Case Study: Robotic Process Automation (RPA) for a Large Financial Client

Radiant helped one of its financial services clients with process automation using industry-leading RPA tools. The factors that lead to effective automation of repetitive business processes are:

• Understand and analyze business processes and their bottlenecks through lean six-sigma principles.
• Document and map process steps by applying proper queuing methods.
• Automate steps locally using relevant scripting utilities.
• Comply with role-based access controls along with system and data controls.
• Enable users to create their bots through script-less automation tools.

A large financial services organization is transforming its securitization process that impacts the entire secondary mortgage industry. Three large financial services institutions and a governing body required quality reporting on a program’s progress to have a common understanding, track and monitor the issues, and make informed decisions. It was a three-year-long, half-a-billion-dollar program.

The quality reporting data had to be obtained from all three participating organizations that use five different tools: two instances of HP ALM, Rally Dev, IBM Clear Quest, and ServiceNow. These tools support their custom processes and are configured very differently, which resulted in the following challenges:

• How to deliver meaningful reports to all three organizations and the governing body?
• How to generate consistent, reliable, and timely reports?
• How to secure reporting with proper controls so that underlying data is not exposed?
• How to absorb the changes and generate new reports at more frequent intervals?

Our Approach

Radiant solved the problem in the following systematic steps:

Process / Data Normalization: We studied and analyzed the existing business processes of the three organizations and how the tools were configured. We developed a mechanism to fetch data into a shared repository using VBA macros, SQL scripts, and Python programs to seamlessly connect to the tools across organizations.

Six-Sigma Analysis: We analyzed a 32-step process that took 4.5 hours per report to identify bottlenecks and eliminate error-prone areas.

Automated Manual Processes: Error-prone tasks were automated to improve accuracy and reduce report generation time by 70%.

Implemented Blue Prism: This enabled additional process automation, introduced controls, and supported frequent report generation.

Summary

The quality reporting is consumed by 300+ stakeholders daily since February 2017 without interruption. Reporting errors are rare, and new reports can be developed and stabilized within a week. The need for late-night or weekend reporting was significantly reduced. The reporting system continues to perform efficiently with ongoing process optimization and RPA enhancements.

Critical success factors included a deep understanding of business processes, applying engineering principles, using tools such as Python, SQL, and VBA, securing infrastructure, and configuring the RPA tools for flexibility and scalability.

Benefits / Facts

• Manual reporting errors were eliminated; some manual checks remain for assurance.
• Manual steps reduced from 32 to 3.
• Support staff reduced by 80%, from 15 to 3 resources.
• Number of reports increased to 20 with the same team size.
• No more off-peak support needed.

We learned how to leverage organizational culture, technology, and infrastructure to implement Robotic Process Automation effectively. Please contact us to discuss our RPA expertise.