Case Studies
Regulatory Analytics Lake for an APAC Retail Bank
- Industry: Banking & Financial Services
- Service Pillar: Data & AI → Data & Analytics
Executive Summary
An APAC retail bank faced significant delays in regulatory reporting due to fragmented data sources and manual consolidation processes. Each month-end close took over 10 days, impacting compliance timelines and operational efficiency. Mindmap Technologies implemented a modern, governed data architecture that automated ingestion, transformation, and delivery of analytics-ready datasets.
Client Challenges
- Multiple siloed systems (Core Banking, CRM, Risk, and Treasury)
- Manual reconciliation between data marts leading to inconsistent figures
- Reporting latency of over 10 days for key regulatory submissions
- High dependency on Excel-based reconciliation and adjustments
Our Approach
- Designed a centralized cloud-based data lakehouse with automated CDC ingestion from all core systems
- Established standardized schemas and business rule validations for data consistency
- Built star-schema regulatory marts with complete lineage and auditability
- Integrated a self-service BI layer for Finance and Risk teams with secure role-based access
Technologies Used
Kafka (CDC), Snowflake, Airflow, dbt, Power BI, Azure Data Factory
Key Outcomes
01
Reporting Time Reduced: 10–12 days → 2 days (80% improvement)
02
Data Accuracy: 98% lineage coverage and data integrity across reports
03
Faster Insights: Near real-time dashboards for key regulatory metrics
04
Operational Impact: 30% reduction in manual data preparation effort