{"id":541,"date":"2023-03-25T11:36:23","date_gmt":"2023-03-25T11:36:23","guid":{"rendered":"https:\/\/solonangel.com\/?p=541"},"modified":"2024-02-15T14:43:06","modified_gmt":"2024-02-15T14:43:06","slug":"unconventional-thinking-for-success-with-solon-angel","status":"publish","type":"post","link":"https:\/\/solonangel.com\/unconventional-thinking-for-success-with-solon-angel\/","title":{"rendered":"Press: How AI Could Protect Your Business From Financial Fraud"},"content":{"rendered":"\n
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A milestone in the fight against corruption and corporate crime has been reached.<\/p>\n\n\n\n

Artificial intelligence (AI) has been making a big difference in nearly every industry and is changing all of our lives on a personal level, but to date, it hasn\u2019t curbed sophisticated white-collar crime. In this article, we will cover the world\u2019s first known case of an AI-enhanced investigation by a California audit services firm as it uncovered a real human CPA, a controller, committing over $2.8 million in fraudulent transactions. Not only will this change how accounting works, but it may also start restoring confidence in the profession and our financial institutions.<\/p>\n\n\n\n

Why does this matter? Fraud has been and will continue to be a massive drain on the world\u2019s economy, with us as citizens bearing the brunt of its effects. According to the Association of Certified Fraud Examiners\u2019 (ACFE) \u201cReport to the Nations<\/a>\u201d (download required), the potential total global loss caused by fraud is approaching an estimated $4 trillion. There are many AI and machine learning solutions for high-volume, low-amount fraud problems, but while corporate white-collar crimes (financial statement fraud) are the least common cases, they are also the costliest. This means that the bulk of the problem has been left unresolved, and AI is the only realistic and proven technology to help clean this up by doing the impossible: processing, understanding and reporting on never-before-seen insights into our double-entry economy in seconds.<\/p>\n\n\n\n

California audit services firm Gursey Schneider LLP used AI-enhanced audit tools<\/a> to process and understand a massive amount of client data and extract insights with enough evidence to move forward with a $2.8 million criminal fraud case. This type of analysis of over six million transaction records would be impossible with traditional tools such as Microsoft Excel, computer-assisted accounting tools (CAAT) or robotic process automation (RPA), but it falls right within the sweet spot of the capacity and speed of AI. Its potential to ingest vast amounts of information \u2014 a must in today\u2019s big data world \u2014 and understand the details of what\u2019s going on under the hood far surpasses anything that older methods can accomplish. To date, only a few of the Big Four have had the opportunity to invest in and explore the possibilities of AI, but there are no known reported cases of them having this type of success. With the democratization of AI and surge of venture capital, we\u2019re seeing the advent of a new class of solutions.<\/p>\n\n\n\n

Yet this doesn\u2019t mean that accountants, auditors, fraud and forensics experts, or any finance professionals should fear for their jobs. Rather, it\u2019s the opposite. While AI can take 100% of the data and identify the suspect transactions, it still requires human context and intuition and client understanding to pull it all together and report to the client. In fact, Gursey has seen the perceived value of services they deliver reinforced thanks to this engagement.<\/p>\n\n\n\n

With today\u2019s challenges in the amount and complexity of data, and increasing scrutiny by regulators, firms must set a road map to AI for themselves. Given that 42% of fraudsters committed their acts by creating fraudulent transactions in accounting systems, it\u2019s the only method capable of detecting schemes. How does AI help? The biggest advantage over traditional methods is that it unlocks anomalies and rare occurrences hidden in the deep mountains of data, where no human could possibly have the time or energy to inspect. AI does not necessarily flag instances of fraud directly\u00a0\u2014 it still takes a human\u2019s intuition and experience to make the final judgment call\u00a0\u2014 but it does identify related patterns of activity across the full data set and calls out:<\/p>\n\n\n\n