Tyler Technologies Beneish M-Score Historical Data
The historical data trend for Tyler Technologies'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.
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Tyler Technologies Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.54 |
-2.78 |
-2.51 |
-2.54 |
-2.63 |
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Tyler Technologies Quarterly Data
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Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
| Beneish M-Score |
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-2.54 |
-2.65 |
-2.53 |
-2.57 |
-2.63 |
Competitive Comparison
For the Software - Application subindustry, Tyler Technologies'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.
Tyler Technologies Beneish M-Score Distribution
For the Software industry and Technology sector, Tyler Technologies's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Tyler Technologies's Beneish M-Score falls into.
Tyler Technologies 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 Tyler Technologies 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 * 1.0177 | + | 0.528 * 0.9603 | + | 0.404 * 0.9998 | + | 0.892 * 1.0549 | + | 0.115 * 0.966 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.078 | + | 4.679 * -0.046582 | - | 0.327 * 0.8659 |
| = | -2.63 |
* 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 (Dec23) TTM: | Last Year (Dec22) TTM: |
Total Receivables was $620 Mil.
Revenue was 480.934 + 494.684 + 504.279 + 471.853 = $1,952 Mil.
Gross Profit was 212.925 + 225.16 + 223.177 + 199.837 = $861 Mil.
Total Current Assets was $861 Mil.
Total Assets was $4,677 Mil.
Property, Plant and Equipment(Net PPE) was $209 Mil.
Depreciation, Depletion and Amortization(DDA) was $171 Mil.
Selling, General, & Admin. Expense(SGA) was $458 Mil.
Total Current Liabilities was $1,001 Mil.
Long-Term Debt & Capital Lease Obligation was $636 Mil.
Net Income was 38.903 + 47.011 + 49.13 + 30.875 = $166 Mil.
Non Operating Income was 0.652 + 0.787 + 0.643 + 1.246 = $3 Mil.
Cash Flow from Operations was 147.419 + 177.496 + -19.184 + 74.709 = $380 Mil.
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Total Receivables was $577 Mil.
Revenue was 452.221 + 473.191 + 468.685 + 456.108 = $1,850 Mil.
Gross Profit was 193.333 + 204.663 + 193.448 + 192.418 = $784 Mil.
Total Current Assets was $847 Mil.
Total Assets was $4,687 Mil.
Property, Plant and Equipment(Net PPE) was $224 Mil.
Depreciation, Depletion and Amortization(DDA) was $172 Mil.
Selling, General, & Admin. Expense(SGA) was $403 Mil.
Total Current Liabilities was $890 Mil.
Long-Term Debt & Capital Lease Obligation was $1,005 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) |
| = | (619.704 / 1951.75) | / | (577.257 / 1850.205) |
| = | 0.317512 | / | 0.311996 |
| | = | 1.0177 |
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) |
| = | (783.862 / 1850.205) | / | (861.099 / 1951.75) |
| = | 0.423662 | / | 0.441193 |
| | = | 0.9603 |
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 - (860.585 + 208.759) / 4676.663) | / | (1 - (847.242 + 223.775) / 4687.417) |
| = | 0.771345 | / | 0.771512 |
| | = | 0.9998 |
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 |
| = | 1951.75 | / | 1850.205 |
| | = | 1.0549 |
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)) |
| = | (172.041 / (172.041 + 223.775)) | / | (170.767 / (170.767 + 208.759)) |
| = | 0.434649 | / | 0.449948 |
| | = | 0.966 |
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) |
| = | (458.345 / 1951.75) | / | (403.066 / 1850.205) |
| = | 0.234838 | / | 0.217849 |
| | = | 1.078 |
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) |
| = | ((636.028 + 1001.138) / 4676.663) | / | ((1005.438 + 889.695) / 4687.417) |
| = | 0.350071 | / | 0.404302 |
| | = | 0.8659 |
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 |
| = | (165.919 - 3.328 | - | 380.44) | / | 4676.663 |
| | = | -0.046582 |
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.
Tyler Technologies has a M-score of -2.63 suggests that the company is unlikely to be a manipulator.
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