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Crypto-assets are forcing the valuation profession to revisit some of its most fundamental assumptions.

The discussion presented by the CBV Institute on crypto valuation makes one point very clear: valuing crypto is not about inventing new theory, but about rigorously applying existing valuation principles to a new asset class.

Crypto-assets challenge traditional valuation in several ways:

• Limited or non-existent cash flows for many tokens
• High volatility and fragmented markets
• Rapid technological obsolescence and protocol risk
• Unclear boundaries between utility, governance, and speculative components

As a result, price is often mistaken for value. Market quotes may exist, but liquidity, market depth, reliability of exchanges, and regulatory risk must be assessed before concluding that an observed price represents an appropriate measure of value.

From a valuation perspective, the key questions remain unchanged:

• What rights does the token actually confer?
• What economic benefits, if any, can reasonably be expected?
• Who are the market participants, and under what assumptions are they transacting?
• Which standard of value is appropriate for the purpose — financial reporting, litigation, or transaction support?

Crypto valuation is not about hype or prediction. It is about discipline, skepticism, and clarity of purpose. As with any emerging asset class, the greatest risk is not uncertainty — it is overconfidence.

For practitioners interested in how valuation frameworks apply to crypto-assets, this is a conversation worth watching:
https://www.youtube.com/watch?v=5SYOcWQtP5U

Artificial intelligence is no longer a theoretical discussion in business valuation — it is already influencing how we work.

The recent discussion shared by the CBV Institute highlights an important shift:
AI is not about replacing professional judgment, but about reshaping how that judgment is exercised.

In valuation practice, AI is beginning to affect several core areas:

• Faster processing and normalization of large financial datasets
• Improved benchmarking and pattern recognition across transactions and markets
• More efficient scenario analysis and sensitivity testing
• Enhanced consistency in documentation and working papers

That said, valuation remains fundamentally a human discipline. Determining the appropriate standard of value, assessing reasonableness, interpreting risk, and exercising professional skepticism are not automatable decisions. They are responsibilities.

The real opportunity is not “AI versus valuators,” but AI as a force multiplier for rigorous professionals. Those who understand valuation theory, standards, and context will be best positioned to use these tools responsibly and effectively.

The profession has always evolved with better tools. AI is simply the next one — and it will reward discipline, not shortcuts.

For those interested in where the profession is heading, this is a discussion worth watching:
https://www.youtube.com/watch?v=5lSKwxcAeUg

In valuation and financial reporting, the word “value” is often used as if it meant the same thing in every context. It does not. Confusing these concepts can lead to flawed decisions, misaligned expectations, and, in some cases, litigation risk.

Fair Market Value (FMV) is a transaction-based concept. It reflects the price that would be agreed upon between a willing buyer and a willing seller, acting at arm’s length, with neither under compulsion and both having reasonable knowledge of relevant facts. FMV is commonly used in tax matters, shareholder disputes, and private transactions.

Fair Value, under IFRS (notably IFRS 13), is a financial reporting concept. It is an exit price—the price that would be received to sell an asset or paid to transfer a liability in an orderly transaction between market participants at the measurement date. It explicitly focuses on market participants, principal (or most advantageous) markets, and excludes entity-specific synergies.

Other value notions also matter, depending on purpose:

• Value in Use (IAS 36) reflects entity-specific cash flows and is relevant for impairment testing.
• Fair Value Less Costs of Disposal introduces a market-based lens adjusted for exit costs.
• Investment Value or Strategic Value incorporates buyer-specific synergies and is generally not appropriate for financial reporting.

The key takeaway is simple but often ignored:
Value is not a single number. It is a function of purpose, standard, and assumptions.

As professionals, our role is not just to calculate value, but to ensure the right definition of value is being applied to the right question. That distinction is where rigor — and credibility — truly begin.