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Three Benefits of AI and ML in Banking and Finance
Predictive data analysis will be offered by applying AI and ML as banks and financial institutions try to provide better services with more actionable information such as patterned customer behavior and spending behavior data sets.
Fremont, CA: With the growing risk management challenges alongside increasing governance and regulatory conditions in the banking industry, banks need to develop their services for more specific and better customer service. In various applications across several channels, Fintech brands are increasingly applying artificial intelligence (AI) and machine learning (ML) to utilize all available customer data to predict how the requirements of customers are evolving. And they are also speculating about what services will be useful for them, what kind of fraudulent activity is most likely to attack the systems of customers. In banking, AI and ML, along with data science acceleration, are needed to improve customers' portfolio offerings.
Here are three benefits of AI and ML in banking and finance:
Functionality of Chatbots
For both clients and banks, the ability to recognize the user's past behavior and craft targeted campaigns is a blessing. Such a customized campaign generates all the customer's necessary information when making it and saves both time and energy. Customers of today also enjoy services that are customized according to their preferences and improve their banking experience.
Preventing Fraudulent Activities
Banks have had to violate some pre-set guidelines during the traditional process to prevent users from fraudulent transactions. Even before the external threat violates the customer's account, advances in machine learning can sense suspicious activity. The fundamental advantage of this is that machines are capable of performing real-time, high-level analysis, which is impossible for humans to perform manually.