AI4Contracts: LLM & RAG-Powered Encoding of Financial Derivative Contracts

Mridul, Maruf Ahmed; Sloyan, Ian; Gupta, Aparna; Seneviratne, Oshani

doi:10.24963/ijcai.2025/1034

AI4Contracts: LLM & RAG-Powered Encoding of Financial Derivative Contracts

Maruf Ahmed Mridul, Ian Sloyan, Aparna Gupta, Oshani Seneviratne

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Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence. AI4Tech: AI Enabling Technologies. Pages 9305-9312.

https://doi.org/10.24963/ijcai.2025/1034

Keywords

Advanced AI4Tech: Generative and LLMs-driven AI4Tech
Domain-specific AI4Tech: AI4Finance

Abstract

Large Language Models (LLMs) and Retrieval Augmented Generation (RAG) are reshaping how AI systems extract and organize information from unstructured text. A key challenge is designing AI methods that can incrementally extract, structure, and validate information while preserving hierarchical and contextual relationships. We introduce CDMizer, a template driven, LLM, and RAG-based framework for structured text transformation. By leveraging depth-based retrieval and hierarchical generation, CDMizer ensures a controlled, modular process that aligns generated outputs with predefined schemas. Its template-driven approach guarantees syntactic correctness, schema adherence, and improved scalability, addressing key limitations of direct generation methods. Additionally, we propose an LLM-powered evaluation framework to assess the completeness and accuracy of structured representations. Demonstrated in the transformation of Over-the-Counter (OTC) financial derivative contracts into the Common Domain Model (CDM), CDMizer establishes a scalable foundation for AI-driven document understanding, structured synthesis, and automated validation in broader contexts.

Maruf Ahmed Mridul, Ian Sloyan, Aparna Gupta, and Oshani Seneviratne. 2025. AI4Contracts: LLM & RAG-Powered Encoding of Financial Derivative Contracts. In Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-25. IJCAI, 9305–9312. https://doi.org/10.24963/ijcai.2025/1034

@inproceedings{ijcai2025p1034,
  title     = {AI4Contracts: LLM & RAG-Powered Encoding of Financial Derivative Contracts},
  author    = {Mridul, Maruf Ahmed and Sloyan, Ian and Gupta, Aparna and Seneviratne, Oshani},
  booktitle = {Proceedings of the Thirty-Fourth International Joint Conference on
               Artificial Intelligence, {IJCAI-25}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {James Kwok},
  pages     = {9305--9312},
  year      = {2025},
  month     = {8},
  note      = {AI4Tech: AI Enabling Technologies},
  doi       = {10.24963/ijcai.2025/1034},
  url       = {https://doi.org/10.24963/ijcai.2025/1034},
}

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TI  - AI4Contracts: LLM & RAG-Powered Encoding of Financial Derivative Contracts
AU  - Mridul, Maruf Ahmed
AU  - Sloyan, Ian
AU  - Gupta, Aparna
AU  - Seneviratne, Oshani
T2  - Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-25
PB  - International Joint Conferences on Artificial Intelligence Organization
PY  - 2025
SP  - 9305
EP  - 9312
DO  - 10.24963/ijcai.2025/1034
UR  - https://doi.org/10.24963/ijcai.2025/1034
ER  -