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Use Cases for AI in Finance

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    data management best practices for optimal performance

    Artificial intelligence (AI) is currently being utilized across the entire spectrum, helps to improve efficiency, consolidate information and data, and detect anomalous behavior. However, AI is especially beneficial in the finance sector, where it’s transforming everything from financial planning to loan underwriting to fraud prevention and more.

    AI is most commonly used in finance to automate repetitive high-frequency, high-frequency tasks. This reduces human errors and allows for resources be allocated to other strategic actions. Automating processes with robotics can, for instance, reduce costs and manual data entry by up to 50% to 70 percent. AI can help accelerate market research, forecast investment growth and assess risks by identifying anomalies and advising users with real-time alerts.

    Other applications for AI in finance include preventing cyberattacks and financial crimes. Fraudulent transactions cost billions of dollars each year. AI can help identify suspicious patterns in large databases. AI can detect fraudulent transactions by using deep learning and other sophisticated algorithm. For example, when a car loan request is found to be out of compliance with the company’s policies.

    AI is also a vital component in providing 24/7 support for customers, assisting them with financial services through voice and chatbots. AI-powered virtual assistants let customers to access account information, look up the history of transactions, and gain specific insights by asking simple questions using natural language. Moreover, these assistants can offer personalized and proactive recommendations regarding additional savings or investments or insurance.

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