Data Engineering Frameworks with AI and ML Algorithms: Fraud Detection and Prevention Strategies in Insurance Sector

In this study, the author investigates using data engineering framework along with AI and ML algorithms to detect and prevent frauds in insurance sector.In order to identify more fraud, we use predictive modelling, real time stream and anomaly detection.Intelligent fraud prevention systems are proven effective according to risk analysis and model performance evaluations.

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Publication Details

Published
2025-05-10
DOI
https://doi.org/10.63374/qitp-ijdeng_05_01_002
Primary Topic
Imbalanced Data Classification Techniques
Type
article
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article

Data Engineering Frameworks with AI and ML Algorithms: Fraud Detection and Prevention Strategies in Insurance Sector

Bhagya Laxmi Vangala
Imbalanced Data Classification Techniques
article

Data Engineering Frameworks with AI and ML Algorithms: Fraud Detection and Prevention Strategies in Insurance Sector

Bhagya Laxmi Vangala
article en

Abstract

In this study, the author investigates using data engineering framework along with AI and ML algorithms to detect and prevent frauds in insurance sector.In order to identify more fraud, we use predictive modelling, real time stream and anomaly detection.Intelligent fraud prevention systems are proven effective according to risk analysis and model performance evaluations.

Vol. 5(1)
Global Engineering and Materials (United States) (US)
Peace, Justice and strong institutions
Openalex Percentile: Top 95%
Imbalanced Data Classification Techniques
DOIOpen Access PDFOpenAlex
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Data Engineering Frameworks with AI and ML Algorithms: Fraud Detection and Prevention Strategies in Insurance Sector — Bhagya Laxmi Vangala · (2025) | TGRS Research Map | TGRS