Case Study: Lenddo achieves 40% IT cost savings and scalable global credit scoring with Amazon Web Services

Lenddo - Customer Case Study

Lenddo is a fintech company that helps businesses evaluate the character and identity of potential customers—often people with little or no credit history—so they can access credit and services. Running on AWS from the start, Lenddo built models that use thousands of social and transactional data points, but rapid growth of social-data storage (about 3.5 TB and rising far faster than member data) caused database index bloat and escalating costs on MongoDB/EC2, forcing a redesign to remain scalable and cost-effective.

In March 2014 Lenddo rearchitected on AWS: long-term social data moved to Amazon S3, frequently accessed data to Amazon DynamoDB with MongoDB as a daily cache, and compute scaled with EC2 Auto Scaling and Amazon EMR for Hadoop-based analytics. The new design cut monthly IT spend by ~40%, removed storage and latency bottlenecks, enabled fast, scalable credit scoring in minutes, and let the team focus on improving identity-verification and scoring algorithms.

Lenddo

Naveen Agnihotri

Chief Technology Officer