AI-augmented decision-making in financial services

Artificial intelligence has fundamentally transformed decision-making across the financial services industry. By integrating machine learning with human expertise, financial institutions now leverage AI systems to conduct real-time risk assessment, detect and prevent fraud, optimize investment portfolios, and provide enhanced decision support to professionals. These AI-augmented approaches enable faster analysis of transaction data, more accurate identification of patterns and anomalies, improved forecasting capabilities, and data-driven investment strategies. While delivering significant advantages in operational efficiency, credit risk management, fraud prevention, and investment performance, the industry still faces challenges related to regulatory compliance, model transparency, and data privacy. Looking forward, explainable AI, federated learning, natural language processing, and quantum computing represent promising directions for further advancing financial decision-making capabilities

Authors

Publication Details

Journal
World Journal of Advanced Research and Reviews
Published
2025-04-13
DOI
https://doi.org/10.30574/wjarr.2025.26.1.1169
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

AI-augmented decision-making in financial services

Swapna Reddy Anugu
World Journal of Advanced Research and Reviews
Big Data and Business Intelligence
article

AI-augmented decision-making in financial services

Swapna Reddy Anugu
article en

Abstract

Artificial intelligence has fundamentally transformed decision-making across the financial services industry. By integrating machine learning with human expertise, financial institutions now leverage AI systems to conduct real-time risk assessment, detect and prevent fraud, optimize investment portfolios, and provide enhanced decision support to professionals. These AI-augmented approaches enable faster analysis of transaction data, more accurate identification of patterns and anomalies, improved forecasting capabilities, and data-driven investment strategies. While delivering significant advantages in operational efficiency, credit risk management, fraud prevention, and investment performance, the industry still faces challenges related to regulatory compliance, model transparency, and data privacy. Looking forward, explainable AI, federated learning, natural language processing, and quantum computing represent promising directions for further advancing financial decision-making capabilities

World Journal of Advanced Research and ReviewsVol. 26(1)
Openalex Percentile: Top 89%
Big Data and Business Intelligence
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.