RPA & Business Intelligence

RPA automates high volume low value tasks in back end processes using tools and platforms powered by Artificial Intelligence. The robotics part thus does not refer to actual robots but applications or bots that perform the automation.
Once set up and implemented, robots take control of mouse and keyboard actions such as opening applications, clicking, copying and pasting information from one banking system to another, sending emails and other labor-intensive “low-value add” tasks. These robots work at the individual data field level and act similar to an Excel macro across internal software systems.

Top Benefits of RPA in Banks

    • Banking RPA does not require new core IT infrastructure change or upgrades.
    • RPA does not require coding experience.
    • Implementation is fast. Very fast.
    • RPA is hardwired for change. A banking robot can be installed or updated in less than a week when banking processes change.
    • IT intervention is minimal. Front-line employees can be trained to maintain and “manage” their own banking robots.
  • An RPA implementation actually increases (not decreases) morale of human workers by reducing the burden of boring data-entry work.
  • Robots work 24/7/365 meaning very high productivity, faster process throughput and thus a more responsive bank.

Business Intelligence 

A dedicated team of experienced Data Scientists, Consultants and an “Exploratory” young team of programmers combine to identify maximum impact business use cases for our customers. We then use data to identify operational excellence and cost control initiatives, and also predict business critical outcomes. Our clients make better decisions faster and have the edge as they aim for growth and market share.
Depending on business need and existing technology investment we use a combination of tools including several built by our own innovation factory. Our consultants have expertise across the board in many platforms and tools including:

  • SAP Predictive Analytics and SAP Business Objects BI Platform
  • IBM Cognos Analytics and Planning Analytics
  • Oracle Analytics Servers. Oracle Analytics for Applications
  • Open source Apache stack Hadoop, Spark, Storm, Cassandra as well as Mongo DB and R programming environment (Julia, Python, R)
  • Tableau and Qlikview