IRIS joins the automation race with Ai Auditor
Accountancy software group IRIS has teamed up with specialist developer MindBridge Analytics to launch its first artificial intelligence product for UK practitioners.
The IRIS Ai Auditor is based on software developed by MindBridge that applies machine learning and other AI techniques to help auditors identify data anomalies and risky transactions within a company’s financial data.
Similar versions of the software are already being used at Kingston Smith and other large UK accountancy firms, but the IRIS partnership will help the Canadian company reach a much wider network of customers.
“It’s a very synergistic partnership,” said IRIS chief product and marketing officer Nick Gregory.
“We know about accountancy and 80% of the top 100 accounting practices in the UK are IRIS customers. We’ll be introducing them to AI and what it can do for their audit services. Many firms have already been looking at this area and quite frankly we’re pushing at an open door.”
The audit market has developed into two tiers, where the Big Four have sucked up all talent and big customers, Gregory explained: “The next tier down, the top 200, want to do audits but find it very difficult to compete. The talent shortage means they’ve got to pay a lot to deliver audits, plus there’s a lot of risk. Ai Auditor will help our customers compete with the Big Four and provide an audit service at prices their clients can afford.”
When IRIS started looking around for a viable solution, MindBridge was the obvious choice, he added. “We’re putting it under our IRIS AI banner, but when a firm buys it, the product will be MindBridge AI. It’s got momentum and credibility in the market, so we’ll be hitting the ground with a recognised product,” Gregory said.
MindBridge CEO Eli Fathi sees “huge potential” for artificial intelligence in accountancy: “We believe that AI will not replace auditors but auditors who use AI will replace those who don’t.
“AI allows them to transform their practice towards an intellectually augmented, efficient and cost-effective workforce... AI will empower accountants to do their job more efficiently, accurately and effectively all with a greater depth of analysis into the financials.”
For IRIS, the AI initiative is partly about keeping up with the marketing arms race that is developing around the topic. But where Sage and QuickBooks are developing AI communication bots and others such as Xero, Receipt Bank and AutoEntry focus on auto-coding transactions, Ai Auditor digs into the realms of big data and pattern recognition, where automation offers a natural fit with the analytic tasks involved with audit work.
The software learns over time what a normal transaction looks like and uses the underlying model to assign a risk score to each transactions so that it can bring forward the ones that deserve the most attention.
“Audit is an obvious application for AI. It can look at the entire data set, not just a sample, and it can search for patterns. You can also nudge it to search out of norm exceptions for further investigation. By narrowing down the audit to those exceptions, it’s much more thorough at that first level,” Gregory explained.
Ai Auditor is the first of several AI products IRIS is promising. The use cases for AI in accounting are “falling off the page”, Gregory said, and is involved in a number of conversations with other prospective partners. IRIS is also doing development work of its own in some of these areas.
“Accountants can’t compromise accuracy, so the volume of data they are having to handle is becoming unwelcome. AI can assist in a number of areas such as complex tax calculations or where rules need to refer to different scenarios, such as the circumstances that might apply to a client with a company car. That’s a perfect question to ask AI,” he said.
Another possibility would be to get AI to run checks on accounts before submission to ensure all the correct rules have been applied. According to Gregory, “AI can become the accountant’s best friend when it comes to looking at exceptions, edge cases and the data behind the data.”
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