Implementation of a Next-Generation Customer Data Platform for Scalable Data Management in Financial Services

The client faces increasing complexities due to rapid business growth, resulting in fragmented and legacy data architectures that cannot efficiently handle the volume, variety, or velocity of data. Key pain points include slow data access times, limited support for real-time operational and analytical decision-making, difficulty integrating new data sources, and escalating infrastructure costs.

A large, mature banking institution focusing on retail, corporate, and digital banking services, seeking to modernize its data infrastructure to support real-time analytics and customer insights.

• Establish a unified, robust, and scalable data architecture supporting real-time data processing for operational and analytical purposes.
• Enable faster data delivery, targeting sub-3 seconds for data availability in analytics lakes or data stores and near-instant access (under 50 milliseconds) for external systems and customer-facing applications.
• Support ingestion and processing of high-volume, unstructured, and diverse data sources, including transactional and event data streams.
• Implement data governance frameworks that facilitate data discovery, lineage, and compliance, incorporating data anonymization where necessary.
• Reduce infrastructure costs by replacing legacy systems with cloud-ready, scalable solutions capable of handling billions of records efficiently.
• Accelerate data integration and deployment timelines, aiming for an initial operational setup within two weeks of project kick-off.

• Core data streaming engine for real-time event and change data capture (CDC) collection from source systems
• Data lakes for raw and enriched data storage supporting analytical and operational use cases
• Operational Data Stores (ODS) to house optimized domain-specific data for external systems like online/mobile banking and CRM
• GraphQL API layer for secure, read-only aggregation and presentation of customer data views
• API Gateway to route client requests to appropriate microservices with integrated security controls
• Data Hub for cataloging, metadata management, data discovery, governance, and lineage tracking
• GDPR-compliant data anonymization mechanisms to ensure privacy and regulatory adherence

• Source systems providing transactional data, event streams, and unstructured data
• External analytical tools and business intelligence platforms
• Customer-facing applications such as digital banking interfaces
• Security and GDPR compliance modules for data privacy management

• High data throughput supporting processing of approximately 10 billion records
• Data delivery latency of under 3 seconds for analytical data stores
• Real-time data availability for operational systems within 50 milliseconds
• System scalability to accommodate growing data volumes and sources
• Strong data security, access control, and privacy features including GDPR compliance
• Reliability and robust monitoring with tools like Prometheus and Grafana

The implementation of a cutting-edge, scalable data management platform is expected to vastly improve data access speeds, operational efficiency, and analytical capabilities. This will enable timely insights and decision-making, support high-volume data processing, and reduce total cost of ownership by replacing outdated legacy systems. The client aims to become more customer-centric and data-driven, gaining a competitive edge in the market.