What is the value of the Audit Common Data Model?

What is the value of the Audit Common Data Model?

Working with partners such as Microsoft, thirteen audit firms, academic institutions and supported by the Institute of Chartered Accountants in England and Wales (ICAEW), Engine B has created a new standard for the data that auditors can use ensuring completeness and accuracy – an Audit Common Data Model.

But, what is the significance of a Common Data Model for Audit? And how will it revolutionise the future of audit for years to come?

The audit industry needs to change

Audit is long overdue a shake-up. Current industry challenges such as increased regulatory pressures, a lack of competition, sporadic use of common data standards and the inefficiency of current data extraction processes have all created a burning platform for transformation. Undeniably, audit firms must now get to grips with regulatory changes and data challenges and open their minds to new, empowering ways of working.

In recent years, technological advancement has meant that auditors can automate audit processes and leverage Robotic Process Automation (RPA) applications and artificial intelligence (AI) to analyse General Ledgers, for example. Therefore, technological progression in the audit profession isn’t a new concept. The question is this: “While these new technologies help auditors to achieve more with less, are they accessible to all audit firms, no matter their size?” The answer is a resounding no.

A level playing field for audit

Many technologies used in the professional services industry, such as data extraction The audit industry needs to changetools, are either expensive or lock you into one ecosystem where you have to use one supplier’s data and analytics tools. Furthermore, these tools are developed primarily by large audit firms. As a consequence, it presents an issue for challenger audit firms or emerging players in the sector because it further increases the relative capacity of the leading firms and acts as a barrier to entry for smaller competitors.

In 2019, the CMA published a paper outlining serious competition concerns and proposing changes to legislation to improve the audit sector. They proposed companies are choosing audit firms with whom they have the best ‘cultural fit’ or ‘chemistry’, rather than those who offer the toughest scrutiny. The report also highlighted that auditors’ focus on quality appears diluted by the fact that at least 75% of the revenue of the Big Four comes from other services.

If choice is too limited, with the Big Four audit firms conducting 97% of the audits of the biggest companies – what if there were a requirement to share technology? Could it serve to open up the industry and create a level playing field for all audit firms, no matter their size?

We believe so. This is why Engine B has created the Audit Common Data Model.

How does it work?

Engine B’s Audit CDM works by providing a common data access platform that can be installed in any client environment. It’s unique in that is enables the interrogation and analysis of both structured and unstructured data. As audit firms roll it out, competing firms and even non-audit services organisations can leverage the Audit Common Data Model in the same client site.

The value of the Audit Common Data Model“The measure of intelligence, is the ability to change”

We know the digitisation of audit is a much-talked-about phenomenon. And whilst it is fair to say that audit services have evolved over the years, technology is evolving much faster resulting in a lag behind for the profession. Engine B’s Common Data Model for audit provides a clear opportunity for the industry to meet regulatory requirements, increase competitiveness and provide a better quality of services. As Einstein said, “the measure of intelligence, is the ability to change” – so we invite all firms, regardless of size, to join us in utilising our common data access platform and embrace the audit of the future.

Find out more about Engine B’s Audit CDM by downloading our Audit Common Data Model Guide.