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Forbes
21-07-2025
- Business
- Forbes
What Is ASC 820, Why Is It Important For Positive Investor Relations?
Tomas Milar is the Founder and CEO of Eqvista, an equity management platform. Financial and operational strategy optimization often overshadows the importance of maintaining positive investor relations in tiding over market turbulence. For example, the U.S. technology sector took a hit this spring against the backdrop of the trade wars triggered by announced tariff hikes. This was reflected in the Nasdaq-100 Technology Sector index, whose six-month returns were -11.84% as of April 23. In contrast, Zscaler, the company that was presented the 2024 IR Magazine Best overall investor relations (large cap) award, saw a 10.82% rise in the same period. A key obstacle in maintaining positive investor relations is strengthening investor confidence in reported asset valuations, especially when your company has a large amount of intangible assets. Complete and structured transparency, like that obtained by complying with ASC 820, is often the best solution to alleviate such concerns. This article will explore the significance of ASC 820 and how you can comply with this accounting standard. ASC 820's Significance ASC 820, also known as the Fair Value Measurement standard, is an accounting standard that guides companies in measuring and reporting their investments in a GAAP-compliant manner. For instance, in an acquisition, ASC 805 requires the acquirer to recognize the acquired party's assets, liabilities and non-controlling interests at fair value. Under other ASC accounting standards, fair value assessments are required for intangible assets and financial assets in periodic financial reporting and reports made by investment companies to their investors. This enhances consistency and comparability in financial reporting as a result and enables investors to understand the value of assets owned by their companies. Since ASC 820 also includes disclosure requirements, it not only requires fair value reporting but also explanations regarding valuation processes and assumptions. Such reporting enables investors to perform informed analyses and better anticipate events that could impact the value of company assets. How To Comply With ASC 820 To comply with ASC 820, you must calculate an asset's fair value as the price at which two knowledgeable principal market participants would willingly exchange it on the measurement date. If a principal market does not exist, the market that would provide the best selling price should be considered. Another condition for ASC 820 compliance is explaining your valuation methodology to help the intended reader interpret the fair values reported. While this accounting standard requires you to consider prices in principal markets, not all assets have active markets. Therefore, we must categorize assets as level 1, level 2 and level 3 depending on the difficulty in ascertaining fair values and then choose appropriate valuation methodologies. Level 1 assets have active markets and hence have quoted prices. Publicly traded stocks, commodity derivatives, government securities and exchange-traded funds (ETFs) are some examples of level 1 assets. Assets that lack active markets and quoted prices but whose value can be calculated using observable inputs are called level 2 assets. For instance, a derivative of a level 1 asset would qualify as a level 2 asset. Such a derivative does not have an active market, but its value can be calculated based on the level 1 asset's value. Trademarks and other intellectual properties, private equity and various other assets whose value must be determined using unobservable inputs are called level 3 assets. These levels are informally referred to as liquidity hierarchy levels since the asset liquidity reduces with increasing levels. However, fair value hierarchy is the official term for this classification method. The fair value of level 1 assets must be the quoted prices on the measurement date. For level 2 assets, the fair value must be calculated based on the input values reported on the measurement date. Finally, level 3 asset fair values must be calculated based on estimations and assumptions based on the latest available data on the measurement date. Under ASC 820, the following valuation approaches are prescribed for level 2 and level 3 asset fair value reporting. Certain assets that can generate positive cash flows can be valued using the income-based valuation approach. This involves estimating all future cash flows expected from an asset and then discounting them to arrive at their present value. Businesses that are nearing liquidation are often valued using the asset-based valuation approach, wherein we simply calculate the business' net worth as total assets minus total liabilities. In this valuation approach, we arrive at the value of an asset by referencing the published fair value assessments and selling prices of similar assets. One of the methodologies that comes under this approach involves establishing a market valuation multiple by dividing the total value of similar assets by an observable and relevant metric. As this method relies directly on market data, it aligns most closely with the requirements of ASC 820. ASC 820 Disclosure Requirements To allow investors to validate fair values and anticipate any fluctuations, ASC 820 requires you to disclose the following details. Knowing the liquidity hierarchy level helps investors judge whether the correct valuation methodology has been used. You must explain the valuation methodology used and the reasoning behind your choices. This is especially important in the case of level 3 assets, where you would often customize asset valuation methodologies to make accurate fair value assessments. Any observable inputs and assumptions used in the fair value assessment must be provided to investors so they can independently validate the fair values. Since unobservable inputs must be assumed or estimated in level 3 asset fair value assessments, you must provide a sensitivity analysis to illustrate how variations or inaccuracies in these assumptions could impact the resulting fair values. Compliance Simplified One can interpret the intention behind ASC 820 as aiding prudent investment decision making by increasing consistency, transparency and comparability in financial reporting. If your business can abide by the spirit of the standard, it can maintain accounting compliance and positive investor relations. The information provided here is not investment, legal, tax or financial advice. You should consult with a licensed professional for advice concerning your specific situation. Forbes Finance Council is an invitation-only organization for executives in successful accounting, financial planning and wealth management firms. Do I qualify?
Forbes
09-04-2025
- Business
- Forbes
The AI Valuation Paradox: Balancing Hype With Real-World Impact
Tomas Milar is the Founder and CEO of Eqvista, an equity management platform. For the past year, soaring artificial intelligence (AI) startup valuations have been justified by rapid revenue growth, driven by various industries recognizing AI's potential to reshape operations and enhance productivity. A prime example is OpenAI's valuation, which grew more than tenfold in just three years, from $14 billion in 2021 to $157 billion in 2024, fueled by ChatGPT's success and its impressive projected earnings. The market's confidence in AI is evident in the lofty average revenue multiple of 23.4x commanded by AI startups. However, we may soon witness a decline in the high funding levels AI startups currently attract, driven by the rise of low-cost, asset-light alternatives. While this in itself is a strong reason for AI startup valuations to deflate, I believe the exaggeration of current AI capabilities leaves room for further corrections. Recently, we have seen AI startups secure valuations that were thousands of times their annual revenues. For example, xAI and Infinite Reality were valued at $40 billion and $12.25 billion, respectively. Even considering the growth potential of AI startups, such valuation multiples are excessive. Such outliers can skew data that most AI companies can achieve such heights when the reality is that many more AI startups tend to close their doors before achieving such market success. AI startups have distinguished themselves from their predecessors with an unprecedented ability to generate revenue. According to Stripe (paywall), today's leading AI startups that have reached an annualized revenue of $30 million have done so five times faster than past SaaS companies. At the same time, we must acknowledge that AI startups are much more capital-hungry than other tech startups. OpenAI faces significant operational costs from its flagship product, ChatGPT, spending approximately $700,000 daily (paywall)—over $255 million annually. While these operational costs are offset comfortably by its $3.6 billion annualized revenue (paywall), OpenAI faces intense competition from tech giants such as Google as well as emerging players such as Anthropic. To maintain its competitive edge, OpenAI must spend an additional $5 billion annually to train new models. This is an expense that will likely continue until OpenAI establishes itself as the undisputed market leader. To put things into perspective, OpenAI's total funds raised stand at $21.9 billion (registration required). However, recent advancements by new entrants and the limitations of existing AI models cast doubt on both the funding needs and valuations of AI startups. DeepSeek, the Chinese AI startup, has disrupted the U.S. AI startup ecosystem by demonstrating that premier AI models could be built without exorbitant capital expenditure. Although various experts are disputing this, the company claims that the total training cost was $5.6 million for DeepSeek-R1, the model that delivers performance comparable to OpenAI's ChatGPT. When we compare the training costs for the two startups, we can see that OpenAI could train new models for less than half a day with DeepSeek's entire budget. We are already seeing the AI leaders being challenged. After the release of DeepSeek-R1, between January 23 and 25, ChatGPT lost 41.3 million views. Thus, some investors are questioning if high-performing AI models really cost as much as advertised. The reasons to believe that AI startups are overvalued are plentiful. Firstly, we haven't yet achieved true artificial general intelligence (AGI), which by definition is capable of performing any intellectual task a human can. What we have right now is a very narrow version of AI that can reliably carry out certain tasks, such as natural language processing or image recognition, but has limited application elsewhere. Secondly, AI's commercial viability remains questionable. A Boston Consulting Group (BCG) report analyzing 1,000 companies that adopted AI found that only 4% generated substantial value, while only 22% had progressed beyond the proof-of-concept stage to generate any value at all. Notably, the companies that stood out were already well-positioned for success due to strong nonfinancial factors, such as patents filed and employee satisfaction. Thirdly, various studies note that the capabilities of AI in tasks such as logical reasoning, chemical compound discovery and code writing have been exaggerated. Thus, only a few AI startups that achieve significant breakthroughs, such as closing the gap between advertised and actual capabilities and enhancing commercial viability, are likely to survive and justify their valuations, while the majority perish. While some AI startups' values are astronomical multiples of their annual revenues, these cases represent a small group of outliers. Once we exclude the outliers, we can observe reasonable valuation multiples across all stages. However, a widely recognized cause for concern for AI startups is their struggle to achieve profitability due to their asset-heavy nature and the high costs associated with operations and training. Additionally, AI's real-world impact remains limited, with narrow applications, questionable commercial viability and sometimes-exaggerated capabilities. As low-cost alternatives emerge, investors are increasingly scrutinizing whether U.S. AI startups can maintain their competitive edge. The information provided here is not investment, tax or financial advice. You should consult with a licensed professional for advice concerning your specific situation. Forbes Finance Council is an invitation-only organization for executives in successful accounting, financial planning and wealth management firms. Do I qualify?
