Paper Number

ECIS2026-1993

Paper Type

SP

Abstract

Financial processes must be managed in alignment with governance, risk, and compliance (GRC) requirements and audited in accordance with reporting guidelines and standards. Financial process mining addresses these requirements by reconstructing and analysing journal entries due to domain-specific quantitative and qualitative aspects. Event log data derived from enterprise resource planning (ERP) systems are underspecified and, consequently, do not necessarily reflect financial business processes accurately. To address this challenge, the paper proposes the idea of using a fine-tuned large language model (LLM) to interpret and classify journal entries. This fine-tuned LLM is intended to augment a rule-based algorithm, enabling the accurate specification of financial process activities based on posted journal entries. The paper outlines the planned methodological approach for the research and initial work items that have been developed.

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Jun 14th, 12:00 AM

Financial Process Mining In The Age Of Large Language Models

Financial processes must be managed in alignment with governance, risk, and compliance (GRC) requirements and audited in accordance with reporting guidelines and standards. Financial process mining addresses these requirements by reconstructing and analysing journal entries due to domain-specific quantitative and qualitative aspects. Event log data derived from enterprise resource planning (ERP) systems are underspecified and, consequently, do not necessarily reflect financial business processes accurately. To address this challenge, the paper proposes the idea of using a fine-tuned large language model (LLM) to interpret and classify journal entries. This fine-tuned LLM is intended to augment a rule-based algorithm, enabling the accurate specification of financial process activities based on posted journal entries. The paper outlines the planned methodological approach for the research and initial work items that have been developed.

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