Data is at the centre of financial reporting and the auditing process. It can tell you a lot, objectively, about your business – and helps you to build a picture of a moment in time, spot unexpected outliers and exposure points, as well as trends for future strategy development.

But it is often an untapped resource for your business, not captured completely and efficiently or harnessed to its fullest capacity to give you actionable insights.

Technology is transforming the audit process: safeguarding and promoting transparency; enhancing accuracy and precision; and meaningfully impacting your decision-making process.

It’s a balance between accessing the right data analytics tools and technology for your needs and objectives, with an audit team skilled in asking the right questions and identifying what this data can tell you.

Grant Thornton’s data assurance team uses a range of data analytic tools and techniques across all phases of the auditing process, complementing and supporting your audit engagement team. We can extract large amounts of data from a range of data points within your organisation, and present and articulate the findings in ways that are not only simple, but also commercially-focused. This means effective and accurate proof points for sound and robust decision-making, identifying anomalies or high risk areas, and assisting the business to increase performance and productivity overall.

A case by case approach

We draw from a range of innovative data analytics and automation tools, and build a personalised approach dictated by your specific circumstances, objectives and needs.

Our core data assurance offering is embedded into our audit process providing a modern, standardised and effective audit testing. We understand your scope and data points relevant to your organisation and industry, and develop a tailored audit program. It incorporates data from multiple sources as well as automation that allows rapid development of bespoke and real-time analysis and benchmarking capability.

Bringing your data to life

How people – and business leaders – consume insights is very individual. When the insights gained from data are not clearly articulated, it can be meaningless.

There are many ways to bring static data to life for the purpose of better understanding your data, what it means and identifying ineffective controls or processes. Our team employs a range of visualisation techniques and tools to complement our data findings.

This allows us to not only review your data for audit purposes and provide added insights throughout the audit process, but also clearly highlight anomalies and identify root causes and, therefore, support development of a plan to address these.

Key services

  • Data analysis
    Data quality assurance & control
  • Analytic tools & techniques
    Data quality assurance techniques
  • Expert data quality analysts
    Quality data management

Whole ledger analytics

Background
A key requirement during an external audit was to examine the general ledger transaction population to identify any potential events of fraud or error in the financial reporting.
What we did
We developed a risk-based analytical tool using a number of data points to identify any potential transactions for further investigation. We began with an exploratory analysis to understand by first analysing the data points to understand their reasons for existing, and aligned to our understanding of the business, its internal processes and operations. We then determined the 'riskiest' factors to identify the key transactions to examine.
Value we add
Using a risk-based approach, we ensured that the audit was focused on where the risks and issues may have occurred. Adopting an exploratory-analysis approach meant we focused on asking the data to tell us the story, rather than performing some form of random sampling that may, or may not, have identified unexpected behaviour.

Insurance claims case study

Background
Many insurers offer opportunities to improve policy holder experience by automating the claims management process. However, these processes can sometimes be vulnerable to exploitation by others.
What we did
A large proportion of health insurance claims relate to ancillary benefits performed at small health practices, like dentists and optometrists. Using an automated claims approval system, the claims can be processed at the time a service is performed for a patient.
Value we added
Our Data Assurance team developed an analytical routine tailored to the insurance claims and the analysis identified claims occurring outside of normal business hours. These insights were provided to management to review their internal processes and implement controls to prevent claims being accepted outside of the expected business hours, reducing the chances of external fraud occurring.
Get in touch
Merilyn Gwan
Partner & Head of National Assurance Quality
Merilyn Gwan
Learn more about Merilyn Gwan
Merilyn Gwan
Partner & Head of National Assurance Quality
Merilyn Gwan

Get in touch

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Merilyn Gwan

What is data assurance? 

Data assurance:

Harnessing your data and data points to build objective proof points to help with decision-making, identifying anomalies or high risk areas in the business, and assisting the business to increase performance and productivity overall.

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