Many organisations are required to provide mandatory operational reports to industry regulators. Given these reports’ periodic and non-revenue-generating nature, staff often manually create them. Using MuleSoft automation for regulatory reporting would avoid relying on staff members with historical knowledge of the requirements and previous processes.
Historically passing this task off to newer team members has introduced errors, as they often have to learn new and complex requirements. The penalties for failing to create accurate reports can be severe, with many enterprises having received high-profile public reprimands and fines.
The Challenge Faced Today
Automation and modernisation of these processes have taken a backseat to other revenue-generating projects. However, creating some reports has become unmanageable, with multiple disparate, legacy systems, sometimes with only GUI access to source the data.
The laborious, manual tasks to implement the process are out of sync with the pace of change organisations must deal with today. Additionally, these reports are infrequent, requiring structured and unstructured data, such that traditional reporting tools can be a costly fit.
With the advent of MuleSoft’s automation capability (MuleSoft Composer and RPA), solutions can be created iteratively to automate various tasks, eventually being combined to automate the complete end-to-end process.
The Solution
Mulesoft Composer has a scheduler task step that can be used as a trigger to compile these reports by orchestrating the data gathering from various sources. Composer can use its out-of-the-box connectors for standard applications or, where necessary, trigger an RPA Bot for less-defined interfaces.
The diagram below shows how the data can be gathered from the following sources.
Shown on the diagram are the following sources and connections
- Google Sheet. This represents the storage of the transient data collected during the process. This connection can trigger the process if the scheduler is insufficient, especially during unit testing.
- Internet. This represents a Composer HTTP call to get data from an application with a well-defined and exposed API.
- File Extracts. It is common for applications and data stores to provide ordered data extracts in a text file. An RPA Bot triggered by Composer can read this text file.
- Internet or, in this second instance, screen scraping bots. An everyday use of RPA bots is for internet screen scraping, whereby the application has no interfaces or cannot provide one to the required security levels. However, it may have an extract capability via user menu options, so in this scenario, an RPA bot can log in, filter the data and then select to download the information to an extract. Hence, this step represents user screen data collection.
- Jira. Represents an application that has an out-of-the-box Composer connector.
Note – Some connectors have limitations, such that the out-of-the-box connector has to be replaced with an RPA bot or Anypoint Platform API. Hence, some data collection steps will need an alternative method, such that the Composer connector calls an RPA Bot / Anypoint API application/client solution as an intermediate step.
- The last step indicates that Composer would create a Google Sheet for a user to review the information collected to ensure no errors. This step can be bypassed if the organisation has confidence in the final report created. Still, if a user guardrail is preferred, the user can trigger the transmission of the last file once successfully reviewed.
Note – A Google Sheet could be a text file stored on the VM where the RPA bots are run. Additionally, automated checks can be made on the file created, depending on the reporting template Swagger file. This would give greater assurance to the point where the review step may be removed if the reviewer is confident that the report has passed all the checks. User confidence can be built up over time as the solution allows multiple and frequent iterations of the process. This develops agile feedback in conjunction with regulatory reporting processes to improve report quality, along with the risk reduction benefits.
Benefits
The benefits of using MuleSoft automation for regulatory reporting are as follows:
- Removal of error-prone manual operations.
- Reduction of dependence on staff with historical business knowledge.
- Reduction in the inefficiencies or re-learning the process and requirements each time the report needs to be generated.
- Reduction in the risk of fines.
- Transparency in the process of auditing.
Conclusion
Using MuleSoft automation for regulatory reporting provides a solution to streamline traditional manual reporting processes and offers numerous benefits to those implementing a solution.
It streamlines and simplifies the reporting process, reduces manual errors, saves time and frees up resources to work on revenue-generating tasks.
We have shown the flexibility of MuleSoft Composer and RPA in implementing a solution. Demonstrating how they can connect to virtually any endpoint or application and retrieve data, regardless of technology and deployment. Using MuleSoft automation in this way is becoming necessary to avoid financial penalties and remain ahead of competitors. If you’d like to know more about MuleSoft Composer or RPA and how to automate processes within your business, you can get in touch here.
