
Optimizing Analytics Management in Financial Services
Analytics Management in Financial Services
InterSystems connects your analytics management process to the same source of high-quality unified data at each stage of analytics development. Our solutions integrate data from internal and external data sources, such as data warehouses, data lakes, data lakehouses, CRM systems, transaction systems, and external services. Clients can run their predictive and prescriptive analytics on this unified data layer or deliver normalized data to any consumer at the point of need.
When the entire analytics lifecycle is built on a unified data layer, your business has the potential to increase revenue and operational efficiency.

Analytics Management in Financial Services
InterSystems connects your analytics management process to the same source of high-quality unified data at each stage of analytics development. Our solutions integrate data from internal and external data sources, such as data warehouses, data lakes, data lakehouses, CRM systems, transaction systems, and external services. Clients can run their predictive and prescriptive analytics on this unified data layer or deliver normalized data to any consumer at the point of need.
When the entire analytics lifecycle is built on a unified data layer, your business has the potential to increase revenue and operational efficiency.

Model risk management is critical in identifying and mitigating risks throughout a analytics lifecycle, ensuring the reliability and accuracy of predictive models. Effective data management is an essential enabler of analytics capabilities for financial services firms, as it helps organizations transform raw data into meaningful insights that guide actionable steps.
The InterSystems Difference
Data Management for Analytics
Fragmented data and siloed technology contribute to a 15-18* month time-to-market for new analytics, hampering a firm's ability to adapt models at scale. Data quality and inefficient use of data throughout the model management process impact model performance and increase the cost of analytics development.
InterSystems solutions make it easy to build, test, and deploy models that incorporate more data from more sources at every stage of the analytics development process, supporting effective data analysis and decision-making.
Our solutions automate data integration and quality checks, orchestrate workflows, ensure adherence to governance and compliance frameworks, and seamlessly integrate into your analytics environment to eliminate data duplication and manual data wrangling.

Our approach to data management is fundamentally different from data warehouses, data lakes, and data lakehouses. We enable firms to implement
a smart data fabric that connects to data at the source, and applies transformations, data pipelines, business rules, security, and analytical processing to data as it's being requested. This ensures that data is always current and accurate for any consumer. Our solutions can be deployed in the cloud, on-premises, or in a hybrid approach.
* McKinsey & Co “Scaling Analytics Across Financial Services: Understanding the Value of Model Life Cycle Transformations”
Key Benefits
Our solutions are designed for high-performance mission-critical applications with roles-based access to ensure the right users are getting access to the right data at the right time.

We offer a comprehensive suite of cloud-first solutions that empower organizations to build and deploy high-performance, real-time intelligent applications. Our innovative technologies enable seamless integration, orchestration, and AI-driven insights across data and application silos, helping businesses unlock the full potential of their data to solve any business challenge.
Supporting Innovation in
Financial Services for Decades




