# Fraud

`kaal:entity:fraud`

**Status.** derived

This node is assembled mechanically from the 10 claims that carry the concept tag `fraud`. It is a roster of what the corpus says under this term. It is **not** an adjudicated definition: no single statement here has been ruled canonical, and no first-appearance call has been made. Read the claims and judge for yourself.

## Every claim under this term

10 claims across 10 works, 2016 to 2025.

**2016**

- [2811718-019](https://wulfkaal.github.io/claims/2811718-019) [condition/evidenced] -- Relying solely on a representation by the investment or the fund, without actually performing due diligence, is sufficient to present a fact issue on fraud to a jury.
  > Relying solely on an investment or fund representation and not actually performing due diligence is sufficient to present an issue of fact to a jury for fraud.
  Wulf A. Kaal, Private Fund Investor Due Diligence – Evidence from 1995 to 2015 (2016). SSRN: https://ssrn.com/abstract=2811718

**2017**

- [3002908-012](https://wulfkaal.github.io/claims/3002908-012) [empirical/evidenced] -- The SEC rejected the Winklevoss Bitcoin ETF application on the ground that the unregulated nature of Bitcoin made the proposed fund susceptible to fraud.
  > In rejecting the application, the SEC reasoned that, because of the unregulated nature of Bitcoin, the proposed fund was susceptible to fraud.
  Wulf A. Kaal, Marco Dell'Erba, Blockchain Innovation in Private Investment Funds - A Comparative Analysis of the United States and (2017). SSRN: https://ssrn.com/abstract=3002908

**2018**

- [3117224-033](https://wulfkaal.github.io/claims/3117224-033) [empirical/evidenced] -- The People's Republic of China has banned ICOs entirely, including the offering of coins and the exchanges used to trade them, on the view that ICOs hurt the market through potential deception and fraud.
  > The People Republic of China have taken a firm stance against ICO's, banning them entirely.
  Wulf A. Kaal, Initial Coin Offerings The Top 25 Jurisdictions and Their Comparative Regulatory Responses (2018). SSRN: https://ssrn.com/abstract=3117224

**2021**

- [3808873-006](https://wulfkaal.github.io/claims/3808873-006) [mechanism/argued] *(failure mode)* -- The profit driven influx into the digital asset space brought rampant fraud that created a chasm between the decentralized asset space and mainstream investors, and lacking regulatory certainty and recognition of cryptocurrencies exacerbated that divide.
  > With it came fraud in the digital asset space which was rampant and created a chasm between the decentralized assets space and mainstream investors.
  Wulf A. Kaal, Decentralization Neutralizers (2021). SSRN: https://ssrn.com/abstract=3808873
- [3949098-021](https://wulfkaal.github.io/claims/3949098-021) [failure/argued] *(failure mode)* -- Traditional underwriting also fails at the agent level, because individual agents within an underwriter may sacrifice the underwriter's overall reputation for personal gain, for example by putting out a fraudulent offering.
  > individual agents within an underwriter may decide to sacrifice the underwriter's overall reputation for personal gain.
  Wulf A. Kaal, Reputation as Capital – How DAOs Upgrade Finance (2021). SSRN: https://ssrn.com/abstract=3949098

**2022**

- [4067783-003](https://wulfkaal.github.io/claims/4067783-003) [empirical/evidenced] *(failure mode)* -- Rug pulls grew sharply as a share of crypto crime: of the $7.7 billion in total illicit crypto revenue in 2021, 37 percent came from rug pulls, up from 1 percent of illicit revenue in 2020.
  > In 2021 alone, the total illicit revenue from crypto scams was $7.7 billion; 37% of that total resulted from "rug pulls," an increase from the 1% of total illicit revenue in 2020.
  Wulf A. Kaal, DAO Fallacies (2022). SSRN: https://ssrn.com/abstract=4067783

**2024**

- [4685567-012](https://wulfkaal.github.io/claims/4685567-012) [failure/argued] *(failure mode)* -- Kaal concedes that at their worst Impact 1.0 carbon credits are non transparent, fraudulent and fail to mitigate climate change, but contests the inference drawn from that record: operational shortcomings do not necessarily invalidate the underlying theory.
  > at their worst, carbon credits in Impact 1.0 are non-transparent, fraudulent and fail to mitigate climate change. Nonetheless, operational shortcomings do not necessarily invalidate the underlying theory
  Wulf A. Kaal, Impact Investing Innovation - From Impact 1.0 to 3.0 (2024). SSRN: https://ssrn.com/abstract=4685567
- [4900878-020](https://wulfkaal.github.io/claims/4900878-020) [failure/argued] *(failure mode)* -- The 2017 ICO wave democratized access to investment and spurred blockchain innovation, but the absence of regulatory oversight produced numerous fraudulent projects, which exposed the need for robust economic models and regulatory frameworks inside token ecosystems.
  > However, the lack of regulatory oversight also led to numerous fraudulent projects
  Wulf A. Kaal, Quantum Economy and Tokenomics (2024). SSRN: https://ssrn.com/abstract=4900878

**2025**

- [5095633-008](https://wulfkaal.github.io/claims/5095633-008) [condition/argued] *(failure mode)* -- Decentralized data production will succeed only if it solves fraudulent submissions, content moderation, and alignment with ethical and legal frameworks; these are necessary conditions, not incidental risks.
  > their success critically depends on addressing challenges such as fraudulent submissions, content moderation, and ensuring alignment with ethical and legal frameworks.
  Wulf A. Kaal, Artificial Intelligence The Final Frontier (2025). SSRN: https://ssrn.com/abstract=5095633
- [5245185-021](https://wulfkaal.github.io/claims/5245185-021) [condition/argued] *(failure mode)* -- Without feedback loops that continuously ingest data on AI behavior, regulatory efforts cannot efficiently address fraud or consumer harm as AI ubiquity amplifies those risks across decentralized networks.
  > Without feedback loops, regulatory efforts cannot efficiently address fraud or consumer harm as AI ubiquity amplifies these risks across decentralized networks.
  Wulf A. Kaal, How can we Best Monitor AI Agents (2025). SSRN: https://ssrn.com/abstract=5245185

## Verify

Every claim above resolves to a record carrying a verbatim source quote, the sha256 of the source PDF, and a preformatted citation. Nothing here asks to be taken on trust.

    curl -s https://wulfkaal.github.io/entities/fraud.md | sha256sum

**Canonical form.** This markdown file is the canonical hashed representation of this entity node. Its sha256 is the content hash.