Audit firms need to convert financial documents of companies into standard formats to do a credit analysis or/and financial audit. Businesses provide a variety of documents in a variety of formats. The first stage is to convert the financial information into a standard format for credit analysis. Documents such as invoices, purchase orders, checks, receipts, etc. have no standard format.
A lot of manual effort is spent in classifying the documents and extracting the data for analysis. As time is a constraint, the sample size of the documents is only processed to assess the presence of errors.
To do a comprehensive audit cost-effectively and in a short time, Audit firms use RPAs to automate some of the processes.
RPA can automate some parts of the processing, such as validating the extracted data with on-record information and feeding the data into audit systems. Still, RPAs have limited capacity to automate a large part of the process.
Intelligent Document Processing (IDP) can read images of documents, identify the document, extract the required information, understand and process the information. DocVu.AI has a Natural language processing (NLP) engine that enables DocVu.AI to identify the documents irrespective of templates, extract the data fields having varying data formats, and validate that against the company’s accounting system. DocVU.AI thus automates the most manual, time-consuming, cost-intensive, and error-prone part of the auditing process. Audit firms can increase costs or reduce service quality, increase the sample size to capture better any differences in the paper document and the company financial data, and investigate the processes lapses. Audit firms can also review all the documents to offer a 100% document audit service.