AgentRAG-DQ: Agentic Retrieval-Augmented Generation for Autonomous Data Quality Orchestration in Banking Warehouses

DOI

10.2991/978-94-6463-978-0_35How to use a DOI?

Keywords

Data Quality Management; Banking Data Integration; Retrieval-Augmented Generation; Agentic AI; Data Warehouse Architecture; Kimball Methodology

Abstract

The multiplied growth of financial information together with the often complex regulatory requirement has only worsened the challenge involved in maintaining information quality, integrity and coherence across dissimilar banking frameworks. In this manuscript, a detailed roadmap on data quality governance in the banking sector is outlined, addressing the relevant concerns in data integration, migration, and cross-system harmonisation. We present a new infrastructure that integrates symbiotically the traditional method of data warehousing with the state of the art Retrieval augmented generation (RAG) and agentic AI modalities. The framework standardizes multi-layered quality checks across the data life cycle starting with data extraction at source-systems, through ETL pipes, to data exploitation in OLAP systems. Empirical findings that are obtained through the migration of several large-scale banking data migrations indicate a 47% reduction in the occurrence of data quality incidents, a 63% increase in migration accuracy, 38% minimalisation of manual reconciliation labour, and a 52% shrinkage in the data mismatch resolution period.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Rambabu Tangirala
PY  - 2025
DA  - 2025/12/31
TI  - AgentRAG-DQ: Agentic Retrieval-Augmented Generation for Autonomous Data Quality Orchestration in Banking Warehouses
BT  - Proceedings of the 1st Engineering Data Analytics and Management Conference (EAMCON 2025)
PB  - Atlantis Press
SP  - 406
EP  - 416
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-978-0_35
DO  - 10.2991/978-94-6463-978-0_35
ID  - Tangirala2025
ER  -