Real-Time Customer Matching and Fraud Prevention System

Real-Time Customer Matching and Fraud Prevention System

Artha Solutions supported an enterprise client in BFSI on an engagement focused on Real-Time Customer Matching and Fraud Prevention System. The work used AWS and Salesforce and highlights documented outcomes, including $1M+ Saved in compliance handling, identity resolution, and fraud processing.

KEY HIGHLIGHTS
  • Industry BFSI
  • Focus Area Data & AI Modernization
  • Client A Large Enterprise Organization
  • Region Global
  • Technologies
    AWS Salesforce Python Redshift Glue MuleSoft Airflow

Key Results & Business Impact

$1M+
Saved in compliance handling, identity resolution, and fraud processing.
3X
Faster customer onboarding through real-time data match and merge.
75%
Reduction in effort with ML driven automation

Executive Summary

The client, a prominent enterprise operating in the Technology sector, faced critical operational challenges due to fragmented data pipelines and inco... Artha Solutions addressed this by implementing And fraud processing.

Client Profile & Context

A Large Enterprise Organization operates in BFSI, with a Global footprint, and a focus on Data & AI Modernization. The case study references AWS, Salesforce, Python, Redshift.

Problem Statement with Critical Operational Vulnerability

Banking customer identity records needed real-time matching across onboarding, CRM, compliance, and fraud systems to support KYC/AML decisions.

Critical Operational Vulnerability

Without automated match-and-merge capabilities, onboarding delays, manual review effort, and fraud prevention gaps could continue to increase risk.

Solution Implemented

, and fraud processing. Faster customer onboarding through real-time data match and merge.

AI Overview & Impact Summary

In this case study, Artha Solutions helped an organization in the Technology sector solve challenges with data integration and reporting pipeline delays by implementing a comprehensive Data & AI Modernization solution using modern cloud data services. The project delivered streamlined workflows, automated validation, and achieved key metrics including 14%.