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SES (SES AI) Beneish M-Score : 0.00 (As of Mar. 15, 2025)


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What is SES 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.

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

During the past 6 years, the highest Beneish M-Score of SES AI was 0.00. The lowest was 0.00. And the median was 0.00.


SES AI Beneish M-Score Historical Data

The historical data trend for SES 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.

* Premium members only.

SES AI Beneish M-Score Chart

SES AI Annual Data
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SES AI Quarterly Data
Dec19 Sep20 Dec20 Mar21 Jun21 Sep21 Dec21 Mar22 Jun22 Sep22 Dec22 Mar23 Jun23 Sep23 Dec23 Mar24 Jun24 Sep24 Dec24
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Competitive Comparison of SES AI's Beneish M-Score

For the Auto Parts subindustry, SES 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.


SES AI's Beneish M-Score Distribution in the Vehicles & Parts Industry

For the Vehicles & Parts industry and Consumer Cyclical sector, SES AI's Beneish M-Score distribution charts can be found below:

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



SES 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 SES AI 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 * +0.528 * +0.404 * +0.892 * +0.115 *
-0.172 * SGAI+4.679 * TATA-0.327 * LVGI
-0.172 * +4.679 * -0.327 *
=

* 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 $0.95 Mil.
Revenue was 2.04 + 0 + 0 + 0 = $2.04 Mil.
Gross Profit was 1.288 + 0 + 0 + 0 = $1.29 Mil.
Total Current Assets was $276.90 Mil.
Total Assets was $329.79 Mil.
Property, Plant and Equipment(Net PPE) was $48.09 Mil.
Depreciation, Depletion and Amortization(DDA) was $8.31 Mil.
Selling, General, & Admin. Expense(SGA) was $38.40 Mil.
Total Current Liabilities was $22.82 Mil.
Long-Term Debt & Capital Lease Obligation was $7.98 Mil.
Net Income was -34.545 + -30.186 + -19.897 + -15.557 = $-100.19 Mil.
Non Operating Income was -8.869 + 0.504 + 0.831 + 1.749 = $-5.79 Mil.
Cash Flow from Operations was -12.292 + -22.723 + -22.092 + -8.979 = $-66.09 Mil.
Total Receivables was $3.91 Mil.
Revenue was 0 + 0 + 0 + 0 = $0.00 Mil.
Gross Profit was 0 + 0 + 0 + 0 = $0.00 Mil.
Total Current Assets was $348.63 Mil.
Total Assets was $406.81 Mil.
Property, Plant and Equipment(Net PPE) was $51.06 Mil.
Depreciation, Depletion and Amortization(DDA) was $5.54 Mil.
Selling, General, & Admin. Expense(SGA) was $47.48 Mil.
Total Current Liabilities was $20.36 Mil.
Long-Term Debt & Capital Lease Obligation was $11.32 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)
=(0.95 / 2.04) / (3.911 / 0)
=0.465686 /
=

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 / 0) / (1.288 / 2.04)
= / 0.631373
=

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 - (276.904 + 48.092) / 329.785) / (1 - (348.627 + 51.058) / 406.81)
=0.014522 / 0.017514
=

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
=2.04 / 0
=

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))
=(5.541 / (5.541 + 51.058)) / (8.308 / (8.308 + 48.092))
=0.097899 / 0.147305
=

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)
=(38.395 / 2.04) / (47.483 / 0)
=18.821078 /
=

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)
=((7.977 + 22.815) / 329.785) / ((11.316 + 20.355) / 406.81)
=0.09337 / 0.077852
=

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
=(-100.185 - -5.785 - -66.086) / 329.785
=-0.085856

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.


SES AI Business Description

Traded in Other Exchanges
N/A
Address
35 Cabot Road, Woburn, MA, USA, 01801
SES AI Corp is a pre-commercialization stage company engaged in the development and initial production of high-performance Lithium-Metal (Li-Metal) rechargeable battery technologies for electric vehicles (EVs), urban air mobility (UAM), which encompasses electric vehicle take-off and landing (eVTOL), and other applications. The company is an integrated Li-Metal battery manufacturer with capabilities in material, cell, module, AI-powered safety algorithms, and recycling.
Executives
Gang Li officer: Chief Manufacturing Officer 35 CABOT ROAD, WOBURN MA 01801
Kyle Pilkington officer: Chief Legal Officer 35 CABOT ROAD, WOBURN MA 01801
Jing Nealis officer: Chief Financial Officer 1, ROBINSON ROAD, #18-00 AIA TOWER, SINGAPORE U0 048542
Qichao Hu director, 10 percent owner, officer: CEO & Chairman 1, ROBINSON ROAD, #18-00 AIA TOWER, SINGAPORE U0 048542
Hong Gan officer: Chief Science Officer 1, ROBINSON ROAD, #18-00 AIA TOWER, SINGAPORE U0 048542
Sk Inc. 10 percent owner 26, JONG-RO, JONGNO-GU, SEOUL M5 03188
General Motors Holdings Llc 10 percent owner 300 RENAISSANCE CENTER, MC 482-C24-A68, DETROIT MI 48265
Temasek Holdings (private) Ltd 10 percent owner 60B ORCHARD ROAD #06-18 TOWER 2, THE ATRIUM@ORCHARD, SINGAPORE U0 238891
Rohit Makharia officer: Pres. & Chief Op. Officer 1, ROBINSON ROAD, #18-00 AIA TOWER, SINGAPORE U0 048542
Anirvan Coomer director 35 CABOT ROAD, WOBURN MA 01801
Yongkyu Son officer: Chief Technology Officer 1, ROBINSON ROAD, #18-00 AIA TOWER, SINGAPORE U0 048542
Tianqi Lithium Hk Co., Ltd. 10 percent owner NO. 10 EAST GAOPENG ROAD, CHENGDU, SICHUAN F4 610041
Joanne Ban officer: Chief Legal & Corp. Officer 1, ROBINSON ROAD, #18-00 AIA TOWER, SINGAPORE U0 048542
Robert M Friedland director 150 BEACH ROAD #25-03, THE GATEWAY WEST, SINGAPORE U0 189720
General Motors Financial Company, Inc. 10 percent owner 801 CHERRY ST, SUITE 3500, FORT WORTH TX 76102