Risk / Financial AI / Investment Banking

Author
Umran Nayani
Source
SSRN 5963734
Original publication
29 December 2025
First-party page release
23 September 2026
Full paper release
28 September 2026

The Cognitive Primitives of Investment Banking: An Ontology for AI-Driven Augmentation in High-Stakes Finance

A conceptual ontology for distinguishing the cognitive work performed across high-stakes investment-banking tasks before applying AI augmentation.

01 / Method

What the research does

The paper derives four classes of cognitive primitives and associated truth conditions from public and theoretical sources.

02 / Limitations

What the evidence does not establish

The work defines an ontology rather than reporting a benchmark, production deployment, institutional adoption or autonomous decision system.

03 / Institutional relevance

Why the research matters

Helps institutions identify which parts of financial work can be bounded, tested and augmented without collapsing materially different reasoning tasks into one model prompt.

04 / Full Paper

Read the complete paper

The complete first-party paper is available here without leaving the publication page. The reader loads only when requested.

Full paper readerChoose “Read Full Paper” to load the PDF on this page.

© Little Black Journal LLP / Umran Nayani. All rights reserved. This paper is made available for reading and personal reference. No additional reuse licence is granted unless expressly stated.

05 / Citation & Provenance

Source record

Suggested citation
Umran Nayani. (2025). The Cognitive Primitives of Investment Banking: An Ontology for AI-Driven Augmentation in High-Stakes Finance. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.5963734
SSRN record
SSRN 5963734
Publication status
Working paper published on SSRN. It is not described here as peer reviewed.
First-party provenance
Prepared from the verified public source record and the company’s bounded research archive. A first-party copy of the full paper is preserved on this site, with the SSRN record retained as independent publication provenance.
Rights
© Little Black Journal LLP / Umran Nayani. All rights reserved. This paper is made available for reading and personal reference. No additional reuse licence is granted unless expressly stated.

07 / Application

From research to institutional work

The paper is evidence of completed research, not a claim that every method has been deployed in every environment. Explore the relevant capability routes for current scope and commercial boundaries.

AI Systems & Build Labs Research & Institutional Work

Research enquiry / Cognitive Primitives of Investment Banking

Apply the research to a consequential question.

The enquiry subject identifies this paper without introducing analytics, hidden fields or visitor tracking.

Start a research enquiry