Month: June 2025
New Tax Cut & Spending Bill, Protecting Law Enforcement, VA Benefits and Semiconductor Supply Chains
Quantum Computing: Separating Hype from Real-World Business Value
How to Navigate Money Before Saying ‘I Do’
Responsibilities of Being the Executor of a Will
Understanding the Goodwill to Assets Ratio
The goodwill to assets ratio measures how much of a company’s total assets come from goodwill – an intangible asset like brand value or customer loyalty – and it plays a role in assessing the company’s overall value. It provides a ratio or percentage of the amount of intangible versus tangible assets. Understanding what the ratio represents, how it is calculated, and how to interpret it is essential for effectively applying it to business operations and investment decisions.
Goodwill Defined
Goodwill can be defined as an intangible asset that comes about when the acquiring firm obtains such assets from the acquired firm at a higher value. When it comes to accounting standards, both International Financial Reporting Standards (IFRS) and Generally Accepted Accounting Principles (GAAP), intangible assets must be evaluated for impairment, but don’t need to be amortized. Based upon IFRS 38, goodwill is generated solely during an acquisition and is defined as the amount of the acquisition price for the acquired company over its book value. IFRS 38 does not recognize goodwill generated by the company internally.
Calculating Goodwill
Goodwill = Liabilities – Assets + Purchase Price
If a company looks at acquiring another company for $750,000, and the company being acquired has assets of $900,000 and liabilities of $450,000, the net assets would be $450,000. Based on the goodwill formula:
Goodwill = $450,000 – $900,000 + $750,000 = $300,000
Once the goodwill has been established, the Goodwill to Assets Ratio Formula is used as follows:
Goodwill to Assets Ratio = Unamortized Goodwill / Total Assets
If one company is putting itself up for sale with a selling price of $75 million, it would have to establish its book value, based on recent financial statements, along with its goodwill value. Factors that go into calculating a company’s goodwill include if the company has prime real estate, a well-known brand, a rich list of clients, or intellectual property that sets itself apart from competitors in the industry that won’t expire for years. For example, if its intangible assets are $15 million, subtracted from its selling price of $75 million, its tangible assets or book value would be $60 million.
Based on the ratio, it’s calculated as follows:
$15 million / $75 million = 20 percent
Therefore, the ratio is 20 percent for the company’s goodwill as part of the company’s valuation. Otherwise, if the purchase goes through, whoever buys the company spends 20 percent on the company’s goodwill.
Analyzing the Goodwill to Assets Ratio
This ratio gives an overview of a business’s financial health. The lower the ratio, the more tangible or physical assets that can be sold. Conversely, the higher the ratio, the fewer intangibles a company has. Much like assets that can be written down, so can a company’s goodwill.
This ratio is not one-in-all and should be measured against businesses within the same industry. Based on this analysis, if a company has a large amount of goodwill on its financial statements, if it’s written down, it could still result in a lower valuation despite the company having a large amount of assets.
Looking over time, it shows the importance of ongoing evaluations. In 1975, according to the University of California, Los Angeles, companies on the Standard and Poor’s 500 (S&P 500) had $122 billion of intangible assets and $594 billion of tangible assets, or about a 21 percent intangible to tangible assets ratio. These companies included most industrial and energy sector names like GE, Procter & Gamble, 3M, Exxon Mobil, along with IBM, based on market capitalization. However, in 2018, the ratio increased to 84 percent of intangible to tangible assets. Intangible assets accounted for $21.03 trillion and $4 trillion when looking at most of the companies on the S&P 500, which included Apple, Alphabet, Microsoft, Amazon, and Facebook, based on market capitalization.
While the growth of technology and communication services has risen and skewed the tangible to intangible ratio, it shows the importance of evaluating companies and sectors individually, not just with a broad brush.
Sources
Boom of Intangible Assets Felt Across Industries and Economy
Why AI Falls Short for U.S. Tax Guidance
The rise of artificial intelligence tools like ChatGPT and Grok has transformed how Americans seek information. From meal planning to complex financial questions, these platforms offer instant answers to virtually any query. But when it comes to U.S. tax advice – especially international tax matters – relying on AI can lead to serious and costly mistakes.
The Allure and Limitations of AI Tax Help
The appeal of AI for tax questions is understandable. However, AI’s limitations become glaringly apparent in international tax matters. This specialized field combines extraordinary complexity with constant change, creating a perfect storm that exposes AI’s weaknesses. The landscape shifts regularly through regulatory updates, IRS interpretations, and court decisions – changes that AI systems struggle to incorporate in real-time.
Consider the IRS Practice Units, internal training materials for tax examiners that became public in 2020. From January through early May 2025 alone, the IRS released 35 new Practice Units, with 22 addressing intricate international tax topics such as foreign tax credit computations, base erosion anti-abuse tax, and treaty provisions. These rapidly evolving resources represent just one stream of constantly changing tax guidance that AI models could fail to capture, leading to outdated or incomplete advice.
How AI Gets Tax Advice Wrong
AI’s accuracy problems stem from its fundamental design. Large language models like those powering ChatGPT and Grok train on vast amounts of text from diverse sources – online forums, books, articles, websites, and public records. This training produces responses that sound authoritative and conversational, but this polish masks significant limitations.
The core issue is what experts call “simplexity” – AI’s tendency to oversimplify complex tax law. When AI presents intricate regulations as straightforward concepts, it fundamentally misrepresents the law itself. This problem has already surfaced with the IRS’s own Interactive Tax Assistant chatbot.
AI systems also suffer from interpretation errors, reliance on outdated information, and conflation of similar but distinct tax concepts. For instance, an AI might confuse the Foreign Tax Credit with the Foreign Earned Income Exclusion – similar-sounding but entirely different provisions with vastly different implications.
The Real-World Cost of AI Errors
Mistakes in international tax compliance carry severe consequences. The IRS considers international tax enforcement a top priority, and errors in reporting foreign income or assets trigger substantial penalties. A late FBAR or foreign information return like Form 8938 or 5471 carries a $10,000 penalty. Errors involving foreign assets can result in a 40 percent accuracy-related penalty on unpaid taxes.
Importantly, relying on AI advice won’t qualify as “reasonable cause” to avoid these penalties. Last year, the U.S. Taxpayer Advocate Service highlighted a Washington Post analysis showing that AI chatbots from major tax preparation companies provided incorrect advice up to 50 percent of the time on complex questions. Beyond financial penalties, taxpayers face the stress of audits and the time-consuming burden of correcting mistakes.
Why Human Expertise Remains Essential
While AI continues to advance, it currently falls far short of replacing human expertise in international tax matters. Experienced tax professionals bring irreplaceable skills that algorithms cannot match. They stay current on evolving IRS guidance, monitor treaty updates, and analyze new case law. Most importantly, they apply professional judgment to each unique situation.
International tax planning rarely follows a one-size-fits-all approach. Professionals provide strategic thinking and contextual analysis that optimize outcomes for specific circumstances. They understand when exceptions apply, how different rules interact, and what documentation requirements must be met. These nuanced judgments remain beyond AI’s current capabilities.
Conclusion
This doesn’t mean AI has no role in tax planning. It can serve as a useful starting point for understanding basic concepts or generating initial questions to discuss with a professional. However, treating AI as a substitute for qualified tax advice is a risky gamble.
The appeal of instant, free tax guidance is strong, but the cost of getting it wrong can be devastating. Until AI can match the precision, current knowledge, and professional judgment of experienced tax professionals, taxpayers would be wise to view it as a supplement to – not a replacement for – human expertise.