CREDIT RISK. A Practical Approach. to Measuring the Probability of. Financial. istockphoto/thinkstock. 28 April 2012 The RMA Journal

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1 CREDIT RISK A Practical Approach to Measuring the Probability of Financial Distres s istockphoto/thinkstock 28 April 2012 The RMA Journal

2 D i s t r e s s This process for analyzing financial distress offers helpful insights for asset-based lenders and commercial lenders alike, regardless of the underlying collateral position. by Stan Scott The credit risk rating process remains subjective at best, despite advances in credit default modeling. Boiling down innumerable variables into a single risk rating for a commercial borrower seems a daunting task. Naturally, this begs the question of how well this single risk rating addresses the probability of financial distress for the borrower and the quantification of underlying risk factors. Credit risk is widely defined as the chance of default or the probability of loss given default. The condition of financial distress can be described as the inability of the borrower to meet obligations, both secured and unsecured, on a timely basis. The first step to assessing the probability of financial distress and quantifying key risk factors is to define the fundamental nature of the business, classify its operating profile, and characterize its operating environment as follows: Business type: manufacturer, distributor, service, etc. Product type and price point. Macroeconomic conditions. Industry profile. Value chain and industry position: high-level performer in high-risk industry, or what exactly? Regulatory issues. A thorough industry review is critical yet often neglected, which may lead the lender to evaluate the prospective borrower in a vacuum rather than in the context of its unique landscape. An industry review means giving close examination to the playing field on which the company operates. Key questions include: What drives demand? What is the market share distribution and who are the key players? What are the key supply inputs and what drives supply? What are the short- and long-term outlooks for the industry? Answers to these questions are likely to have a direct impact on your borrower, particularly in today s global economy, and will supply direct inputs into pro forma sensitivity analysis. Establishing the Risk Profile and Identifying Key Risk Factors From this basic business landscape, a lender needs to establish a detailed credit risk profile that rates a series of typical risk factors from low to high, as shown in Table 1. Identify Table 1 A Detailed Risk Profile Factor Low Risk Moderate Risk High Risk Demand elasticity Low Moderate High Life cycle Mature Growth Decline/infancy Economic cycle Recovery/ early growth Boom Recession Cyclical nature Noncyclical Counter-cyclical Cyclical Competition Competitive Oligopoly Monopoly Demand power Low Moderate High Supply power Low Moderate High Barriers to entry High Moderate High Threat of substitution Low Moderate High Degree of operating leverage Low Moderate High Degree of financial leverage Low Moderate High Working capital intensity Low Moderate High Customer concentration level Low Moderate High Supplier concentration level Low Moderate High Sales in relation to break-even point Above Equal Below April 2012 The RMA Journal 29

3 the prospective borrower s risk profile and then assess the individual risk factors through a cash flow sensitivity analysis based on the results of multiple scenarios best case, worst case, and most likely or simply on the most likely scenario. Then grade the individual risk factors based on the predicted absolute dollar change. Experience suggests that borrowers often are overly optimistic in their forecasts, so assumptions must be scrutinized closely and tempered with reality. If using the multiplescenario approach, take the sum of probability factors multiplied by the predicted dollar change for the best case, most likely, and worst-case scenarios. Business risk often is measured by historical operating earnings or cash flow volatility and is a function of, among other things, sales volatility and operating leverage, as measured by the percentage of fixed costs making up total costs, representing the cost structure. Higher fixed costs as a percentage of total costs mean greater leverage and risk. Financial risk is a function of the degree of interest-bearing debt within the capital structure, as measured by, for example, the debt-toequity ratio. The higher the debt-to-equity ratio, the greater the degree of leverage and risk, or the degree of financial leverage (DFL). One of the greatest risks for a manufacturer with a high degree of operating leverage (DOL) functioning just above the break-even sales point would be a decline in revenue, resulting in a decline of the gross margin percentage and earnings, all else equal. These firms often are cyclical in nature, so the onset of a recession may trigger a sales slide. Generally, the higher the degree of operating leverage, the greater the capital intensity, labor intensity, and working capital intensity. Highly elastic service companies, on the other hand, often are not capital intensive. Consequently, they are able to more easily absorb a sudden revenue shock. The presence of a key high-concentration customer for a manufacturer bearing a high DOL can present at least four types of risks: 1. Sales concentration risk. 2. Price compression risk (assuming the customer has leverage in the business relationship). 3. Credit risk, including payment failure, forced discounts, or slow pay. 4. Higher inventory levels. The last two risks result in trade-cycle lengthening, while all of them, independently and collectively, have an adverse effect on cash flow. For small businesses competing in a highly monopolized industry or characterized by a well-entrenched oligarchy controlling a majority market share, strong industry growth may not necessarily trickle down to smaller competitors. This should be kept in mind when evaluating aggressive growth plans of smaller competitors. If operating in a fiercely competitive, high-price-point product market (for example, big-ticket items) characterized by high elasticity of demand (a small change in price results in a large change in demand) and plentiful substitutes, the borrower may have little influence over prices and selling margins. Analyzing Cash Flow Sensitivity and Quantifying Risk Factors Having established a credit risk profile, it is now time to bake this profile into a series of cash flow projections and conduct a sensitivity analysis to assess the most likely cash flow scenario, with an eye toward predicting financial distress and quantifying specific risk factors. The process may include the following steps: Assessment of historical operating performance and financial condition. Financial projections massaged realistically in light of the borrower s assumptions. Identification of distress parameters, such as failure to pay secured and unsecured creditors on time. Quantification of key risks. Prediction of financial distress. A historical quality of earnings assessment should be a part of the review process, particularly when analyzing a turnaround. This assessment should include the separation of historical earnings into cash versus accrual earnings, with a focus on change in accruals from period to period. Significant increases in the accounts receivable trend (avoiding a single point of reference) should be supported by positive revenue trends, normal dilution and bad-debt experience, stable turnover, sufficient diversification, adequate proof-of-delivery documentation, and the absence of pre-billing. Increases in inventory should be supported by, among other things, satisfactory cost tests, test counts, absence of slow-moving inventory, and adequate inventory mix. Cash earnings are considered more sustainable than accrual earnings in the long run. When assessing cash flow projections in an attempted turnaround scenario where cost-cutting measures are involved, check the validity of assumptions by comparing current and projected operating expenses on a commonsize basis to peer averages. Experience suggests that borrowers often are overly optimistic in their forecasts, so assumptions must be scrutinized closely and tempered with reality. Consider comparing results to industry statistics available from RMA, IBISWorld, Standard & Poor s, or Value Line and look for differences in both small and large business sectors. Earnings performance should be evaluated over the course of a complete economic cycle. Also, be wary of adjusted earnings or EBITDA presentations. Assumptions for 30 April 2012 The RMA Journal

4 nonrecurring items must be scrutinized closely. The cash flow sensitivity analysis will involve testing for various change rates in the following cash flow drivers, based on the credit risk profile already established: 1. Sales change percentage. 2. Gross margin (GM) percentage change. 3. Change in net trade-cycle days in absolute dollars, indicating the degree of working-capital intensity. The longer the net trade cycle (NTC), the greater the attendant required working-capital investment. 4. Degree of operating leverage (DOL): Fixed costs (FC) versus variable costs (VC). The greater the VC, the greater the elasticity. Measured as: Sales VC/Sales VC FC; measures percentage of EBIT change per 1% change in level of output. This is a measure of business risk. 5. Degree of capital intensity: ongoing investment in fixedasset requirements. 6. Degree of financial leverage (DFL): Measured as EBIT/ EBIT I, measures earnings per share change percentage resulting from a 1% change in EBIT. This is a measure of financial risk. In our hypothetical example above, our borrower, ABC Company, is a widget manufacturer. The high-risk factors include the following: Economic recession. Cyclical nature. High demand power (customer has leverage). High degree of operating leverage. Working-capital intensive. High customer concentration level (25%). Table 2 highlights ABC Company s financial results for the most recent fiscal year and is the beginning point for the cash flow sensitivity testing. Scenario 1: Cash break-even point of financial distress Assumptions include the following: A 10% sales decline. GM percentage decline from 30% to 29%. Accounts receivable days: 50. Inventory days: Default rate of interest: 10% (violation of debt-service covenant). The asset-based lender reduces the rate of advance on inventory by 5%. The objective here is to assess the prospective distance from financial distress, while understanding the combination of factors and the degree of change necessary to reach financial distress. Table 2 Financial Results for ABC Company (in thousands) FYE Date: 12/31/11 Operating Results WC Changes Direct Cash Flow Indirect Cash Flow Est. Sales Base Sales Beg AR 1479 Cash Receipts Chg WC -108 COGS Growth 600 End AR 1553 Cash COGS 8855 Basic CF 459 Base COGS 8400 Chg AR -74 Cash GM 3672 CFFO 351 GM (%) % Beg Inv 1726 Cash Oper Exp 3321 CAPEX -50 Fixed OE % End Inv 1812 CFFO 351 Asset Sale 0 Var. OE(%) % Chg Inv -86 Beg. LTD 1500 CFFI -50 Tot. OE(%) % Beg AP 1036 End LTD 1350 CMLTD 150 EBIT (%) % End AP 1087 End LOC 1489 New LT Loan 0 Total Int. Ex. 191 Non-FCC Int. 90 Chg AP 52 End Debt 2839 Net Chg NP -150 FIT (%) % TRADE CYCLE (TC) Beg Liab Add 'l PIC/DIV 0 IAT (%) % AR Days 45 End Liab 3926 CFFF -150 Depr 100 Inv Days 75 Cash Resources NCF 151 EBITDA % AP Days 45 Cash Required Net Cash Sur 151 Basic CF % NET TC 75 Net Cash 233 Net Cash Def 0 Beg. Equity 1000 End Equity 1359 Total Assets 5286 Cash Coverage 1.02 ABL Draw 0 NWC 789 ABL Pymt 151 Financial Ratios GM-VC 2835 RLOC ABL Assets/Liab 1.35 FREE CF 0 BCF/CMLTDex 2.30 CM-FC 735 Beg. RLOC Bal 1640 NWC/TA 0.15 CFFO/CMLTD 2.34 DOL 3.86 ABL Line 2000 RE/TA 0.26 CFL/CMEX 2.16 DFL 1.35 Borrow Base 1722 NW/TL 0.35 Debt/NW 2.89 DTL 5.21 Add'l$ Avail. 82 EBIT/TA 0.14 Debt/EBITDA 3.40 TA/EBITDA 6.33 ABL Interest 101 Sales/TA 2.38 B.E. Sales $10,182 EBIT/Int End ABL Bal Z-Score 3.59 BE BCF % 0.86% FCFF 427 ABL Avail$YE 233 Z-score > 3=healthy; >1.8<3=undefined;,1.8=bankruptcy April 2012 The RMA Journal 31

5 Table 3 Results of Tests for Probability of Financial Distress (in thousands) Result Base Case Break-even Case Most Likely Case Sales $12,600 $11,340 $10,710 Sales growth 5% <10%> <15%> Break-even sales $10,182 $11,473 $12,058 GM% 30% 29% 28% Net income $359 <$19> <$182> EBITDA $835 $ Net cash $233 $0 <$284> A/R days Inventory days A/P days Scenario 2: Most likely case Assumptions include the following: A 15% sales decline. GM percentage decline from 30% to 28%. Accounts receivable days stretch to 55. Inventory days stretch to 85. Default rate of interest of 10% (due to violation of debtservice covenant) is charged. Asset-based lender reduces rate of advance on inventory by 5% as a precautionary measure. Justification for Scenario 2 Assumptions The economy has just entered the early stages of a severe recession. A downward trend is predicted for our borrower s industry, which can be described as mature, cyclical in nature, and controlled by an oligarchy. Moreover, this borrower s customers bear a high degree of demand power, and the largest During and after the recent financial crisis, commercial lenders watched various renditions of the above scenario play out across a number of industries, impacting numerous borrowers. 45 implied stretch to 58 Borrowing base $1,722 $1,600 $1,668 EBIT/Int CFFO/CMLTD <1.75> Debt/Net worth DOL DFL 1.35 <11.82> <0.35> Z-score 3.59 healthy 3.16 healthy 2.75 undefined Implied rating BBB CC D Probability of distress 2.5% 48.2% 80% customer represents 25% of the borrower s business. The projected sales and gross margin declines are in accordance with negative industry forecasts and are exacerbated by the heavy dependence on a major client, which is itself now under stress. Furthermore, as is so often the case, optimism veils the oncoming financial storm and the borrower is unprepared, having failed to enact critical preemptive cost and inventory reductions. Meanwhile, the borrower s customers are delaying payment as self-preservation instincts kick in amid deteriorating economic conditions and uncertainty. The combination of these factors compresses both sales levels and selling margins while stretching the borrower s trade cycle. The asset-based lender responds by charging the default rate of interest, while reducing its rate of advance on inventory by 5%. The result is obviously financial distress, as evidenced by the dramatic swing in net cash from $233,000 in the prior year to a deficit of $284,000 currently, a negative change of $517,000, as noted in Table 3. Net cash is the difference between cash resources (equivalent to cash receipts from operations plus additional unused borrowing base availability) and cash required (equivalent to all operating cash requirements; assumes vendors are paid within 45 days) plus nonfinanced capital expenditures and required principal debt payments. Deficit net cash represents financial distress. During and after the recent financial crisis, commercial lenders watched various renditions of the above scenario play out across a number of industries, impacting numerous borrowers. It is important to quantify key risk factors as measured in absolute dollars and on some basis such as a percentage of total cash needs annually, while considering the relative materiality of the risk factor as a function or in relation to the specific operating environment. For example, the materiality of concentration risk escalates with rising operating and financial leverage, while operating near the break-even sales level with limited liquidity to absorb the loss of a major customer. On the other hand, a company bearing a highly elastic cost structure operating well above break-even may easily absorb the loss of a key account. A key question with regard to concentration risk is which party has the leverage in the relationship. The answer to this question helps determine the probability of the loss of a key account or a margin squeeze forced by the key customer. In our example above, leaving all else constant, the loss of the major client (25%) would result in a negative earnings swing of $449,000. Assuming a probability factor of 25% for the occurrence of this event implies an absolute-dollar loss risk of $112,000. Meanwhile, assuming a 75% likelihood of a severe recession, leading to a sales contraction of 15% given the borrower s high-risk industry, results in a earnings reversal of $265,000, or an absolute-dollar risk factor of $199,000, which could be classified as the most significant individual risk factor. As reflected in Table 4, there is a dramatic increase in the probability of distress beginning with rating B down to D. This section of the scale represents a significant share of the 32 April 2012 The RMA Journal

6 asset-based lending playing field. For asset-based lenders, this is likely not far from experiential reality, which marks the need for financial distress sensitivity analysis as a critical tool in the portfolio manager s toolkit. Key Ratios and What They Imply for Cash Flow It is critical to use the above process to identify the financial profile of successful borrowers based on cash flow sensitivity analysis and the resulting range of meaningful financial ratios that accompany success, while answering the critical question of the borrower s capacity to generate sufficient cash resources to meet cash requirements on a sustainable basis. Does the borrower have the cash flow/liquidity capacity to absorb not simply a cyclical downturn but a systemic shock under a worst-case scenario? There are many in the financial and economic communities who fear another looming financial crisis related to sovereign debt and underlying credit derivatives. In today s global financial world, it is no longer enough to simply assume a normal business cycle. Many believe the fallout of the financial crisis may be leading to a new normal that has yet to reveal itself. It is important to note the changes in key ratios between the scenarios and the implications from a cash flow perspective. It also is important to recognize the limitations of certain traditional accounting ratios such as debt-to-equity or tangible net worth (TNW) when viewed in isolation. Equity is an accounting value, while TNW is essentially an adjusted accounting value. Each is rarely consistent with actual equity value as determined by market value or liquidation value for a going concern. This obviously begs the question of what these two terms actually represent in a meaningful credit analysis. TNW may or may not have meaningful implications for a reserve cushion to absorb deficit cash flows or as a cushion of assets against debts. These values must be viewed with other key financial barometers to derive meaningful insights regarding a borrower s liquidity, solvency, or ability to meet obligations. Today s asset-based lender must consider firm valuation as part of the credit analysis and understand the application of valuation methodologies in assessing prospective borrowers beyond that of simply applying a liquidation scenario unless it is determined that the company is incapable of continuing as a going concern and that its greatest value lies in the liquidation of its parts. It is important to separate business risk from finance risk and assess operational and financial restructuring efforts. If the business is capable of continuing as a going concern, what is its enterprise value? The higher the value, the greater the comfort level afforded to a secured lender in knowing that the probability of a safe exit from a troubled loan is enhanced. In the event financial distress is evident, a key consideration should be whether or not the operation is broken or if the distress is a function of Table 4 Greater than If interest coverage ratio is poor capitalization, which might be remedied through a recapitalization effort. Conclusion The above process for analyzing financial distress may uncover information critical to asset-based lenders and commercial lenders alike, irrespective of underlying collateral position. A proactive approach to implementing this predictive process may alert both lender and borrower to impending financial distress and perhaps enable each party to take timely and critical steps to mitigate key risks. These could include cost-cutting efficiency Ratings* to Rating is Cumulative probability of distress (5 years) D 80.00% C 69.65% CC 48.22% CCC 39.15% B % B 24.04% B % BB 9.27% BBB 2.50% A- 1.35% A 0.20% A+ 0.19% AA 1.00% AAA 0.75% *Derived from information in The Cost of Distress: Survival, Truncation Risk and Valuation, by Aswath Damodaran, New York University, January The higher the value, the greater the comfort level afforded to a secured lender in knowing that the probability of a safe exit from a troubled loan is enhanced. measures, revenue diversification, additional equity injections, vendor assistance, and heightened awareness of proficient trade-cycle management all steps that could make the difference between failure and long-term sustainability. v Stan Scott is senior vice president and underwriting manager, First Capital, Oklahoma City, Oklahoma. He can be reached at sscott@firstcapital.com. To learn more, go to RMA s Annual Statement Studies: Industry Default Probabilities and Cash Flow Measures. April 2012 The RMA Journal 33