Designed & built a central dashboard to track rolling 24 hour incidents. Use big data from social media channels (Instagram, Twitter, Facebook, Tumblr) to enable actionable insights from the real time stream of incoming data related to Barclays.
Reduce the time taken to action fraud by making data driven decisions. Get insight into customers sentiments, ability to drill down into complex data, easy to infer and make decisions. Cut down on the number of personal and training requirements. Reduce use of proprietary software for development, move to open source technologies and maintainablity.
Create an easy-to-use dashboard for incident & fraud detections. Complete separation of front-end and back-end using a micro-service architecture, to maintain strict security and data protection protocols. Create a front-end style guide to enable barclays to iterate and make changes.
Barclays found the v1.0 of the product significantly increased the performance of their fraud detection team and re-engaged our expertise to develop v2.0 with additional features.
Significant cost savings by creating a flexible, technology architecture based on open source software and tools. The open source software led to less reliance on proprietary software tools.
A simplified dashboard enabled the team to take the generated data and make faster decisions, reducing the time taken to action in fraudulent cases. This reduction in time to action, generated from the automated alerts within the dashboard, greatly improved the performance of the teams.
The complete decoupling of the front-end & back-end architecture allowed Barclays to work with external contractors by providing them access to dummy/anonymized data without worrying about maintaining compliance with their own strict security & data access protocols.
We are a diverse & multidisciplinary team spread across different time zones.
We are a remote, distritubed, multidisciplinary team. Located in different time zones.