FinAI: Deep learning for real-time anomaly detection in financial transactions

FinAI represents a groundbreaking deep learning framework designed to address the critical challenges of financial fraud detection in today's high-volume digital transaction environment. Traditional rule-based detection systems have proven increasingly inadequate against sophisticated fraud techniques, suffering from high false positive rates and delayed processing times. The FinAI solution integrates stream processing technologies with advanced neural network architectures on Cloudera's distributed computing platform to enable real-time anomaly detection across multiple transaction channels. Its three-tiered architecture—comprising a Stream Processing Layer using Apache Kafka and Spark, a specialized Deep Learning Engine, and a Self-Adaptive Learning Module—delivers substantial improvements in detection accuracy, processing efficiency, and operational cost reduction. Through continuous learning mechanisms that adapt to evolving fraud patterns, FinAI maintains exceptional performance while minimizing false alerts, fundamentally transforming fraud management economics for financial institutions worldwide.

Authors

Publication Details

Journal
World Journal of Advanced Engineering Technology and Sciences
Published
2025-05-09
DOI
https://doi.org/10.30574/wjaets.2025.15.2.0354
Primary Topic
Complex Systems and Time Series Analysis
Type
article
Field-Weighted Citation Impact
0.00
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article

FinAI: Deep learning for real-time anomaly detection in financial transactions

Jaydeep Taralkar
World Journal of Advanced Engineering Technology and Sciences
Complex Systems and Time Series Analysis
article

FinAI: Deep learning for real-time anomaly detection in financial transactions

Jaydeep Taralkar
article en

Abstract

FinAI represents a groundbreaking deep learning framework designed to address the critical challenges of financial fraud detection in today's high-volume digital transaction environment. Traditional rule-based detection systems have proven increasingly inadequate against sophisticated fraud techniques, suffering from high false positive rates and delayed processing times. The FinAI solution integrates stream processing technologies with advanced neural network architectures on Cloudera's distributed computing platform to enable real-time anomaly detection across multiple transaction channels. Its three-tiered architecture—comprising a Stream Processing Layer using Apache Kafka and Spark, a specialized Deep Learning Engine, and a Self-Adaptive Learning Module—delivers substantial improvements in detection accuracy, processing efficiency, and operational cost reduction. Through continuous learning mechanisms that adapt to evolving fraud patterns, FinAI maintains exceptional performance while minimizing false alerts, fundamentally transforming fraud management economics for financial institutions worldwide.

World Journal of Advanced Engineering Technology and SciencesVol. 15(2)
Openalex Percentile: Top 86%
Complex Systems and Time Series Analysis
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FinAI: Deep learning for real-time anomaly detection in financial transactions — Jaydeep Taralkar · World Journal of Advanced Engineering Technology and Sciences (2025) | TGRS Research Map | TGRS