The Land of Startups is a Land of Pivots

We've graduated from the Peachscore+Dealum Accelerator, and in the midst of another pivot; having identified a beachhead industry for our data operations solution. The blog will be on hold for 1-2 months as we bring aboard marketing help. 

Converting intangibles to operating assets – Carbon Credits vs. Data

By David Huer | Aug 2025

Carbon Credits as a Universal Commodity: From Standards to Specifications, E*Comdty Research & Advisory, Capitalism, Freedom, and Carbon Credits, March 21, 2025 [Link]

Valuation Approaches:

The article argues that developers of process-driven innovations should not seek external standards verification--nor be compliant to those standards "in an effort to measure legitimacy". Instead, the author calls for adherence to "metrics (that are) tied to tangible, provable processes" that deliver repeatable, verifiable outputs.

Case:

The core challenge with carbon credits is their economic structure. A "carbon credit" is meant to function as an asset, yet its definition is blurry, its property rights weak, and its market adoption uneven. This makes it difficult for firms to treat credits as true operating assets, which in turn slows investment and undermines trust. 

The article argues that carbon credits valuation should evolve to process-based proof rather than external, shifting standards. Verification should rely on measurable, quantifiable outcomes (e.g., CO₂ captured, plastic recycled), transparently recorded through blockchain and digital ledgers. This enables tokenization—turning verified credits into standardized, fungible tokens for efficient trading across exchanges and OTC markets. Specifications emerge organically from market consensus, ensuring liquidity and transparency, unlike imposed standards that create inefficiencies. 

DreamWorks’ securitization of copyright license receivables in the intangible asset space is mirrored conceptually here: carbon credits become credible when process-based, digitized, and traded under market-defined specifications. A practical example is blockchain-enabled carbon removal verification, where X tons of CO₂ removed are transparently linked to Y tradable credits.

Implications for Financial and Strategic Reporting:

The suggested approach is that companies can adopt process-based verification to generate measurable, auditable outcomes. Tokenized carbon credits can be treated as standardized assets, enhancing balance sheet clarity, risk reporting, and capital allocation. For regulators, the role becomes that of referee—enforcing transparency and fraud prevention, but not dictating methodologies. This reframing aligns carbon credits with other commodities, integrating them into corporate reporting frameworks and investor-grade ESG disclosures.

Key Takeaways:

• Specifications driven by process-produced evidence enable liquidity and transparency.
• Blockchain and tokenization embed proof directly into carbon credits, making them self-verifying and universally tradable.
• Governments should enforce legal and fraud protections but avoid dictating methodologies.
• The transition to tokenized credits faces scaling challenges but offers an elegant solution for creating a universal, trusted carbon credit market.
• Ultimately, proof of process—not compliance to standards defined to refuse true innovation—will drive legitimacy and market adoption.

Valuing Corporate Intangibles

By David Huer | June 2025

(2023) Nicolas Crouzet, Yueran Ma, FINANCING AND VALUATION OF INTANGIBLE ASSETS, Nicolas Crouzet, Yueran Ma, Kellogg School of Management, Northwestern University, [Link] (Accessed Q2-2025). Expert Consultative Group on Valuation of Intangible Assets, GENEVA, OCTOBER 12, 2023

Summary

The paper discusses methods to value intangible assets; and opens by emphasizing the growing utility of intangible assets modern companies. These assets are increasingly vital but present major challenges for financing and valuation. 

Crouzet and Ma note the key distinction between separable intangibles (e.g., patents, software, brands) that can be sold or pledged independently, and nonseparable intangibles (e.g., know-how) that are deeply embedded in the firm and which is  typically financed through equity or enterprise-level debt. 

Structural bottlenecks limit financing use cases options for intangibles: unclear property rights, thin markets, and limited accounting transparency. For separable assets, valuation is hindered by the scarcity of secondary market transactions. The context of  the valuation is also to be considered: 

(1) Economists: "...define intangible assets as non-physical, firm-controlled resources resulting from past expenditures that are expected to yield future economic benefits ( proprietary knowledge, software, customer relationships, and internal databases. Crucially, this definition excludes financial assets and public goods like open-source software, as these do not stem from exclusive firm investment."

(2) Financial Accountants: "...require identifiability: assets must be separable or arise from contractual/legal rights to be recognized. As a result, only acquired intangibles are typically recorded on balance sheets, while internally developed assets are often omitted." 

The authors continue by delving into the role of uncertainty and discount rates in valuation.

The authors argue that in this age, it is prudent to capture "the true scope and value of firm-created intangible capital." One of the ways is to ensure the presence of "Robust institutional support—especially bankruptcy protections and accurate reporting—(which are) is essential for unlocking capital derived from intangible assets.  

This is challenging, so  income-derived valuation methods are often used. Methods are used on a case-by-case basis. Moreover, the authors "caution against inflating discount rates based on perceived risk; instead, systematic risks should influence discounting, while idiosyncratic risks, such as obsolescence or legal uncertainty, are better handled by adjusting cash flow projections. Income-derived methods include: With-and-without, Relief-from-royalty, Excess earnings, and Greenfield method. These are explained in the article.