The Role of Financial Data Analytcis in Driving Strategic Decision in Asset Management Firms
- DOI
- 10.2991/978-94-6239-642-5_95How to use a DOI?
- Keywords
- Asset management; financial data analytics; risk management; machine learning; model risk; governance; ESG
- Abstract
This essay examines how financial data analytics shapes strategic decision-making in asset management firms, with a focus on risk management and governance. It reviews how integrated analytics platforms and machine-learning tools support portfolio construction, real-time exposure monitoring, scenario analysis, and faster decision cycles, improving visibility over market, liquidity, and factor risks. At the same time, it highlights the limitations that can reduce strategic effectiveness, including data quality issues, model risk and overfitting during regime shifts, and the interpretability challenges of “black-box” models. The essay argues that analytics delivers sustainable strategic value only when embedded within robust governance frameworks that ensure transparency, accountability, and disciplined human oversight - particularly as ESG metrics and alternative data become more central to investment processes.
- 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.
Cite this article
TY - CONF AU - James Midgley PY - 2026 DA - 2026/04/29 TI - The Role of Financial Data Analytcis in Driving Strategic Decision in Asset Management Firms BT - Proceedings of the 2026 11th International Conference on Financial Innovation and Economic Development (ICFIED 2026) PB - Atlantis Press SP - 914 EP - 920 SN - 2352-5428 UR - https://doi.org/10.2991/978-94-6239-642-5_95 DO - 10.2991/978-94-6239-642-5_95 ID - Midgley2026 ER -