Data Digital Financial Services

Financial Services Company Re-architected its Business Rules Engine Built on FICO Blaze

A leading non-banking financial company re-architected its business rules engine built on FICO Blaze and achieved a 95% reduction in response time for decision automation and increased platform scalability to support 1000 concurrent users from 50 users earlier.

Business Need

The financial services company sought to enhance its underwriting process agility and decided to implement FICO Blaze —a business rules management system—to enable consistent, reliable, and data-driven decision-making. Quickly realizing the benefits, the company decided to extend the implementation of Blaze to their other processes & lines of business and wanted to assess their current implementation to make sure its systems were optimized in terms of architecture, design, coding, and processes to enable a quick response from the BRE.

Tools and Technology

The client upgraded their existing FICO Blaze versions 6.1 and 7.2 to the latest version of FICO Blaze advisor 7.5. The client also introduced structured estimation & risk management and implemented ticketing/defect management tools like JIRA and Version One, and load balancers (Netscaler, Radware, Apache, and F5) to enhance scalability and availability of their platform.

Success Factors

The client cited ValueMomentum’s deep knowledge in BRE and expertise in the banking industry, their close collaboration with ValueMomentum throughout the implementation and assessment projects, and the efficacy of the detailed assessment as key factors for the successful implementation of FICO Blaze across their business-critical products.


Applying recommendations from the assessment allowed the company to reduce the time to change business rules from multiple days/weeks to 1 or 2 days, and the BRE response time across applications from 64 seconds to 3 seconds. The company also achieved improved availability and scalability of their systems without any downtime during production deployments, enabling an increase in the number of concurrent users – from 50 to 1000.

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