High-velocity staffing drives a holistic data-management strategy.

A growing FinTech partnered with Altimetrik to implement a world-class data platform to maximize loan originations, minimize risk provisioning, and build a highly scalable data platform.

Over the first four months of the project, Altimetrik ramped up an 83-member team including six data-engineering scrums, two data-science scrums, three product-engineering scrums, and four Salesforce-engineering scrums.

  • 40% Higher Scrum-team Release Velocity
  • 36% Improvement in Risk-assessment Accuracy
  • After 4 Months: 40 Hires per Month in 7 Tech Stacks
  • 8 Distinct Classes of Skills Staffed with Industry-leading Talent

A holistic approach and speedy team ramp-up drive positive business outcomes.

While some teams within the existing IT landscape and operating model were familiar with the agile approach, others were struggling—or simply maintaining an outdated SDLC. Some elements of a mature DevOps shop were missing, hampering the effective unified system needed for higher project velocity.

From a data analytics and data science perspective, no solutions or proven use cases had been established. Altimetrik took a holistic look at the data platforms, the approach to data management, and the use of data for business outcomes. Altimetrik proposed to drive agile maturity and fill in the missing pieces of DevOps (mainly QE automation) throughout the enterprise.

Altimetrik ramped up a 20-member team in the first month to get the project off the ground and quickly added another 63 team members in the following three months for a total of six data-engineering scrums, two data-science scrums, three product-engineering scrums, and four Salesforce-engineering scrums.

Outcomes Delivered

Maximized Loan Origination

  • Optimized the discoverability and ease of customer acquisition.
  • Intelligent analytics-enabled highly tailored loan products designed for the needs of the business-borrower segment.

Minimized Risk Provisioning and Maximized ROI

  • Assessed risk through machine learning to minimize the occurrence of bad loans or payment delinquency.
  • Clarified and simplified visualization capabilities to facilitate interest-rate decisions (pricing), predictive-uptake models and what-if analyses.
  • Improved accuracy of direct mail targeting by 36%.

Globally Seamless Commercial Ecosystem

  • Utilized a highly scalable platform tailored for globalization, multiple regulatory environments, operating processes, and business cultures.

“While there is some value in analytics being done by a small team sitting in an ivory tower, the real promised value of analytics for a company comes from immersing analytics in the day-to-day operations. By making sure decisions —small and large—are made with pragmatic analytics drawn from data, augmented by both the expertise and gut feel of the decision-maker.”

Jayaprakash Nair

Head of Analytics