Summary of Identification Of Regulatory Requirements Relevant to Business Processes: a Comparative Study on Generative Ai, Embedding-based Ranking, Crowd and Expert-driven Methods, by Catherine Sai et al.
Identification of Regulatory Requirements Relevant to Business Processes: A Comparative Study on Generative AI, Embedding-based Ranking, Crowd and Expert-driven Methods
by Catherine Sai, Shazia Sadiq, Lei Han, Gianluca Demartini, Stefanie Rinderle-Ma
First submitted to arxiv on: 2 Jan 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed paper explores the challenge of identifying regulatory requirements relevant to business processes in a rapidly changing regulatory landscape. Domain and legal experts currently rely on manual methods to assess compliance, which is time-consuming and prone to errors. To alleviate this burden, the authors investigate three AI-powered approaches: an embedding-based NLP ranking method, a generative AI method using GPT-4, and a crowdsourced method. These methods are evaluated through two case studies: an Australian insurance scenario and a global banking use case. The study provides insights into the strengths and weaknesses of each method in terms of applicability, automation, transparency, and reproducibility, ultimately offering guidelines for selecting the most effective combination of methods based on factors like process usage, impact, and dynamics. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper looks at how to help experts identify which rules are important. Right now, they have to do this by hand, which takes a lot of time and can be tricky. The authors test three AI tools: one that uses words and phrases, another that generates text, and a third that asks people for input. They use these tools to evaluate two scenarios: an insurance company in Australia and a bank that operates worldwide. The study shows which methods work best for different situations. |
Keywords
» Artificial intelligence » Embedding » Gpt » Nlp
