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New framework boosts LLM auditability in enterprise finance

A new framework called the Knowledge-Driven Analytics Framework (KDAF) has been proposed for enhancing the trustworthiness of Large Language Models (LLMs) in enterprise finance. This framework focuses on auditability and traceability of information, which are critical for regulated financial workflows. Evaluations show that while KDAF does not significantly outperform traditional methods like BM25 in terms of answer accuracy, it excels in citation traceability and provides complete provenance chains for retrieved facts. AI

IMPACT Enhances trust and auditability for LLMs in regulated financial sectors, potentially accelerating enterprise adoption.

RANK_REASON The cluster contains an academic paper detailing a new framework for LLM analytics.

Read on arXiv cs.IR (Information Retrieval) →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

New framework boosts LLM auditability in enterprise finance

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The cluster contains an academic paper detailing a new framework for LLM analytics.
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COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · Sergiy Lunyakin ·

    Auditable by Construction: An Ontology-Driven Framework for Trustworthy LLM Analytics in Enterprise Finance

    arXiv:2608.20661v1 Announce Type: new Abstract: Enterprise adoption of large language models in finance is constrained less by fluency than by trust: in Financial Planning and Analysis (FP&amp;A) and other regulated workflows, an answer is usable only if it is traceable to author…

  2. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Sergiy Lunyakin ·

    Auditable by Construction: An Ontology-Driven Framework for Trustworthy LLM Analytics in Enterprise Finance

    Enterprise adoption of large language models in finance is constrained less by fluency than by trust: in Financial Planning and Analysis (FP&A) and other regulated workflows, an answer is usable only if it is traceable to authoritative sources and auditable after the fact. This p…