A more fluent audit with natural language processing

Natural language processing (NLP) is an area of computer science and artificial intelligence (AI) that aims to enable computers to process substantial amounts of natural (or human) language data. NLP attempts to address the inherent problem that while human communications are often ambiguous and imprecise, computers require unambiguous and precise messages to enable understanding..

NLP could significantly empower the audit, as it would enable auditors to analyse unstructured data.  Structured data — found in spreadsheets and ledgers — can already be comprehensively analysed using  data & analytics (D&A) and automated capabilities. But more than 80%[2] of data today is in unstructured formats such as contracts, emails, PDFs, and other documents. A key battleground is to develop digital assistants that can read this data and identify key information. Having a bot, for example, analyse the accuracy of one of those unstructured files. The development of NLP capabilities to read emails is another example. By using the processing power of intelligent machines, we can use correlation theory to extract data from unstructured sources.

Once the technology has been instructed on what to look for by the auditor, NLP could read emails and other documents to search and identify information (also utilising optical character recognition technology that can ‘read’ documents such as PDFs). The difference between the technology doing this and a person is scale — an NLP application could read thousands to millions of documents in a fraction of the time it would take a human to perform the same task. These NLP technologies can be used in combination with other modern technologies such as RPA (Robotic Process Automation) to execute tasks based on email content to deliver powerful efficiencies within a range of business processes.