Solution Brief

The Power of the Semantic Layer in Financial Services

Semantic Layer for Financial Services
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The financial services industry is facing unprecedented change, driven by evolving customer expectations, regulatory pressures, and the growing importance of data-driven decision-making. To thrive in this environment, financial institutions must leverage their data to deliver exceptional customer experiences, gain a competitive edge, and foster innovation. The semantic layer emerges as a critical tool, simplifying data access, fostering trust in analytics, and enabling self-service capabilities.

The Role of a Semantic Layer

A semantic layer provides a unified, business-friendly representation of data, enabling organizations to simplify data complexity, enhance decision-making, and drive collaboration. Some key benefits include:

    1. Simplified Data Access: Maps complex datasets into business terms like “portfolio,” “revenue,” or “customer.”
    2. Faster Time to Insight: Accelerates query performance and reduces data preparation time.
    3. Trusted Insights: Ensures data consistency and governance for regulatory compliance.
    4. Cost Optimization: Reduces cloud costs by eliminating redundant data processing and optimizing compute usage.

Financial Institutions leverage a semantic layer to instill trust in Generative AI and analytics-driven KPIs. A semantic layer can yield:

  • $2+ million in analytics project cost savings
  • 3x increase in ROI of IT investments
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"Customer experience is critical. Customers demand diverse, flexible options, and organizations must leverage data to meet these needs."

Ramdas Narayanan, Bank of America

"Driving an analytics transformation requires both technical capabilities and a strong data-driven culture within the organization."

Jon Francis, PayPal

ROI of Semantic Layers in Financial Services

  1. Optimized Cloud Costs: Semantic layers reduce cloud analytics costs by over 3x by optimizing compute usage, improving query performance, eliminating redundant data copies, and streamlining data preparation.
  2. Optimized Human Capital Costs: Using a semantic layer reduces the effort for a typical 1,000-hour analytics project by nearly half. An average organization has 25 such projects annually, estimating savings of $2.3 million annually.
  3. Trusted Results through Data Governance: AtScale’s semantic layer delivers result consistency and improves text-to-SQL performance, achieving nearly 100% accuracy by providing analysts and LLMs with a common business language, by mapping diverse data into familiar terms like “product,” “customer,” and “revenue.”
  4. Improved Customer Outcomes: Accelerate time-to-insight by 4x, enabling proactive decision-making that enhances customer experiences.

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