Case Study

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Process: Holdings, Futures, Security and Trade


  • Finance Industry is originated and operated by trade, security and holding data files even received via mails.
  • It is directed and manually processed by multiple support teams such as the team for checking Data Quality Monitoring and a team for checking finance and accounts.
  • These tasks have to be daily completed before market industry opens at 9am.
  • It is also necessary to the stock market value data and financial market data of the organization.
  • Manual interaction of multiple data sources is required (FX rates, futures, securities, holdings).
  • High quality data required in order to follow rules with regulations of organization.
  • Finance industry contain piled up documents with complex data files which have high human error rate.
  • Dependent on skilled employee for daily completion advances high risk profile.
  • Processes needs to interact with multiple applications such as CRM, Bloomberg, Terminal, legacy systems, web portals, email and excel.
Finance Case Study


  • The Robot can log in as employee user to the online portal and also employee server.
  • Robots can check for the requests and data files present and can extract the data as per type of request.
  • Robot then logs into the required applications as a named employee user and completes the transaction as per the process request. These include communications with secured and unsecured portals as well as interactions with real-time financial market-data systems such as Bloomberg terminal.
  • Once the process has been completed successfully, the Robot then emails the agents, fund manager, business unit with the appropriate update to the enquiry.
  • The Robot creates a log file of processed transactions and emails it to the nominated business unit.
  • If a transaction fails for any reason the Robots notifies the business unit and transfers the enquiry back to the unit to complete (i.e. files data not present).
  • If the transaction fails to complete due to an application not being available the Robot will re-try and notify the business unit/service desk of interruption.

Finance: Use Case


  • Quality improves and 0% error rate is achieved.
  • Degree of successful operation: 100% of effort is automated.
  • Improvement of Service levels: as now time differs from-45min to 7 min.
  • Reduction in all risk profiles and errors.
  • Reduction in operational costs due to FTE.
  • Improved scalability (On-boarding Robots 15 min vs Human 6+ weeks)
  • Reduction of over-reliance in skilled FTE and loss of money on FTE.
  • Improved staff retention – reduced of human resources on high volume but having low value work to focus on complex value work.
  • ROI (return on investment): 4 months.

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