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Consumer credit management

Consumer Credit Behavioral and Data Analytics Firm

03 November 2021

consumer credit management

The Client

Consumer Credit Behavioral and Data Analytics Firm.

The Need

The client is a U.S.-based Consumer credit analytics firm with their products delivering real-time behavioral scores to creditors at real time to help lenders ability to risk-segment consumers and nudge consumers towards measurable improvements in their financial behaviors. The client works with some of the largest global finance institutions helping deliver real-time value with their analytics products.

The client needed a team of qualified engineers with expertise in developing enterprise solutions using J2EE, Data warehousing solutions, and data analytics and user behavioristics.

The Challenge

The client needed to set up an off-shore development with the right technical know-how to handle some of the big challenges associated with the finance industry.

  • Large Volumes of High-Velocity Data
  • Maintaining Continuous Availability
  • Delivering accurate analytics and assessments in real-time
  • PII Compliance, Data Encryption and Data Security
  • Provide Real-time Sentiment and Behavioral results of users

Clearly, the client understood that traditional RDBMS were not meant to scale to the several small transactions, scale horizontally, real-time performance and OLAP needed for their product and required solutions that would scale on-demand across different data centers with redundancy. Reliance on the selection of the right set of technologies, framework, proven solutions and expert resources to get their application right was highly critical.

The Solution

Star Knowledge understood the criticality of the required solution backed by an excessive amount of security measures to ensure customer data is secure at all times and provides real-time scalability and high-velocity performance.

With the client clear on a solution based on low latency, and high scalability with 100% availability, Star Knowledge helped the customer finalize the tech stack that would be the best suited for the purpose. The solution was built using Java’s enterprise framework J2EE, Hibernate framework, and Amazon Redshift to support its large-scale data warehouse and manage complex analytics queries and backed by fast read and write database clusters to complement the analytical capabilities of Redshift and IBM Watson to generate predictive statistical, behavioral and sentiment analytics.

For security purposes, the solution is complemented by ensuring PII compliance, secure PGP data encryption, and secure authentication using Spring Security and SFTP for file transfer.


  • Gain data-driven accurate real-time analytics
  • Continuous Availability and Real-time delivery
  • High-velocity data read and writes with faster scalability
  • Autonomous and easy administration of resources and workloads
  • No unplanned downtimes
  • Proactive alert management

Technology Used

  • J2EE
  • Spring Security
  • Hibernate
  • Spring MVC
  • Amazon RedShift
  • AngularJS and JQuery
  • Watson Data Insights

Looking to build similar applications? contact us, for your application needs.

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