Unified Financial Services Data Platform

3 posts · Feb 2023 – Sep 2026

What this trail covers

Elastic and Google Cloud enable financial institutions to build comprehensive customer financial profiles by integrating data from mainframes into BigQuery for processing and enrichment, and then into Elastic Cloud for advanced search capabilities. This architecture supports use cases like enhanced customer experience, Customer 360 views, partnership management, cost optimization, and risk reduction through fraud detection. The system allows for data migration and orchestration from mainframes to cloud-based data stores, enabling unified data for AI-powered fraud prevention, security, and compliance.

All Elastic trails

Sep 2026The security attack hiding in your unified dataThis post details how unifying observability and security data on a single platform (Elastic) enables AI agents to perform cross-domain investigations, turning observability alerts into automated security investigations. It highlights that attackers exploit the gap between separate platforms, leading to duplicated costs and missed threats. The post emphasizes that existing observability data contains valuable security signals, and a unified ingest layer makes this data queryable by all teams. It also discusses grounding AI agent reasoning in organizational procedures by ingesting playbooks into Elasticsearch, enabling auditable and actionable recommendations. The core technical contribution is the architectural pattern of co-located, jointly queryable data for AI-driven cross-domain analysis, turning a single alert into a comprehensive investigation with auditable steps.
Aug 2026Smart city data, operations, and securityThis post details how Elastic enables the unification of smart city data by bridging Operational Technology (OT) and Information Technology (IT) environments. It explains the architecture using Elastic Agent managed by Fleet for normalizing data from legacy industrial protocols and modern IoT sources into Elastic Cloud. The post emphasizes the value of correlating OT and IT data for real-time operational insight, faster incident response, and improved decision-making through Kibana dashboards. It also highlights the importance of geospatial data for context and discusses security considerations for connected OT infrastructure, including Zero Trust principles and MITRE ATT&CK® for ICS mapping.
Aug 2025Why intelligent banking starts with unified, AI-powered dataThis post emphasizes the critical need for unified data platforms in financial services to combat AI-driven fraud, enhance security, and meet compliance demands. It highlights how Elastic's Search AI Platform, combining observability, security, and fraud prevention capabilities, can transform fragmented defenses into a cohesive operational fabric. The post details how Elastic Observability provides full-stack visibility, Elastic Security unifies SIEM and endpoint protection with AI-driven investigation, and Elastic for fraud prevention leverages machine learning on behavioral and contextual data. It advocates for cloud-native infrastructure and a modular, iterative approach to transformation, starting with single use cases and expanding to build a resilient, AI-powered financial ecosystem.
Feb 2023How to build comprehensive customer financial profiles with Elastic Cloud and Google CloudThis post details a reference architecture for building comprehensive customer financial profiles by integrating mainframe data with Elastic Cloud and Google Cloud. It outlines a process for moving data from mainframes to Google Cloud using a Mainframe Connector, processing and enriching it in BigQuery, and then ingesting it into Elastic Cloud for search capabilities. The architecture supports various use cases including customer experience, Customer 360, partnership management, cost optimization, and risk reduction (fraud detection). It also presents advanced mainframe capacity planning strategies, such as remote dataset transcoding on Compute Engine VMs and data transfer via FICON and Interconnect.
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