Unlocking the Potential of Unstructured Data in Finance Through Document Intelligence

Sriranjani Ramakrishnan, Himanshu Sharad Bhatt,Sachin Raja,C. V. Jawahar

PROCEEDINGS OF 7TH JOINT INTERNATIONAL CONFERENCE ON DATA SCIENCE AND MANAGEMENT OF DATA, CODS-COMAD 2024(2024)

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摘要
With the recent advancements, organizations have brought data to the forefront of their digital transformation journeys. Financial services industry is also moving towards adopting data-driven strategies for improved and faster decision making and providing enhanced customer experience. While advances generally in Artificial Intelligence (AI) and specifically in Machine Learning (ML) have fueled a lot of analytics, it is largely restricted to structured data as it is well organized and is easy to work with. This tutorial presents the opportunities to unlock the potential in unstructured documents in financial domain. These forms of data are more challenging to interpret, but can deliver a more comprehensive and holistic understanding of the bigger picture. While there are challenges around processing such document, ability to quickly make decisions by leveraging such data can provide differentiated value propositions and competitive benefits. This tutorial start with select problems & challenges in Document AI space and use cases involving such documents, show the business opportunities present and describe the technical challenges involved. Subsequently, we discuss techniques and algorithms for several document processing requirements and real world applications.
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关键词
Document Intelligence,Information Extraction,Table Struc- ture Recognition,Document Structure & Component Understanding,Tampering & Authenticity,Document Visual Question Answering
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