What Is The Secret To Data Analytics And Audit Quality?
Data analytics has already made significant inroads into various aspects of finance and accounting. Business Intelligence platforms are utilising data analytics tools for planning, budgeting, and reporting, and audit functions are not far behind. A survey of 150 senior audit practitioners by the ICAEW revealed that around 70% believed data analytics can improve audit quality. This is in addition to other benefits such as additional insights, cost-saving, fraud detection, etc. How exactly however does data analytics improve audit quality?
Exploratory and confirmatory data analytics
Exploratory data analytics is employed to find interesting patterns in existing data. This is useful because it may reveal some obscure relationship between variables not easily visible to the naked eye.
Confirmatory data analytics is deployed to look for the existence of certain predefined patterns and confirm a hypothesis. This could be useful in situations where combing through reams of data using traditional technologies would be prohibitively time-consuming. Thus, rather than relying on workarounds like data sampling, confirmatory data analytics can provide a more comprehensive and decisive outcome – therefore reducing the potential risk.
Another key benefit of data analytics is its significantly increased ability to detect fraud and other operational breaches. Companies and even regulators are already using such techniques to look for suspicious patterns in high-risk activity.
Making it work
Despite the benefits that data analytics clearly provides, there are certain challenges which restrict its usefulness in a general sense.
The most obvious challenge is the cost of deploying such a system. Although, with time and broader adoption, the costs are coming down. Software vendors are now developing tools and making them available to corporate clients at more affordable price points. This brings us to the second, and more long term, challenge – lack of a skilled workforce with the appropriate skillset to operate such systems. Even large, professional auditing firms are struggling with skill shortages in this field as it requires high-level cross-disciplinary expertise.
Other challenges remain around data integrity and access. The results from data analytics depend on the quality of the data that is fed into it in the first place. Tech companies relying heavily on data analytics have their entire systems designed around the collection of meaningful data, while for most other companies it is usually a patchwork of disparate legacy systems. This means that data quality can vary wildly, and this, in turn, can impact audit quality.
The benefits of data analytics in compliance, risk management, and audit are apparent. It increases audit quality and, in most cases, provides an additional insight which can prove to be invaluable. However, the dearth of skilled manpower remains a key challenge This will require significant company investments in the development of technical skillsets as well as analytical mindsets on the part of practitioners.
Submit Your CV, or Search Jobs to find out about the roles we currently have available.
Send Us Your Vacancy and one of our consultants will be in contact to discuss your requirements and how we may assist.
Our Renaix Guide to Big Data, Analytics and Fintech provides information on trends in the industry.
On the hunt for your next role? Upload your CV below and we’ll be in touch to discuss your requirements.
For employers seeking the right skills and cultural fit for your business, send us your vacancy to find out more about how we can help.Submit CV Send Us Your Vacancy
Popular this week
- What Qualifications Are Needed To Be An Accountant?
- Agile For Accountants: Six Steps To Provide Necessary Tools And Relevant Processes
- How Does Industry 4.0 Differ From The Previous Generation?
- What Are The Top Five Financial Accounting Facts For #AccountantsDay
- Here’s What Really Matters In Diversity In Educational Backgrounds