Artificial Intelligence-Enabled Innovation Pathways for Financial Risk Management and Control

DOI

10.2991/978-94-6239-801-6_10How to use a DOI?

Keywords

Artificial Intelligence; Financial Risk Management; RegTech

Abstract

As the use of digital solutions in financial services and cross-regional operation increases, the number of risk-related signals is increasing faster. The paper categorizes the contributions of note technologies, including machine learning, deep learning, graph analytics, and natural language processing, as well as the underlying data platforms in identifying and assessing the risk and dealing with compliance management. It also produces synthetical problems of practical implementation. In order to overcome these challenges, this paper presents a couple of important strategic directions of this paper. The former entails the merging of multi-source data, and real-time intelligent analytics, to form an end-to-end process that includes risk identification, risk assessment, risk mitigation as well as feedback and, thus, allows continuous optimization of the risk control process. The latter highlights the RegTech automation adoption and complete lifecycle management of algorithms, including their development and retirement, to enhance compliance control and model risk management. In addition to these strategic directions, there are a set of supportive safeguards, which are necessary. These are strong data governance, high levels of privacy and data protection, interpretability of algorithms, constant observability of the models and systems and accountability in functions clearly defined throughout the organization. Taken together, these steps will offer an operational reference point in terms of making Artificial Intelligence (AI)-based risk control systems transparency-based, verifiable, and effective in the long term.

Copyright

© 2026 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  - Yufeng An
PY  - 2026
DA  - 2026/10/23
TI  - Artificial Intelligence-Enabled Innovation Pathways for Financial Risk Management and Control
BT  - Proceedings of the 2026 2nd International Conference on Financial Innovation and Marketing Management (FIMM 2026)
PB  - Atlantis Press
SP  - 78
EP  - 86
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6239-801-6_10
DO  - 10.2991/978-94-6239-801-6_10
ID  - An2026
ER  -