Читать книгу Enterprise AI For Dummies - Zachary Jarvinen - Страница 59

The finance sector is blessed, or cursed, with both a super-abundance of paperwork and a surplus of regulation. I say “blessed” because the structured nature of the data and tightly defined rules create the perfect environment for an AI intervention.

Credit worthiness: AI can process customer data, such as credit history, social media pages, and other unstructured data, and make recommendations regarding loan applications.

Fraud prevention: AI can monitor transactions to detect anomalies and flag them for review.

Risk avoidance and mitigation: AI can review financial histories and the market to assess investment risks that can then be addressed and resolved.

Regulatory compliance: AI can be used to develop a framework to help ensure that regulatory requirements and rules are met and followed. Through machine learning, these systems can be programmed with regulations and rules to serve as a watchdog to help spot transactions that fail to adhere to set regulatory practices and procedures. This helps ensure real-time automated transaction monitoring to ensure proper compliance with established rules and regulations.

Intelligent recommendations: AI can mine not just a consumer’s past online activity, credit score, and demographic profile, but also behavior patterns of similar customers, retail partners’ purchase histories — even the unstructured data of a customer’s social media posts or comments they’ve made in customer support chats, to deliver highly-targeted offers.