VERSES AI (VERSES AI) Beneish M-Score : -6.30 (As of May. 16, 2024)

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What is VERSES AI Beneish M-Score?

The zones of discrimination for M-Score is as such:

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.

Good Sign:

Beneish M-Score -6.3 no higher than -1.78, which implies that the company is unlikely to be a manipulator.

The historical rank and industry rank for VERSES AI's Beneish M-Score or its related term are showing as below:

VRSSF' s Beneish M-Score Range Over the Past 10 Years
Min: -6.3 Med: -2.87 Max: -2.64
Current: -6.3

During the past 2 years, the highest Beneish M-Score of VERSES AI was -2.64. The lowest was -6.30. And the median was -2.87.

VERSES AI Beneish M-Score Historical Data

The historical data trend for VERSES AI'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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VERSES AI Beneish M-Score Chart

VERSES AI Annual Data

Trend

Mar22

Mar23

Beneish M-Score

VERSES AI Quarterly Data
	Jun21	Sep21	Dec21	Mar22	Jun22	Sep22	Dec22	Mar23	Jun23	Sep23	Dec23
Beneish M-Score	Get a 7-Day Free Trial						-	-	-2.87	-2.64	-6.30

Competitive Comparison of VERSES AI's Beneish M-Score

For the Software - Infrastructure subindustry, VERSES AI'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.

VERSES AI's Beneish M-Score Distribution in the Software Industry

For the Software industry and Technology sector, VERSES AI's Beneish M-Score distribution charts can be found below:

* The bar in red indicates where VERSES AI's Beneish M-Score falls into.

VERSES AI 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 VERSES AI for today is based on a combination of the following eight different indices:

-4.84

0.92 * DSRI

0.528 * GMI

0.404 * AQI

0.892 * SGI

0.115 * DEPI

-4.84

0.92 * 1.4707

0.528 * 1.0746

0.404 * 0

0.892 * 1.1352

0.115 * 0.6602

0.172 * SGAI

4.679 * TATA

0.327 * LVGI

0.172 * 2.0183

4.679 * -0.795088

0.327 * 1.1407

-6.27

This Year (Dec23) TTM:

Last Year (Dec22) TTM:

Total Receivables was $4.14 Mil.
Revenue was 0.545 + 0.559 + 0.276 + 0.392 = $1.77 Mil.
Gross Profit was 0.148 + 0.084 + 0.006 + 0.137 = $0.38 Mil.
Total Current Assets was $11.09 Mil.
Total Assets was $11.40 Mil.
Property, Plant and Equipment(Net PPE) was $0.31 Mil.
Depreciation, Depletion and Amortization(DDA) was $0.26 Mil.
Selling, General, & Admin. Expense(SGA) was $23.03 Mil.
Total Current Liabilities was $3.89 Mil.
Long-Term Debt & Capital Lease Obligation was $0.14 Mil.
Net Income was -14.903 + -7.995 + -8.139 + -5.272 = $-36.31 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = $0.00 Mil.
Cash Flow from Operations was -7.522 + -9.438 + -6.399 + -3.886 = $-27.25 Mil.

Total Receivables was $2.48 Mil.
Revenue was 0.561 + 0.279 + 0.374 + 0.347 = $1.56 Mil.
Gross Profit was 0.085 + 0.147 + 0.1 + 0.023 = $0.36 Mil.
Total Current Assets was $6.87 Mil.
Total Assets was $8.01 Mil.
Property, Plant and Equipment(Net PPE) was $0.42 Mil.
Depreciation, Depletion and Amortization(DDA) was $0.18 Mil.
Selling, General, & Admin. Expense(SGA) was $10.05 Mil.
Total Current Liabilities was $2.33 Mil.
Long-Term Debt & Capital Lease Obligation was $0.15 Mil.

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)
	=	(4.142 / 1.772)	/	(2.481 / 1.561)
	=	2.337472	/	1.589366
	=	1.4707

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)
	=	(0.355 / 1.561)	/	(0.375 / 1.772)
	=	0.227418	/	0.211625
	=	1.0746

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 - (11.092 + 0.308) / 11.4)	/	(1 - (6.872 + 0.416) / 8.01)
	=	0	/	0.090137
	=	0

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
	=	1.772	/	1.561
	=	1.1352

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))
	=	(0.178 / (0.178 + 0.416))	/	(0.256 / (0.256 + 0.308))
	=	0.299663	/	0.453901
	=	0.6602

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)
	=	(23.032 / 1.772)	/	(10.053 / 1.561)
	=	12.997743	/	6.440102
	=	2.0183

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)
	=	((0.142 + 3.886) / 11.4)	/	((0.154 + 2.327) / 8.01)
	=	0.353333	/	0.309738
	=	1.1407

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
	=	(-36.309 - 0	-	-27.245)	/	11.4
	=	-0.795088

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.

VERSES AI has a M-score of -6.27 suggests that the company is unlikely to be a manipulator.

VERSES AI Beneish M-Score Related Terms

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VERSES AI (VERSES AI) Business Description

Industry

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J9A:Germany VERS:Canada

Address

205 - 810 Quayside Drive, New Westminster, BC, CAN, V3M 6B9

Website

https://www.verses.ai

VERSES AI Inc is a cognitive computing company specializing in next-generation AI and developer of KOSM, the world's first network operating system for enabling distributed intelligence. KOSM generates a shared world model of contextualized data, policies, simulations, and workflows.