Adoption of ML/RPA in
Audit report generation
Sankar Murugesan - Director - Digital Project Delivery
Aug 10, 2022
Powered by AI/ML
SOC reports are proof of the credibility of the organization’s ecosystem, which serves as a means to obtain the trust of other organizations. But preparing such a report is a highly laborious task. Because preparing a single SOC report by a third-party auditor demands processing a number of documents to extract the required information and prepare the report based on it. So it demands a highly qualified professional to carefully scrutinize these documents, which is highly time-consuming. Despite all this, the work is not free from clerical errors because the workload on the scrutinizing person is very high. This not only requires rework but also a loss of credibility for the service.
So, from the perspective of a century-old and one of the US’s top 10 audit firms, which processes around 10,000 documents per year to prepare SOC audit reports for its clients, the process is cumbersome and can hamper the business itself as a whole. Because
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Tremendous pressure on employees |
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The process is very slow |
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Loss of credibility |
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Prone to clerical errors |
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Lack of accuracy |
Changepond provided a path-breaking solution after making an in-depth analysis of the current process and inferring points to improve it. It used a two-step solution with an ML engine and an RPA bot. In the first step, the ML engine picks files from the shared folder, processes them, extracts data based on an inbuilt algorithm, and finally saves them in the shared folder in the Bot processable format. In the second step, the bot picks up the ML Engine-extracted data and prepares a memo file using generic templates. The prepared report is saved under the proper folder structure (/Processing, /Processed, /Not-processed) in the shared folder. The Scheduler/Trigger is used to start the ML-engine/RPA bot in the process.
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