Last thing an organization wishes for is default by its customer or vendors. The fact is, it cannot be eliminated but can definitely be minimized, if tracked beforehand. To track the future uncertainty – Risk scoring model can be a very useful tool for organizations or any individuals wanting to minimize risk. In this article we will be talking about Risk scoring models, why to use them and most commonly used models. At the end, we will also discuss how you can know the risk score of your customer or vendors to determine the level of reliability.
Table of Content
What are Risk Scoring Models?
The process of calculating a number, or score, to help determine the risk level of a vendor, customer, or business entity in the presence of risk factors is called risk scoring. Risk rating models are tools used to assess the probability of default. The approach of using a risk based score helps businesses capture more information about users than they can do with the traditional KYC methods. It’s the quantifiable number that allows us to quickly and confidently make informed decisions regarding risks.
Usage of Risk Scoring Models?
Risk Scoring Models is deeply interlinked with minimizing the risk, thus, are used in many domains such as:
- Company risk management
- capital allocation
- portfolio management
- Customer or vendor onboarding
Benefits of Risk Scoring Models
One of the biggest benefits of using Risk scoring models is to identify and mitigate risks that have the potential to damage operations and the reputation of a business. Other than this Risk Scoring model results that are quantifiable, and it is said you cannot manage what you cannot see. So, because risk scoring models provide a quantitative number , it is easy to measure and compare with other institutes to set a benchmark and make informed decisions. Another benefit of using different risk scoring models are these models are universally accepted and thus have a common language to compare.
Types of Risk Scoring Models
There are 4 different types of Risk Scoring models, that we will be discussing in this article
- Piotroski’s F Score Model
- Beneish’s M-Score Model
- Altman’s Z Score Model
- Montier’s C Score Model
Piotroski’s F Score Model
The Piotroski F score is a quantitative number between 0 and 9 that incorporates nine factors that assess a company’s financial strength. These 9 factors are categorized into three different sources of financial strength, which are
- Profitability Strength
- Leverage & Liquidity Strength
- Operating Efficiency
A score of either 0 or 1 is rewarded for each of these factors, depending on whether it has been fulfilled or not. The higher the score, the more reliable the company is. A company that has a Piotroski F-score of 8–9 is considered to be strong. Alternatively, firms achieving the F-score of 0–2 are considered to be weak.
These 3 categories are further divided into 9 categories, that are
Profitability Strength is calculate for 4 points and the break up of 4 points are mentioned below:
- ROA: Return on assets. Net Income divided by year beginning total assets. F score is 1 if ROA is positive, 0 otherwise.
- OCF: Operating cash flow divided by year beginning total assets. F score is 1 if CFO is positive, 0 otherwise.
- ∆ROA: Change in ROA from the prior year. If ∆ROA > 0, F score is 1. Otherwise, F score is 0.
- ACCRUALS: OCF compared to ROA. If OCF > ROA, F score is 1. Otherwise, F score is 0.
Leverage & Liquidity Strength
Leverage & Liquidity Strength is calculated for 2 points and the breakup of 2 points are mentioned below:
- ∆LEVERAGE: Change in long-term debt/average total assets ratio. If the ratio compared to the prior year is lower, F score is 1, 0 otherwise.
- ∆CURRENT RATIO: Change in current ratio. If the current ratio increases from the prior year, F score is 1, 0 otherwise.
- EQ_OFFER: Total common equity between years. If common equity increases compared to prior year, F score is 1, 0 otherwise.
Operating Efficiency is calculated for 2 points and the breakup of 2 points are mentioned below:
- ∆MARGIN: Change in gross margin ratio. If the current year’s ratio minus prior year’s ratio > 0, F Score is 1, 0 otherwise.
- ∆TURNOVER: Change in asset turnover ratio (revenue/beginning year total assets). If current year’s ratio minus prior years > 0, F score is 1, 0 otherwise.
Beneish’s M Score Model
The Beneish M Score model is a mathematical model that uses financial ratios and eight variables to identify whether a company has manipulated its earnings. It is used as a tool to uncover financial fraud. The variables are constructed from the data in the company’s financial statements, and once calculated, create an M-Score to describe the degree to which the earnings have been manipulated.
If M-score is less than the -2.22, then it suggests that the company under consideration is not a manipulator. If M-score is more than -2.22, then it provides the signal that the company can be the manipulator.
The Beneish’s M Score model’s seven variables are:
1. Days’ Sales in Receivables Index (DSRI) It is the ratio of days sales in receivables in a year with respect to the previous year. The large increase in the value of DSR is an indicator of revenue inflation. DSRI = (Net Receivables / Salest) / Net Receivables t-1 / Sales t-1)
2. Gross Margin Index (GMI) It is the ratio of gross margin of a year with respect to the previous year. GMI = [(Sales t-1– COGS t-1) / Sales t-1] / [(Salest – COGSt) / Salest]
3. Asset Quality Index (AQI) It is the ratio of non-current assets to total assets of a year versus the prior year. AQI = [1 – (Current Assets t + PP&E t + Securities t) / Total Assets t] / [1 – ((Current Assets t-1+ PP&E t-1 + Securities t-1) / Total Assets t-1)]
4. Depreciation Index (DEPI) It is the ratio of the rate of depreciation of a year with respect to the previous year. DEPI = (Depreciation t-1/ (PP&E t-1 + Depreciation t-1)) / (Depreciation t / (PP&E t + Depreciation t))
5. Sales, General, and Administrative expenses Index (SGAI) It is the ratio of SG&A expenses of a year with respect to the previous year. SGAI = (SG&A Expense t / Sales t) / (SG&A Expense t-1/ Sales t-1)
6. Leverage Index (LVGI) It is the ratio of total debt to total assets of a year with respect to the previous year. LVGI = [(Current Liabilities t + Total Long Term Debt t) / Total Assets t] / [(Current Liabilities t-1 + Total Long Term Debt t-1) / Total Assets t-1]
7. Total Accruals to Total Assets (TATA) It is calculated as the change in the accounts of working capital other than the cashless depreciation. TATA = (Income from the Continuing Operations t – Cash Flows from the Operations t) / Total Assets t
Seven different types of indices are weighted together as per the following formula to derive at the Beneish’s M-score:
M Score Formula = -4.84 + 0.92 * DSRI + 0.528 * GMI + 0.404 * AQI + 0.115 * DEPI – 0.172 * SGAI + 4.679 * TATA – 0.327 * LVGI
Altman’s Z Score Model
Altman’s Z-Score model is a numerical measurement that is used to predict the chances of a business going bankrupt. Z-Score is based on five financial ratios that can be calculated from data found on a company’s annual report. It uses profitability, leverage, liquidity, solvency, and activity to predict whether a company has a high probability of becoming insolvent.
A score below 1.8 means it’s likely the company is headed for bankruptcy, while companies with scores above 3 are not likely to go bankrupt.
The Altman’s Z Score model’s five financial ratios are:
- A = working capital / total assets
- B = retained earnings / total assets
- C = earnings before interest and tax / total assets
- D = market value of equity / total liabilities
- E = sales / total assets
Altman’s Z Score Model Score = = 1.2A + 1.4B + 3.3C + 0.6D + 1.0E
Montier’s C Score Model
Montier’s C-score, developed by James Montier, takes into account six parameters to determine whether a company is cooking its books. It indicates the probability of financial manipulations based on a quantitative method. C-Score is a discrete score between 0-6 which reflects six criteria used to determine whether a company is cooking the books.
If a company scores 0 there is no evidence of earnings manipulation whilst 6 suggests there is lots of evidence.
The Six parameters to check Montier’s C Score are:
- Growing divergence between net income and cash flow (1 point). A higher level of accruals is associated with a higher likelihood of profit manipulation.
- Increasing receivable days (1 point). A large increase in receivable days might suggest accelerated revenue recognition to inflate profits.
- Increasing inventory days (1 point). Increasing inventory days could suggest that input costs are being artificially flattered or that sales growth is slowing.
- Increasing other current assets (1 point). Companies might be aware that investors often look at receivables and inventory, and might disguise problems in current assets.
- Declines in depreciation relative to gross fixed assets (1 point). Firms have been known to lower depreciation charges in order to inflate profits.
- Total asset growth in excess of 10% (1 point). Some companies become serial acquirers and use acquisitions to distort profits.
How to calculate the Risk Score of your Customers or Vendors?
To calculate the Risk score of any potential customer or vendor company, you have to aggregate all company financial data and use the above mentioned formula. Or Use Platforms like InstaFinancials, where we provide company report – Brisk, with Features like : Risk Scoring Models, Red Flags Analysis, Peer Comparison, News & Sentiment Analysis and Compliance Matrix. The most extensive & exclusive business & risk analytical, actionable insights of Indian companies. One report that fits corporate data needs of all your business functions.