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Banking & Financial Services

Enterprise Performance Management System for Security Operations

14 months32 professionals$7.2M budgetCompleted September 2024

Executive Summary

A major bank's Enterprise Security Division struggled with fragmented security data across 15+ systems, hindering strategic decision-making and compliance reporting. We implemented a comprehensive EPM system that unified security metrics, automated compliance reporting, and enabled predictive risk analytics, resulting in 85% faster reporting and 30% improvement in resource optimization.

The Challenge

Disconnected security systems preventing holistic view of enterprise security posture and performance

Key Issues

  • Security data scattered across 15 different tools and platforms
  • Manual compilation of metrics taking 2 weeks for monthly reports
  • No real-time visibility into security KPIs and trends
  • Resource allocation decisions based on outdated information
  • Compliance reporting requiring 100+ person-hours monthly
  • Unable to correlate security investments with risk reduction

Business Impact: Inefficient security operations and increased risk exposure due to delayed decision-making

The Solution

Integrated EPM platform consolidating all security data with real-time analytics and automated reporting

Phase 1: Requirements & Architecture

Duration: 2 months

  • Interviewed 50+ stakeholders across security divisions
  • Mapped 200+ security KPIs and metrics
  • Designed unified data model for security operations
  • Created integration architecture for diverse data sources

Phase 2: Data Integration

Duration: 4 months

  • Built ETL pipelines for 15 security tools
  • Implemented AWS Redshift data warehouse
  • Created real-time data synchronization using Apache Spark
  • Established data quality monitoring and alerting

Phase 3: Analytics Development

Duration: 5 months

  • Developed 30+ security performance dashboards
  • Built predictive models for risk assessment
  • Created automated compliance report generation
  • Implemented drill-down analytics for incident investigation

Phase 4: Rollout & Training

Duration: 3 months

  • Phased deployment across security divisions
  • Trained 150+ security professionals
  • Established governance and data stewardship
  • Created self-service analytics capabilities

Technologies Used

AWS RedshiftApache SparkTableauPythonREST APIsTerraformDockerApache AirflowPostgreSQLRedis

Results & Impact

85% Faster
Reporting Speed
From 2 weeks to 2 days for reports
30% Improvement
Resource Optimization
Better allocation of security resources
360° View
KPI Visibility
Real-time access to all security metrics
$2.8M Annual
Cost Reduction
Through automated reporting and optimization
94%
User Adoption
Active daily users across security teams
99.5%
Data Accuracy
Automated validation and quality checks

Business Impact

  • Reduced security incident response planning from days to hours
  • Enabled data-driven security investment decisions saving $4M annually
  • Achieved 100% on-time regulatory reporting for first time
  • Identified and remediated 40% of redundant security controls
  • Improved security team productivity by 45% through automation
The EPM system has transformed how we manage security operations. Having real-time visibility into our security posture and performance metrics has enabled us to make faster, more informed decisions that directly impact our risk profile and operational efficiency.
Head of Enterprise Security
Banking Enterprise Security Division

Key Lessons Learned

1

Start with most critical KPIs rather than trying to integrate everything at once

2

Executive dashboard adoption drives organization-wide usage

3

Data governance framework essential before technical implementation

4

Self-service capabilities reduce burden on analytics team

5

Regular feedback loops with users critical for continuous improvement

Next Steps

Following the success of this transformation, the roadmap includes:

  • Integration with threat intelligence platforms for enhanced context
  • Implementation of AI-driven anomaly detection in KPIs
  • Expansion to include third-party risk metrics
  • Development of automated security posture scoring system