ISSN (Print): 3007-6706 ISSN (Online): 3007-6706
International IT Journal of Research Official Publication of Octopus Publication, Hong Kong
Cover of October-December, 2024
research article

AI in Insurance: Enhancing Fraud Detection and Risk Assessment

  • Chinmay Mukeshbhai Gangani

Vol. 2 , Issue 4 (2024) · pp. 226-236

DOI: 10.64180/oct.it.2424226

Abstract

An important development in risk management and fraud detection is the banking industry's use of artificial intelligence (AI). The revolutionary implications of AI in various fields are examined in this research, with an emphasis on the benefits and difficulties associated with its use. AI has a wide range of effects on risk management. Traditional approaches to detecting fraudulent activity and evaluating risks are becoming inadequate as financial transactions get more intricate and sophisticated. AI technologies provide a revolutionary answer to these problems because of their ability to analyse enormous volumes of data at previously unheard-of rates. The use of AI in financial services is examined in this study, with an emphasis on how it might improve risk management and fraud detection. This study explores the many ways artificial intelligence (AI) may be used to identify, stop, and handle fraud in the banking industry. In order to control risk and make wise judgements, the insurance sector has historically depended on actuarial science and historical data. However, a paradigm change in predictive modelling has been brought about by the development of artificial intelligence (AI) and machine learning (ML) algorithms, opening up new avenues for risk assessment and management.

Keywords: Know Your Customer (KYC) AI Real-Time Detection Banking Sector ML Algorithms Financial Transactions Predictive Analytics Textual Data Cross-Channel Analysis.
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