{"id":11096,"date":"2020-01-10T11:00:00","date_gmt":"2020-01-10T11:00:00","guid":{"rendered":"https:\/\/staging.zapliance.com\/?p=11096"},"modified":"2022-08-26T13:23:04","modified_gmt":"2022-08-26T13:23:04","slug":"external-auditor-digitize-yourself","status":"publish","type":"post","link":"https:\/\/staging.zapliance.com\/en\/blog\/external-auditor-digitize-yourself\/","title":{"rendered":"External Auditor, digitize yourself!"},"content":{"rendered":"\n

Digitization projects are currently underway in every industry. Everyone is looking for ways to successfully harness the digital transformation for the benefit of their business model. And of course, auditors are no exception. However, in the auditing industry, there are specific industry drivers that influence digital transformation. This article seeks to highlight some of these particular considerations.<\/p>\n\n\n\n

Fundamentally good prerequisites for digital transformation<\/h2>\n\n\n\n

Auditors are information service providers, that audit and certify. It takes a lot of information processing to analyze the customer\u2019s information and make a judgment. Postings in annual financial statements, i.e., at least those in the balance sheet and P&L statement, form a very structured dataset in today\u2019s ERP systems (often SAP in the case of larger companies). That, above all means, there are good prerequisites in place for using modern analysis tools and methods to analyze audit material efficiently \u2013 just as one would expect in the age of digital transformation. Customers \u2013 as the audited companies \u2013 are also likely to be very interested in efficient data analysis procedures.<\/p>\n\n\n\n

Audit standards and audit innovation do not always go hand-in-hand<\/h2>\n\n\n\n

However, my impression is that modern methods of data analysis are still being used with hesitation for auditing in the sense of a standard audit procedure model. That is probably due to the regulation of the profession. Innumerable auditing standards prescribe what is to be audited and by what means. However, modern methods of data analysis are only slowly becoming part of auditing standards. Therefore, auditors must always be asking themselves whether data analysis is sufficient as an audit procedure or which other audit procedures could be omitted. And because this cannot always be clearly deduced from auditing standards, one innovation or other often tends to be left out of the auditing process.<\/p>\n\n\n\n

Translate old world into new world<\/h2>\n\n\n\n

In this respect, the article \u201cHow Automation Will Change the Face of Audit for CPAs<\/a>\u201d by Christopher T. Kosty is refreshing. It makes reference to a document by the American Institute of Certified Public Accountants (AICPA), which aims to build a bridge between classic audit procedures and the possibilities of data analysis for these audit procedures. It is interesting to note that this work aid is known as the \u201cAudit Data Analytics to Audit Procedures mapping document<\/a>,\u201d which was published by an official professional association of auditors. The document is structured according to different audit areas and shows which data analysis tools and methods can be used to process classic audit procedures. Some suggestions from the audit areas are, for example:<\/p>\n\n\n\n