Artificial Intelligence in Finance: Predictive Analytics, Fraud Detection, and Risk Management in 2024

Goutham  Kacheru; Rohit Bajjuru; Nagaraju  Arthan

doi:10.55927/fjst.v4i1.13398

Authors

Goutham Kacheru Sr. Software Engineer, Apexon
Rohit Bajjuru Masters in Electrical Engineering, Southern Illinois University Edwardsville
Nagaraju Arthan Research Scholar, PhD in IT, University of Cumberlands

DOI:

https://doi.org/10.55927/fjst.v4i1.13398

Keywords:

Predictive Analytics, Fraud Detection, Automated Trading, Risk Management

Abstract

AI is poised to be transformative across virtually all industries, and the financial sector has already experienced major impacts from AI in predictive analytics, fraud detection and risk management among others. This paper also describes the innovation of AI, machine learning and natural language processing (NLP) technologies and their availability in financial services in 2024. Its scope covers richer credit scoring models which harness predictive analytics to assess borrower performance, more sophisticated fraudulent activity detection frameworks that can identify suspicious transactions in real-time, and countless automated trading algorithms which can dynamically adapt to changing market behaviors. Moreover, Algorithms have also deployed in the way financial institutions are evaluating and handling second risk management; AIdriven Risk Management tools have been also there to facilitate decision making process for operational efficiency. We discuss these challenges, and also show how AI will be a crucial part of fundamentally transforming financial analysis from optimizing customer service interactions to stabilizing the economy.

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