Fusion Finance Beneish M-Score Historical Data
The historical data trend for Fusion Finance's Beneish M-Score can be seen below:
* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD.
* For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.
Fusion Finance Beneish M-Score Chart
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Fusion Finance Annual Data
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Trend |
Mar20 |
Mar21 |
Mar22 |
Mar23 |
Mar24 |
| Beneish M-Score |
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- |
- |
- |
-1.35 |
-1.92 |
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Fusion Finance Quarterly Data
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Mar20 |
Mar21 |
Jun21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
Dec24 |
| Beneish M-Score |
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- |
-1.92 |
-2.14 |
-2.07 |
-2.37 |
Competitive Comparison of Fusion Finance's Beneish M-Score
For the Credit Services subindustry, Fusion Finance's Beneish M-Score, along with its competitors' market caps and Beneish M-Score data, can be viewed below:
* Competitive companies are chosen from companies within the same industry, with headquarter located in same country, with closest market capitalization; x-axis shows the market cap, and y-axis shows the term value; the bigger the dot, the larger the market cap. Note that "N/A" values will not show up in the chart.
Fusion Finance's Beneish M-Score Distribution in the Credit Services Industry
For the Credit Services industry and Financial Services sector, Fusion Finance's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Fusion Finance's Beneish M-Score falls into.
Fusion Finance Beneish M-Score Calculation
The M-score was created by Professor Messod Beneish. Instead of measuring the bankruptcy risk (Altman Z-Score) or business trend (Piotroski F-Score), M-score can be used to detect the risk of earnings manipulation. This is the original research paper on M-score.
The M-Score Variables:
The M-score of Fusion Finance for today is based on a combination of the following eight different indices:
| M | = | -4.84 | + | 0.92 * DSRI | + | 0.528 * GMI | + | 0.404 * AQI | + | 0.892 * SGI | + | 0.115 * DEPI |
| = | -4.84 | + | 0.92 * 0.9283 | + | 0.528 * 1.1187 | + | 0.404 * 1.9713 | + | 0.892 * 1.1323 | + | 0.115 * 0.94 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1 | + | 4.679 * -0.08077 | - | 0.327 * 1.0404 |
| = | -2.37 |
* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD.
* For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.
| This Year (Dec24) TTM: | Last Year (Dec23) TTM: |
Total Receivables was ₹91,525 Mil.
Revenue was 4408.4 + 6305 + 6283 + 5386.1 = ₹22,383 Mil.
Gross Profit was 760 + 2626.7 + 2694.9 + 2681 = ₹8,763 Mil.
Total Current Assets was ₹110,068 Mil.
Total Assets was ₹114,807 Mil.
Property, Plant and Equipment(Net PPE) was ₹277 Mil.
Depreciation, Depletion and Amortization(DDA) was ₹112 Mil.
Selling, General, & Admin. Expense(SGA) was ₹0 Mil.
Total Current Liabilities was ₹947 Mil.
Long-Term Debt & Capital Lease Obligation was ₹86,413 Mil.
Net Income was -7193.2 + -3050.4 + -356.2 + 1326.9 = ₹-9,273 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₹0 Mil.
Cash Flow from Operations was 0 + 0 + 0 + 0 = ₹0 Mil.
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Total Receivables was ₹87,071 Mil.
Revenue was 5476.3 + 5052.9 + 4951 + 4287.3 = ₹19,768 Mil.
Gross Profit was 2343 + 2150 + 2137.8 + 2026.5 = ₹8,657 Mil.
Total Current Assets was ₹102,031 Mil.
Total Assets was ₹104,318 Mil.
Property, Plant and Equipment(Net PPE) was ₹230 Mil.
Depreciation, Depletion and Amortization(DDA) was ₹85 Mil.
Selling, General, & Admin. Expense(SGA) was ₹0 Mil.
Total Current Liabilities was ₹1,018 Mil.
Long-Term Debt & Capital Lease Obligation was ₹75,279 Mil.
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1. DSRI = Days Sales in Receivables Index
Measured as the ratio of Revenue in Total Receivables in year t to year t-1.
A large increase in DSR could be indicative of revenue inflation.
| DSRI | = | (Receivables_t / Revenue_t) | / | (Receivables_t-1 / Revenue_t-1) |
| = | (91524.9 / 22382.5) | / | (87071.3 / 19767.5) |
| = | 4.089128 | / | 4.40477 |
| | = | 0.9283 |
2. GMI = Gross Margin Index
Measured as the ratio of gross margin in year t-1 to gross margin in year t.
Gross margin has deteriorated when this index is above 1. A firm with poorer prospects is more likely to manipulate earnings.
| GMI | = | GrossMargin_t-1 | / | GrossMargin_t |
| = | (GrossProfit_t-1 / Revenue_t-1) | / | (GrossProfit_t / Revenue_t) |
| = | (8657.3 / 19767.5) | / | (8762.6 / 22382.5) |
| = | 0.437956 | / | 0.391493 |
| | = | 1.1187 |
3. AQI = Asset Quality Index
AQI is the ratio of asset quality in year t to year t-1.
Asset quality is measured as the ratio of non-current assets other than Property, Plant and Equipment to Total Assets.
| AQI | = | (1 - (CurrentAssets_t + PPE_t) / TotalAssets_t) | / | (1 - (CurrentAssets_t-1 + PPE_t-1) / TotalAssets_t-1) |
| = | (1 - (110068.4 + 276.8) / 114806.5) | / | (1 - (102031.3 + 229.9) / 104317.5) |
| = | 0.038859 | / | 0.019712 |
| | = | 1.9713 |
4. SGI = Sales Growth Index
Ratio of Revenue in year t to sales in year t-1.
Sales growth is not itself a measure of manipulation. However, growth companies are likely to find themselves under pressure to manipulate in order to keep up appearances.
| SGI | = | Sales_t | / | Sales_t-1 |
| = | Revenue_t | / | Revenue_t-1 |
| = | 22382.5 | / | 19767.5 |
| | = | 1.1323 |
5. DEPI = Depreciation Index
Measured as the ratio of the rate of Depreciation, Depletion and Amortization in year t-1 to the corresponding rate in year t.
DEPI greater than 1 indicates that assets are being depreciated at a slower rate. This suggests that the firm might be revising useful asset life assumptions upwards, or adopting a new method that is income friendly.
| DEPI | = | (Depreciation_t-1 / (Depreciaton_t-1 + PPE_t-1)) | / | (Depreciation_t / (Depreciaton_t + PPE_t)) |
| = | (85.3 / (85.3 + 229.9)) | / | (111.9 / (111.9 + 276.8)) |
| = | 0.270622 | / | 0.287883 |
| | = | 0.94 |
Note: If the Depreciation, Depletion and Amortization data is not available, we assume that the depreciation rate is constant and set the Depreciation Index to 1.
6. SGAI = Sales, General and Administrative expenses Index
The ratio of Selling, General, & Admin. Expense(SGA) to Sales in year t relative to year t-1.
SGA expenses index > 1 means that the company is becoming less efficient in generate sales.
| SGAI | = | (SGA_t / Sales_t) | / | (SGA_t-1 /Sales_t-1) |
| = | (0 / 22382.5) | / | (0 / 19767.5) |
| = | 0 | / | 0 |
| | = | 1 |
7. LVGI = Leverage Index
The ratio of total debt to Total Assets in year t relative to yeat t-1.
An LVGI > 1 indicates an increase in leverage
| LVGI | = | ((LTD_t + CurrentLiabilities_t) / TotalAssets_t) | / | ((LTD_t-1 + CurrentLiabilities_t-1) / TotalAssets_t-1) |
| = | ((86413.1 + 947.3) / 114806.5) | / | ((75279 + 1018) / 104317.5) |
| = | 0.760936 | / | 0.731392 |
| | = | 1.0404 |
8. TATA = Total Accruals to Total Assets
Total accruals calculated as the change in working capital accounts other than cash less depreciation.
| TATA | = | (IncomefromContinuingOperations_t | - | CashFlowsfromOperations_t) | / | TotalAssets_t |
| = | (NetIncome_t - NonOperatingIncome_t | - | CashFlowsfromOperations_t) | / | TotalAssets_t |
| = | (-9272.9 - 0 | - | 0) | / | 114806.5 |
| | = | -0.08077 |
An M-Score of equal or less than -1.78 suggests that the company is unlikely to be a manipulator. An M-Score of greater than -1.78 signals that the company is likely to be a manipulator.
Fusion Finance has a M-score of -2.37 suggests that the company is unlikely to be a manipulator.
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