Artificial Intelligence (AI) is transforming the financial sector, revolutionizing how banks, financial institutions and investors operate. Here are nine examples of AI in finance, and how they are changing the industry:
Fraud detection
AI algorithms can analyze transactions in real time, detect anomalies and patterns that may indicate fraudulent activities, and alert banks to take appropriate actions. An example of fraud detection using AI is PayPal’s fraud detection system. PayPal uses machine learning algorithms and rule-based systems to monitor real-time transactions, and identify potentially fraudulent activities.
The system examines data points like the user’s location, transaction history, and device information to identify abnormalities and patterns that can hint at fraudulent behavior. The technology can notify PayPal’s fraud investigation team about a possibly fraudulent transaction so that they can look into it further or block the transaction. The amount of fraudulent transactions on the network has dramatically decreased thanks to this AI-powered solution, making using PayPal safer and more secure.
Customer service
AI-powered chatbots can provide personalized financial advice, answer customer queries, and automate routine tasks like opening new accounts or updating customer information.
The chatbot “KAI” from Mastercard, which helps clients with account queries, transaction histories and expenditure tracking, is an example of how AI is being used in customer support. KAI uses machine learning algorithms and natural language processing to offer consumers tailored help and financial insights across a variety of channels, including SMS, WhatsApp, and Messenger.
brandchannel: Mastercard Grows Its Brand with New Personal Finance Chatbot KAI https://t.co/Mz3vPoDSJm pic.twitter.com/1zizdGgUac
— Muzaffaruddin Alvi (@Muzaffar69) October 25, 2016
Algorithmic trading
AI can accurately assess past and present market trends, spot patterns, and predict future prices. AI algorithms can also perform transactions in real time, using pre-programmed rules and conditions, optimizing investing strategies and maximizing returns.
Financial institutions and investors benefit significantly from this technology, which enables them to make data-driven decisions and maintain an advantage in the fiercely competitive world of trading.
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Risk management
By analyzing complex financial…
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