Success Stories

    • Major Bank

      Business Problem: Bank wants to enable analysts and automate the market research process to increase performance and efficiencies. Reduce the IP liability on the data collected by the analyst. Ensure the data collected is accurate and functional.

      Engagement Model: SOW

      Project: Market Research Automation

      • Create RPA awareness within the Market Research division.
      • Assess and create Bots for Analysts to speed up the research process.
      • Create a centralized solution to ensure efficiency and IP compliance.
      • Replicate the model across all business functions within the division.


    • Big 5 Consulting Company

      Business Problem: PEGA Robotics is becoming the sought-after product in the RPA space. The demand is growing very rapidly. The Consulting Firm is setting up PEGA Robotics COE to service their clients. They don’t have the resource pool to execute their plan.

      Engagement Model: Time and Material
      Project: Establish the COE

      • Leverage our RPA practice and provide resources to help create POCs.
      • Create white-label teams to implement client projects.
      • Currently helping establish offshore RPA COE by mentoring off-shore resources.
      • Assist with the cost & price of opportunities.


    • Client: Major Bank

      Business Problem: Bank is instituting an Enterprise View of the Client process which will require client research and evidence to resolve discrepancies in key client data fields. BAC has identified ~25 external and internal source systems to perform this validation exercise.

      Researching clients, sourcing data and uploading evidence for every customer is expected to be manual, repetitive, and costly. The bank is automating this process to drive increased performance and efficiencies.

      Engagement Model: Time and Material


  • Project: EVOC

    • Robotics Process Automation used in the Enterprise View of the Client process to demonstrate the below capabilities for US Publicly Held Entities*:
    • Read Customer Data: Read customer unique identifier (e.g. ticker, tax ID) from Excel spreadsheet on Shared Drive and input into external sources.
    • Source Data: Locate related data from external and internal sources** (e.g., Mint Global site, Secretary of State site, NYSE site, Internal Bank systems). Extract customer information (e.g. name, address) and store it on the spreadsheet.
    • Validate External Data: Apply basic business logic to standardize the data set (e.g. 123 Ave. = 123 Avenue). Compare source data to external data and identify true matches.
    • Capture Screenshots: Capture and save screenshots from external sources as PDF (e.g. Mint Global, NYSE).
    • Upload Documents: Upload PDFs and Excel spreadsheets to a shared drive.