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Strengthening Regulatory Reporting and Data Integrity through SLA-Driven Managed Services and Intelligent Automation

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Overview

A leading European bank relied on FMIS for regulatory reporting, integrating data from multiple legacy systems, which introduced complexity in data consolidation and transformation. Frequent data quality issues, reconciliation gaps, and defects across environments were impacting reporting accuracy and timelines. Coforge partnered with the client to deliver a managed services model with strong governance, automation, and real-time monitoring to improve data integrity and operational efficiency.

Challenge

  • Managing Complex Data Consolidation and Ensuring Accuracy in Regulatory Reporting
  • Regulatory reporting dependent on FMIS integrating multiple legacy systems
  • Complexity in data consolidation and transformation processes
  • Frequent data quality issues and reconciliation gaps
  • Defects across PRE, UAT, and PROD environments
Challenges in ensuring timely and accurate reporting 

Solution

Coforge implemented a comprehensive managed services and transformation approach:

  • Provided L2 and L3 support for production incidents
  • Managed defect resolution across PRE, UAT, and PROD environments
  • Owned end-to-end SDLC for new requirements including design, development, testing, and deployment
  • Performed reconciliation and data quality and integrity testing
  • Established governance framework for managed services delivery
  • Delivered near real-time dashboards using Power BI with automated provisioning in PaaS using DaaS
  • Integrated dashboards with real-time alerts and implemented automated self-healing mechanisms
  • Leveraged machine learning models to reduce false alerts
  • Supported downstream functions including predictive modeling for fraud detection and transaction monitoring

Tools & Technology

Informatica Powercenter, Power BI

Resolving 95% of issues with Defined SLA | Closed Backlogs in 3 months | 24*7 support model| 20% HC cost reduction

Impact

Improving Data Accuracy, Operational Efficiency, and Compliance Readiness

  • Resolved 95% of issues within defined SLA across priority categories
  • Cleared backlog within first 3 months of managed services transition
  • Enabled 24×7 support model for handling incidents outside SLA
  • Achieved >99% success rate in real-time monitoring
  • Reduced downtime through automated self-healing mechanisms
  • Improved anomaly detection accuracy to over 99%
  • Reduced fraud by over 50 basis points compared to previous models

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