Background
Asset managers are increasingly turning to Snowflake’s cloud infrastructure to address the limitations of outdated databases. Migrating to Snowflake grants them access to a sustainable and secure platform that enables efficient data storage, processing, and analytics. This transition empowers asset managers to streamline operations, improve data accessibility, and reduce costs associated with maintaining on-premises infrastructure.
Client Challenge
A large insurance company’s asset management team was seeking to improve its approach to data management in response to its increasingly complex investment portfolio. The company recognized that transitioning to Snowflake would serve as a foundation for sustainable data analysis for years to come.
Desiring a partner to assist with the transition, the life insurer turned to RiskSpan – a preferred Snowflake partner with substantial experience in database architecture and management.
Specifically, the insurance company sought to achieve the following:
Systems Consolidation: Data stored across multiple transactional systems had contributed to data fragmentation and inefficiencies in data retrieval and analysis. The client sought to establish and maintain a consistent source of asset data for enterprise consumption and reporting.
Improved Reporting Capabilities: Quantifying full risk exposures in fast-moving situations proved challenging, leaving the institution vulnerable to unforeseen market fluctuations. Consequently, the client sought to improve its asset evaluation and risk assessment process by incorporating comprehensive look-through data and classification information. The need for various hierarchical classifications further complicated data access and reporting processes which required streamlining the process of producing ad-hoc exposure reports, which often required several weeks and involved teams of people.
Reduction of Manual Processes: The client needed more automated data extraction processes in order to create exposure reports across different asset classes in a more time-efficient manner with less risk of human error.
Reduction of Infrastructure Constraints: On-premise infrastructure had defined capacity limitations, hindering scalability and agility in data processing and analysis.
RiskSpan’s Approach and Solutions Implemented
Collaborative Partnership: RiskSpan worked closely with the client’s IT, risk management, and analytics teams throughout the project lifecycle, fostering collaboration and ensuring alignment with organizational goals and objectives.
Comprehensive Assessment: Together, we conducted a thorough assessment of the client’s existing data infrastructure, analytics capabilities, and business requirements to identify pain points and opportunities for improvement.
Strategic Planning: Based on the assessment findings, the collective team developed a strategic roadmap outlining the migration plan to the unified data platform, encompassing asset data consolidation, portfolio analytics enhancement, and reporting automation.
Unified Data Platform: Leveraging modern technologies, including cloud-based solutions and advanced analytics tools, RiskSpan orchestrated the integration of various data sources and analytics capabilities. Together, we consolidated asset data from various transactional systems into a unified data platform, providing a single source of truth for comprehensive asset evaluation and risk assessment.
Data Lineage Tracking: The team employed dbt Labs tools to build, validate, and deploy flexible reporting solutions from the Snowflake cloud infrastructure. This enabled the tracking of data lineage, adjustments, and ownership.
Daily Exposure Reporting: Leveraging automated analytic pipelines, we enabled real-time generation of exposure reports across different asset classes, enhancing the client’s ability to make timely and informed decisions.
Automated Data Extraction: We automated the data extraction processes, reducing manual intervention and streamlining data retrieval, cleansing, and transformation workflows.
Hierarchical Classification Framework: We implemented a hierarchical classification framework, providing standardized and consistent data hierarchies for improved data access and reporting capabilities.
Transformative Outcomes
Enhanced Decision-making: Implementing advanced analytics capabilities and exposure reporting empowered our client to make informed decisions more quickly, mitigating risks and capitalizing on market opportunities.
Operational Efficiency: Automation of data extraction, analytics modeling, and reporting processes resulted in significant operational efficiencies, reducing time-to-insight and enabling resource reallocation to strategic initiatives.
Scalability and Agility: The migration to a cloud-based infrastructure provides scalability and agility, allowing our client to adapt quickly to changing business needs and accommodate future growth without infrastructure constraints.
Data Governance and Compliance: The implementation of standardized hierarchical classifications strengthened data governance and compliance, ensuring data consistency, integrity, and regulatory adherence. By leveraging Snowflake’s scalable architecture and advanced features, this large asset manager is now positioned to maneuver both its current and future data landscapes. The implementation of Snowflake not only streamlined data management processes but also empowered the organization to extract valuable insights with unprecedented efficiency. As a result, the asset manager can make data-driven decisions confidently, enhance operational agility, and drive sustainable growth in a rapidly evolving market landscape.
