Srijan | Case Study

Developed an AI-Powered Platform for a FinTech to Improve their Analytics-Driven Decision Making

Written by Suhita Ghatak | Jul 30, 2021 3:31:07 AM

Requirement

They needed a platform that was configurable and scalable to serve the needs of their customer.

The Challenge

The project required high time-compliance as the business operations were based on this platform.

The Solution

The fruitful collaboration between our team and their experts led to the development of a ready-to-use platform-based solution that is: 

  • Easy to configure, scale, and deploy
  • Industry-agnostic and allows workflow orchestration for any use case
  • AI-ready to automate redundant manual tasks
  • Flexible to configure business compliant data analysis rules
  • Capable of analyzing the input data based on a set of rules
  • Intuitive in highlighting the data anomalies and breaches for audit purposes

Overall Approach

A custom combination of solutions was utilized to create this dynamic and accurate platform. The host of AWS services were utilized for monitoring, logging, assessing, auditing, and evaluating the processes. We used Camunda for modeling and creating complex custom workflows that were tailored to the business domain. Data Analysis services in python allowed us to run Data science checks to detect exceptions.

Tech Stack

  • Tools: Camunda, DataBricks
  • Cloud Platform: AWS 
  • Frameworks: AngularJs(JS) , NestJs(Nodejs) , API Platform(PHP)
  • Deployment: Docker, Kubernetes, Spinnaker

 

Benefits

  • Efficient resource allocation and removing repetitive tasks led to a reduction in labor hours by 80-95%. 
  • Streamlined internal processing and enabled higher productivity via a collaborative dashboard
  • Quick onboarding and processing of newer clients 
  • Higher Accuracy of ~45% in prediction forecast for their customers