Searching for Clues
After the long work of closing your books is complete, it’s still not quite time to hang up your hat. Before auditors come knocking, there is still an opportunity to detect residual risk post-close. However, the financial team has been over these balance sheets over and over again, how could they find anything new? Since there is always a risk of human error, this is where machine learning, specifically Artificial Intelligence (AI), comes into play. To that end, we will cover three ways the office of finance can benefit from implementing AI-backed detective controls after the period-end close.
According to a recent survey by the Association of Certified Fraud Examiners (ACFE), a typical organization can expect to lose 5% of their revenue every year as a result of fraud.1 However, according to PwC’s 2018 Global Economic Crime and Fraud Survey, “Only 49% of surveyed global organizations said they’d been a victim of fraud and economic crime.”2
Between the theft itself and secondary damages such as investigations and other interventions, the overall cost of a fraud incident is high. However, that cost often isn’t large enough to justify an average loss of 5% of the overall revenue for an average organization if less than half of companies are victims. PwC suggests that the reasoning behind this apparent conflicting data is that the other 51% of corporate organizations are blissfully unaware of their fraud issues.
1.Take Control of Prevention
While every organization faces its own industry-specific risk, fraud risk is universally faced by all businesses and entities. From asset misappropriation to financial statement fraud, over the past few years, there’s been an overall increase in the total amount of economic crime.3 Furthermore, to make matters worse, today’s senior financial executives have more data than ever to process and review accurately. In response to these obstacles, and due to the most prominent organizational weakness that contributes to fraud being an overall lack of controls, organizations have heavily invested in fraud prevention measures.4
While there are several types of anti-fraud controls, such as surprise audits or a reward system for whistleblowers, implementing a code of conduct and independent audits have become the most common methods of fraud prevention within organizations.5 And on the surface, this makes sense; after all, codes of conduct are easily implemented, and third-party audits are impartial.
However, both of these controls have glaring issues. The study by ACFE found that independent audits, while nice on paper, are not explicitly designed to find fraud, and in their study, those audits were responsible for detecting less than 4% of the total amount of fraud. Additionally, implementing a code of conduct is considered a “passive detection method” or a type of method in which the organization discovers fraud by accident, confession or unsolicited notification by another party. When fraud is uncovered through a passive method, as opposed to an active method in which there is a deliberate search, such as data analytics, both the median loss and duration of the schemes increased by as much as 400%.6
Therefore, in order to effectively combat the growing amount of economic crime, organizations need a tool that not only actively searches for fraud but is designed for the specific threats that the office of finance faces.
2.Remove a Manual Burden
While passive detection methods are not adequate for fraud prevention, detective controls are more inclusive. When the AI-powered tool is connected to your financial data, it provides benefits beyond just fraud discovery.
A detective system analyzes 100% of all datasets, such as General Ledger transactions, in order to improve internal audit functions. When fraud reviews are completed manually, it is time and cost-prohibitive to review every single transaction or posting.
Removing this burden from the financial team, especially in the crush at month-end, allows them to better prepare for audits and even work on other tasks. For the items that an AI tool uncovers requiring human intervention for an in-depth analysis, the team will be able to focus on those tasks. The office of finance needs technology that will support an automated financial close process.
3. Gain Insights to Risk
Today, Artificial Intelligence can play a powerful role in analyzing financial data, identifying insights and ultimately removing risks in the balance sheet. Specifically, Risk Intelligent Inspect by Trintech utilizes Financial Controls AI™, a type of Artificial Intelligence developed specifically for the complex needs of the office of finance and identify errors and anomalies. For each transaction, Risk Intelligent Inspect provides a risk rating and supporting analysis to help users quickly investigate and mitigate any issues.
Additionally, the solution’s machine learning capabilities enable even deeper, more predictive insights over time. Risk Intelligent Inspect vastly improves an organization’s ability to identify fraud and validate controls in a way that simply cannot be done manually or through basic automation of the financial close.
To learn more about how Risk Intelligent Inspect can help your organization overcome key challenges in variance analysis and risk management, check out our webpage.
Written by: Caleb Walter
1 ACFE (2016), “Report to the nations on occupational fraud and abuse” Retrieved November 7, ACFE
2 PWC (2018), “ PwC’s 2018 Global Economic Crime and Fraud Survey” Retrieved November 7, PWC
3 Volkov, Michael (2018), “The Growing Problem of Corporate Fraud” Retrieved November 7, Corporate Compliance Insights
4 ACFE (2016), “Report to the nations on occupational fraud and abuse” Retrieved November 7, ACFE
5 ACFE (2018), “Report to the nations 2019 global study on occupational fraud and abuse” Retrieved November 7, ACFE
6 ACFE (2018), “Report to the nations 2019 global study on occupational fraud and abuse” Retrieved November 7, ACFE