Retrieval Augmented Generation (RAG) for Fintech: Agentic Design and Evaluation

Cook, Thomas; Osuagwu, Richard; Tsatiashvili, Liman; Vrynsia, Vrynsia; Ghosal, Koustav; Masoud, Maraim; Mattivi, Riccardo

Retrieval Augmented Generation (RAG) for Fintech: Agentic Design and Evaluation

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Cook, Thomas, Osuagwu, Richard, Tsatiashvili, Liman, Vrynsia, Vrynsia, Ghosal, Koustav, Masoud, Maraim and Mattivi, Riccardo (2025) Retrieval Augmented Generation (RAG) for Fintech: Agentic Design and Evaluation. In: 2025 3rd International Conference on Foundation and Large Language Models (FLLM). IEEE, Vienna, Austria, pp. 93-100. ISBN 979-833159409-1

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Official URL: https://doi.org/10.1109/FLLM67465.2025.11391155

Abstract

Retrieval-Augmented Generation (RAG) systems often face limitations in specialized domains such as fintech, where domain-specific ontologies, dense terminology, and acronyms complicate effective retrieval and synthesis. This paper introduces an agentic RAG architecture designed to address these challenges through a modular pipeline of specialised agents. The proposed system supports intelligent query reformulation, iterative sub-query decomposition guided by keyphrase extraction, contextual acronym resolution, and cross-encoder-based context re-ranking. We evaluate our approach against a standard RAG baseline using a curated dataset of 85 question-answer-reference triples derived from an enterprise fintech knowledge base. Experimental results demonstrate that the agentic RAG system outperforms the baseline in retrieval precision and relevance, albeit with increased latency. These findings suggest that structured, multi-agent methodologies offer a promising direction for enhancing retrieval robustness in complex, domain-specific settings.

Item Type:	Book Section
Uncontrolled Keywords:	Agentic AI; Domain-Specific Ontology; Fintech; Knowledge Base; Natural Language Processing; Query Understanding; Retrieval Augmented Generation
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science P Language and Literature > P Philology. Linguistics > Computational linguistics. Natural language processing H Social Sciences > HG Finance > Fintech T Technology > T Technology (General) > Information Technology > Fintech
Divisions:	School of Computing
Depositing User:	Tamara Malone
Date Deposited:	28 Apr 2026 15:55
Last Modified:	28 Apr 2026 15:55
URI:	https://norma.ncirl.ie/id/eprint/9294

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