Bankers! Are you tired of poring over tedious loan applications? Do you lie awake at night worrying about shaky credits to small companies? Are all those meetings with small-business loan supplicants cutting into time you could be spending with family or friends? Is the golf game suffering?

Well, cheer up. Right now, all over the country, loan officers are reaching for a handy, all-purpose test that can determine the financial viability of any small company. The test can be found in the July issue of one of the commercial banking profession's most prestigious publications, The Journal of Commercial Bank Lending. It is a neat little formula that its authors describe, with pleasant forthrightness, as a "bankruptcy classification model for small firms."

All that is required is a finger (or some other means of pressing a button), a calculator with a logarithmic function, and the prospective client's latest financial statements. The formula does the rest. Within a matter of seconds, it yields an "H-score": a number with a plus or minus sign in front of it. This is the company's fate. But either way, thumbs up or down, "H" means Happiness for bankers, Humility for small business owners.

A great deal of ingenuity and statistical know-how has gone into the creation of this new formula. The work of three professors (two from the University of Tennessee, one from the University of South Florida) and an insurance company statistician, it was derived from a study of the financial data of 60 small businesses, furnished by banks in the southeastern corner of the country. The companies, whose average revenues were about $1 million a year, were painstakingly grouped to assure industrial comparability.Half had filed for bankruptcy, and half had not.

After numerous experiments on the data, the researchers boiled 40 ratios down to 9, in what amounts to a "One-Minute" test. The authors say that, had the test been available when all 60 companies were still in business, lending officers could have predicted within a few percentage points of dead certainty which ones were headed for failure.

To illustrate the elegance and simplicity of the new screening device, consider the hypothetical case of banker Titus A. Rock, who has recently received a loan request from Strivers Inc., a struggling young company with sales of $3 million and earnings of $93,000 (before interest and taxes).

Titus's first task is to sort out Strivers's balance sheet and income statements to find the relevant data with which to calculate the nine variables. Some bankers, it is true, may encounter certain conceptual difficulties here. John G. Fulmer Jr., professor of finance at the University of Tennessee at Chattanooga, reports that, since publication of the article, he and his co-authors have received phone calls and letters "from bankers all over the country," asking for help. In some cases, the problem seems to be a simple digital awkwardness. "They want to make sure they're hitting the right key on the calculator," says Fulmer. But in other instances the trouble seems almost professional: "They're asking questions like 'How do you calculate cash flow?"

Nevertheless, such potential borrowers as Strivers would be wise to assume that bankers have full control over their fingers, and a working acquaintance with such concepts as cash flow. Armed with these, lending officers like Titus may then briskly proceed to the task at hand, calculating the nine variables. Each variable was selected to highlight a specific dimension of business health.

The first variable -- or V[1], as it has been named -- is made up of retained earnings divided by total assets. Fulmer and his associates picked this one to measure a company's profitability over time. Titus is asked to assume that the higher the ratio, the less likely the company is to fail -- at least, that is, in the near-term. Clutching his calculator tightly, he punches in $360,000, divides it by $2.7 million, and gets .133.

Next comes V[2], sales divided by total assets. This was picked to show the speed with which sales are generated on a given asset base. The speedier the turnover, the more comfort for the lender. Titus inputs $3 million, divides by $2.7 million, and the display, by golly, flashes 1.111. So far, so good.

V[3] represents earnings before taxes divided by equity, a means of gauging profitability unobscured by tax implications. Everybody likes to see black ink, including bankers. Titus plugs in $22,000, divides by the sum of equity and retained earnings, getting .032.

He moves on to the next one, V[4], which measures cash flow, the lifeblood of any business. This calculation calls for dividing cash flow by total debt. Is the cash flowing? Titus divides cash flow -- the sum of net earnings and depreciation -- by the sum of short- and long-term debt, and the answer is .088.

Titus, a quick learner, is getting the hang of it now, so he quickly proceeds to V[5], a ratio that measures the degree of leverage. It consists of total debt divided by total assets. The higher the leverage, the more reason for concern, Titus reasons to himself. He punches in $2.02 million, divides by $2.7 million. The one-line screen reads .748.

Four more to go. Titus notices that V[6] is, on the surface, another type of leverage ratio. It measures current liabilities as related to total assets. But the researchers were surprised to discover that it evidently summarizes something else as well, something they can't put their finger on. In any case, their original assumption -- that the higher the ratio, the greater the likelihood of failure -- didn't prove out. In fact, the inverse was more accurate. Titus dutifully divides $920,000 by $2.7 million and gets .341.

V[7] reflects business size by calculating the logarithm of tangible total assets. In the course of their research, the authors noticed that larger businesses didn't fail as frequently as smaller ones, a finding that was consistent with those of previous academic studies. Titus enters $2.7 million (the sum of current and fixed assets), taps the log key, and his display reads 6.447.

Titus is approaching the fateful number. V[8] measures liquidity, expressed by dividing working capital by total debt. In distilling the variables from 40 to 9, the professors found that low liquidity ratios were particularly reliable indicators of trouble. Titus inputs $780,000, divides by $2.02 million, and .386 appears.

He has reached V[9] now, with no greater anguish to show for his labors than a trembling forefinger. The final variable provides him with an insight into whether or not the borrower will be able to cover interest costs, something any banker is inclined to take seriously. It is calculated from the logarithm of earnings before interest and taxes, divided by interest. The higher the number, the greater the safety.Titus takes a deep breath as he divides $93,000 by $71,000. Answer: 1.3. Then he hits the log key. Up pops .114.

Naturally, Titus has been jotting down notes on the above maneuvers; he isn't yet entirely comfortable with his calculator's memory functions. But with Strivers's unruly balance sheet thus subdued, all that remains is a one-finger exercise on his tiny keypad, a matter of inserting each of the nine variables into its proper place in a prescribed formula.

The equation may look intimidating, but it is actually quite simple:

-6.075 + 5.528 (V[1]) + .212 (V[2]) + .073 (V[3]) + 1.270 (V[4]) - .120 (V[5]) + 2.335 (V[6]) + .575 (V[7]) + 1.083 (V[8]) + .894 (V[9]) = H

Then, presto digito, that's all there is to it. For Strivers, the H-score comes out to be minus .06.

Alert readers will have remarked that the new screening formula can yield a firmly negative H-score even when the company is profitable, as Strivers is. Professor Fulmer concedes this, and more. Not for a moment does he expect his nine-variable test to supplant those qualities of shrewdness, imagination, optimism, and judgment on which the best lending officers have prided themselves and built their careers. "A banker still has to evaluate character," says Fulmer, "and that requires using judgment."

But Fulmer is far too modest. Indeed, the H-factor test could revolutionize the banking industry. It will take time, of course: Some bankers will be slow to grasp the incalculable significance of the new tool; others, sadly, mayd never acquire the manual dexterity needed to use a modern calculator and computer; others, sadder still, may never even learn to read a financial statement.

Nevertheless, with rising professional standards and the help of the software industry, we can expect the new test to come into its own wherever bank loans are made to small businesses. As a result, loan officers everywhere will soon be able to sleep more soundly, knowing that all of their small business customers have one important thing in common -- a positive H-score.

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