Laxmi Sunrise Bank, one of the largest commercial banks in Nepal headquartered in Kathmandu, is accelerating its quality-assurance and digital transformation efforts through the introduction of robotic process automation tools, according to a case study release shared with QA Financial.
Established in 2002 and known for its early adoption of technology in Nepal’s banking sector, Laxmi Sunrise Bank has used automation to reduce manual effort, eradicate errors and streamline data handling, outcomes that resonate with QA and software testing teams seeking more predictable and repeatable execution environments.
The bank’s automation journey began after it became completely paperless in 2018, marking the start of its transition to digital workflows.
“Robotic Process Automation [RPA] was the next step for us in this journey,” explained Jiwan Limbu, chief technology officer of Laxmi Sunrise Bank, reflecting on the bank’s broader modernisation strategy.
Limbu added that, as part of this shift, the institution, which is registered under the Banks and Financial Institutions Act of Nepal, partnered with certified RPA developers to deploy a platform that could integrate disparate systems and reduce manual error, laying the groundwork for more consistent testing conditions.
Data reliability
One of the core QA benefits of Laxmi Sunrise Bank’s automation programme is the reduction of time-consuming and error-prone tasks that previously undermined both operational and testing reliability.
Limbu explained that “fetching data from different systems was one of the most time-consuming jobs for us.”
For example, he said that “at the end of the day processing that takes place at every branch of the bank. Typically, it would take an employee almost an hour to carry out EOD at the branch. Now, we have a UiPath robot that does it in half the time with complete accuracy.”
This dramatic improvement in execution time and accuracy creates a more repeatable and traceable workload for QA engineers to validate across cycles, Limbu stressed.
Manual syncing of customer data from multiple systems was another challenge that hindered both operations and QA efforts.
These tasks were “time consuming, error-prone, and was difficult for employees to handle the inflow of work,” Limbu noted, describing how automation helped create more efficient and uniform workflows.
By eliminating variability, Laxmi Sunrise Bank has laid a foundation for QA teams to build more robust test suites, reduce false positives and establish confidence in regression outcomes.
A notable example of automation’s impact involved a core banking product migration project that once would have taken three months of manual work with sets of makers and checkers manually logging data.
For this initiative, Limbu explained that “we created a robot with sign in credentials to extract and punch in data. We not only reduced the time for this entire project, but also achieved 100% accuracy with no human error.”
For QA professionals, this demonstrates how high-volume, rules-based tasks can be reliably automated to reduce defect risk and produce consistent test environments.
Strenghtening QA foundations
Limbu also reflected on the reasons behind the bank’s choice of platform, noting that it evaluated several vendors before selecting one that was “the most approachable, responsive, supportive, and had the needed technical know-how to train our employees in developing and deploying the solution.”
This in-house development and training approach enabled Laxmi Sunrise Bank to grow internal automation competence, which in turn supports QA teams with deeper integration between automation logic and test frameworks.
Looking ahead, the bank plans to incorporate AI and machine-learning into its processes and train front-line staff in working with automated robots, a move that could further enhance quality and reduce manual variability across functions.
As Laxmi Sunrise Bank continues to embed automation into its workflows, Limbu argued that its experiences highlight how RPA can not only streamline operations but also bolster quality assurance practices by providing more consistent, accurate and repeatable execution, all essential ingredients for robust testing in complex financial systems.
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