Читать книгу Enterprise AI For Dummies - Zachary Jarvinen - Страница 54

Anyone who has seen It’s a Wonderful Life remembers how nervous everyone became when the bank examiner showed up at Bailey Building and Loan. He walked in with a briefcase and spent hours going over financial statements. These days, he might show up with a laptop and a scanner and let the algorithms process the paperwork and identify anomalies and violations of federal and state regulations.

As a field that is driven by well-defined practices, structured data, and pro forma documents and reports, the finance sector is well aligned for automation, and in light of the financial crises of 2000 and 2008, the emergence of practical AI is timely. The “2018 AFCE Global Study on Occupational Fraud and Abuse” reported a loss of $7 billion due to fraud in 2018 alone.

Recent approaches to fraud prevention use a range of AI tools, including data mining, supervised and unsupervised machine learning, behavioral analysis, link analysis, regression, decision trees, neural networks, and Bayesian networks.

Over the past five decades, AI has evolved from offering lightweight consumer applications or add-ons to supplementing and performing mission-critical and even life-or-death functions. The next sections introduce some of the ways AI is changing the landscape for the enterprise.