CIAM Data Hub Architecture for Multi-Channel Identity Access
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Solution Overview
Problem
Existing data storage and processing systems in financial institutions face challenges in integrating complex and diverse applications, managing identity and access, and ensuring efficient data aggregation and reconciliation, which hampers customer experience and compliance with regulatory requirements.
Innovation Solution
Implementing a Customer Identity and Access Management (CIAM) system that integrates with an Enterprise Customer Information Facility (ECIF) for credential management, supports biometric authentication, and uses a processor to manage access controls and data entitlements, while integrating with a data hub for efficient data processing and analytics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple credentials and authentication methods are supported across different channels, then customer experience and adaptability are improved, but system complexity increases
Solution Approach 1:
The CIAM system is designed as a universal platform that handles multiple authentication methods (passwords, biometrics, device fingerprints) and multiple channels (web, mobile, ATM) through a single integrated architecture. The system uses a unified credential store and access control mechanism that can accommodate various authentication types without requiring separate systems for each channel or method.
Solution Approach 2:
The ECIF serves as an intermediary layer between the CIAM system and various application systems. It provides a standardized interface for credential verification and access control, mediating the complexity between the diverse authentication methods and the underlying application systems. This intermediary structure allows the system to support multiple credentials while maintaining manageable architecture.
2Reliability
If access controls and authentication enforcement are implemented at multiple layers, then security and reliability are improved, but processing time and system response increase
Solution Approach 1:
Access control policies and credential verification rules are pre-configured and cached in the system. When authentication requests arrive, the system can quickly match credentials against pre-established policies without performing complex real-time analysis, thereby reducing processing time while maintaining security. The system performs preliminary validation of credential formats and policies before actual authentication occurs.
3Loss of information
If event data capture and analytics are implemented for identity management insights, then decision-making and compliance are improved, but data storage requirements and processing complexity increase
Solution Approach 1:
The system extracts and stores only the essential event data needed for identity management analytics and compliance reporting, rather than capturing all possible system events. The ECIF selectively captures relevant authentication events, access control decisions, and user activity information, filtering out unnecessary data while maintaining the insights needed for effective decision-making and regulatory compliance.
Data Source
AI summary
Embodiments relate to data storage systems and data processing systems using a data hub, connector grid, and channel services. The systems can extract raw data from a plurality of source systems, and load and store the raw data at a data hub implemented by a non-transient data store. The systems can receive request to generate data for consumption and, in response, transmit generates data sets to channel services. The system can implement event detection and logging. The system can implement policy enforcement and identity management with access controls.