# kaal:claim:3409548-008

**Claim.** In the Numerai model, using artificial intelligence to synthesize competing data scientist models into a meta model raises efficiency and improves capital allocation by reducing overhead costs.

**Type.** mechanism  **Support.** argued

**Holds when.**

- crowdsourced data science model with a synthesized meta model

**Source quote.**

> In the Numerai model, the use of artificial intelligence increases efficiency and optimum capital allocation by reducing overhead costs.

**From.** Kaal, *Financial Technology and Hedge Funds* (2019), II.2 Artificial Intelligence and Big Data, page 12

**Cite as.** Kaal, Financial Technology and Hedge Funds (2019). SSRN: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3409548

**Verify.** sha256 of source PDF `74227ab2656b06bfe4a29c942fc2ba26df9f476917e0a9f85ec038b8c3402c40` at https://raw.githubusercontent.com/wulfkaal/Academic-Papers/main/papers/pdf/Kaal%20-%202019%20-%20Financial%20Technology%20and%20Hedge%20Funds.pdf

**Topics.** ai-and-agents, economics

**Keywords.** numerai, artificial-intelligence, meta-model, capital-allocation, efficiency

**Related claims.**

- extends: https://wulfkaal.github.io/claims/2959730-025
- extends: https://wulfkaal.github.io/claims/3002908-038

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