Real-Time AI for Financial Claims Processing: Architecture and Implementation

The integration of artificial intelligence in financial claims processing has revolutionized traditional operational paradigms, introducing unprecedented levels of efficiency and accuracy. This comprehensive article details the architectural framework of real-time AI systems in claims processing, focusing on the implementation of microservices architecture and event-driven processing mechanisms. The technical infrastructure encompasses sophisticated data ingestion protocols, advanced processing layers, machine learning components, and seamless integration interfaces. The implementation addresses critical challenges in latency management, scalability design, and fault tolerance through innovative optimization strategies and robust reliability measures. These architectural enhancements have resulted in substantial improvements across processing speeds, fraud detection capabilities, and system reliability metrics. Looking forward, the architecture demonstrates significant potential for further advancement through enhanced AI capabilities and technical refinements, positioning financial institutions for continued operational excellence in an increasingly digital landscape.

Authors

Publication Details

Journal
European Journal of Computer Science and Information Technology
Published
2025-05-15
DOI
https://doi.org/10.37745/ejcsit.2013/vol13n39122151
Primary Topic
Insurance and Financial Risk Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Real-Time AI for Financial Claims Processing: Architecture and Implementation

Srikanth Dandolu
European Journal of Computer Science and Information Technology
Insurance and Financial Risk Management
article

Real-Time AI for Financial Claims Processing: Architecture and Implementation

Srikanth Dandolu
article en

Abstract

The integration of artificial intelligence in financial claims processing has revolutionized traditional operational paradigms, introducing unprecedented levels of efficiency and accuracy. This comprehensive article details the architectural framework of real-time AI systems in claims processing, focusing on the implementation of microservices architecture and event-driven processing mechanisms. The technical infrastructure encompasses sophisticated data ingestion protocols, advanced processing layers, machine learning components, and seamless integration interfaces. The implementation addresses critical challenges in latency management, scalability design, and fault tolerance through innovative optimization strategies and robust reliability measures. These architectural enhancements have resulted in substantial improvements across processing speeds, fraud detection capabilities, and system reliability metrics. Looking forward, the architecture demonstrates significant potential for further advancement through enhanced AI capabilities and technical refinements, positioning financial institutions for continued operational excellence in an increasingly digital landscape.

European Journal of Computer Science and Information TechnologyVol. 13(39)
Industry, innovation and infrastructure
Openalex Percentile: Top 80%
Insurance and Financial Risk Management
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.

Real-Time AI for Financial Claims Processing: Architecture and Implementation — Srikanth Dandolu · European Journal of Computer Science and Information Technology (2025) | TGRS Research Map | TGRS