible. 5

6 Fig. 4: visualization of risk segmentation and scoring using a heat map. BUSINESS RISK REVIEWS Non-financial analysis will usually be a key element in any SME lending decision. Our Business Risk Review template focuses on the management quality, their planning for the future, and also preparation for contingencies in the present. To be accompanied by a structured questionnaire, Relationship Managers and Credit Officers evaluate various nonfinancial criteria on a rating scale. Generic questions on the quality of management would relate to aspects such as the suitability of the organisation structure for the business, the reliance on key individuals, the depth of succession planning, the experience of the management in previous ventures, perceptions of the skill and astuteness of leadership, and demonstrations of good character and reputation. Further ratings can relate to the strength of general management functions such as Strategy, Marketing, Human Resources, and Accounting for example. FINANCIAL STATEMENT & RATIO ANALYSIS We understand that good financial data is often hard to come by, but we should apply it where we can. Financial statements (and particularly cash flow) can be assessed against some core criteria. It is also important to generate and analyse key ratios informing operating performance, liquidity, capital structure, and especially cash-flow. generate and analyse key ratios informing operating performance, liquidity, capital structure, and especially cash-flow. Our model takes a lot of the hard work out of this for busy relationship managers and credit analysts, by automatically analysing statements and calculating ratios. It will even identify key trends in certain ratios with a view to an even deeper understanding of customer financial performance. 6

7 Fig. 5: automatically compute financial ratios and trends, and score financial statements. SUPPLEMENTARY FEATURES Once the basic building blocks are in place, a bank may want to consider the whether the incorporation of additional functionality will add value. Other potentially useful features include some of the following. Peer Grouping Peer groups are basically clusters of customers sharing similar characteristics. Outlying performance (either overperformance or under-performance) by an individual or any combination of criteria can be given an increased emphasis. This is based on the observation that highperformance customers in any peer group (even if the peer group has a relatively poor outlook compared to others) have a higher chance of survivability. At the other end of the spectrum, no matter how positive the prospects of a particular peer group, there will always be some shake-out of the worst performing firms. Cash-flow Forecasting Some banks may wish to consider introducing a cash-flow forecasting component. Some customers may produce reliable cash-flow forecasts as a routine part of their financial planning, and we may want to consider recognising this diligence in the financial statement analysis. On the other hand, some customers may not produce any reliable financial statements, and we will need to assist them to complete a cash-flow forecast template to assess affordability. Facility Level Analysis Finally, modern approaches to capital measurement also encourage the development of facility level Loss Given Default measures which can be combined with the customer level Probability of Default measures to generate useful Estimated Loss data to drive credit and pricing decisions. This provides a powerful added dimension to portfolio analysis, and allows a bank to exercise a more sophisticated marketing strategy. 7

8 CUSTOMISATION It should be clear that our approach aims to deliver a customised model, tailored precisely to meet the needs of most business and operating models. It is likely that many banks will have sources of useful data and information which we have not considered, which they would like incorporated into the model. For example, there may be internal credit histories or behavioural data, local credit reference bureaux data, or parallel credit scores or ratings from third parties they may like to incorporate. Many banks also like to include data relevant to the personal credit histories of key shareholders, directors, or executives. Or there may be particular socio-economic, geographic, or demographic data points which are relevant to their circumstances. In all these cases, we stand ready to work with teams to support innovation and customisation. Because we realise this is the only path to building true competitive advantage. CALIBRATION Regardless of the modelling approach, calibration is a key phase. Indeed calibration is an iterative process which should be embedded in the risk modelling processes of the bank, always encouraging incremental refinement of the model as live testing continues to provide model performance data. However in the short-term, up until the initial live release of the model, calibration can entail a mix of activities including: Simple eye-balling of the results to see if they are in line with our intuition. Back-testing against previous credits (both good and bad) to see if results are in line with expectations. Parallel testing with the existing process, with a view to noting and explaining discrepancies. Comparison with an existing proven credit models (either internal or third party) if this is available. Fig. 6: develop, test, and calibrate multiple models by varying criteria weightings. 8

9 IMPLEMENTATION We are naturally resistant to heavy capital expenditure wherever possible, and we see no reason why implementing a sound credit rating model should be any exception. However many products seem over-engineered and unnecessarily complex, which ties banks into a costly development phase and often expensive on-going maintenance costs. In our view, it is possible to get a great result with a relatively modest technology budget. it is possible to get a great result with a relatively modest technology budget. Our prototype is a bespoke web application, using a well-established and maintained MVC framework, MySQL database, and reputable JavaScript libraries. All components are open-source with a broad user base and deep knowledge resources, and long-term continuity. Indeed, many of the required skills are likely to be available in-house, or at relatively low cost in the local market. The advantages are lower costs in terms of initial development and maintenance costs, freedom from licensing fees, ownership of in-house intellectual property, and flexibility in deployment and updates. Certainly, if at all possible, it is very useful to enable access via a secure web app, especially if Relationship Managers are expected to work on-theroad to a large extent. Regardless, we can help a bank adopt similar principles in implementation, or work with IT teams to integrate with existing in-house systems. Fig. 7: implement on-the-road model through a secure web application to enable remote, real-time access and collaboration between the front-line and credit. 9

10 GBRW APPROACH TO SME BANKING GBRW is a leader in working with banks around the world, and particularly in emerging markets. We develop and deliver sustainable and profitable SME banking models through practical consulting and training. In a challenging business environment, we have the experience to help banks achieve realistic solutions to addressing the SME market. Our clients particularly value our focus on implementation, rather than just strategy development. GBRW is a firm which works shoulder-to-shoulder with clients to tackle a wide range of SME banking challenges. If your bank finds some of these ideas and approaches useful or interesting, we would be happy to discuss and explore how we might be able to assist. CONTACT DETAILS To discuss your bank s needs in more detail, or to find out more, please contact one of the GBRW team. Jeremy Denton-Clark, Director jeremy.denton-clark@gbrw.com Portfolio Review: Risk analysis of existing portfolio; tactical solutions to NPL issues SME Banking Strategy: Economic analysis and forecasting; market and competitor analysis; segmentation strategy and credit appetite Credit Strategy: Sector and segment caps and limits; credit policy and procedure development Risk Management: Credit risk policies and procedures; development of credit risk scoring and rating tools and models Marketing and Distribution Strategy: Pricing strategy; product and service development; distribution channel strategy Sales Management: Sales targeting and salesforce management Training and Development: Training in credit assessment, sales and service, products and marketing, and many other subjects through face-to-face or elearning Michael Coates, Director michael.coates@gbrw.com GBRW Ltd, 60 Lombard Street, London EC3V 9EA, United Kingdom Web: Phone: +44 (0)