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Implementation of Business Intelligence and Fraud Prevention System for Financial Institution

yalantis

Financial services

Business services

Information technology

Current Challenges

The client experiences significant financial losses due to sophisticated fraud schemes exploiting transaction processing times, manual refund requests, and undetected suspicious behavioral patterns. Operational inefficiencies from manual processes and lack of data-driven decision-making capabilities further impact profitability and customer experience.

About the Client

A US-based neobank specializing in digital financial solutions for millennials with integrated wealth management and rewards programs

Strategic Goals

Reduce fraud-related financial losses by 40% quarterly through automated detection systems
Improve operational efficiency via business process automation
Increase customer adoption rate by 5% through enhanced revenue streams and experience optimization
Establish real-time data visualization and analytics capabilities for proactive decision-making

Core System Requirements

Rule-based fraud detection module with threshold metrics
Real-time transaction monitoring dashboard
Historical data analysis with anomaly detection
Automated report generation and visualization tools
Database duplication for analytical processing
Workflow automation for low-complexity operations

Technology Stack

Amazon Redshift

Amazon QuickSight

Python

SQL

System Integrations

Production database replication
Real-time transaction processing systems
Customer analytics platforms

Performance Criteria

High-availability database architecture
Real-time processing latency <500ms
Enterprise-grade security controls
Scalable cloud infrastructure

Expected Business Outcomes

Implementation will result in 40% reduction in fraud losses per quarter, 5% quarterly increase in user adoption through enhanced service offerings, and significant operational efficiency gains via automated workflows. The BI platform will enable data-driven decision-making with real-time visibility into financial risks and customer behavior patterns.