The Popular Use Cases of Artificial Intelligence in BFSI

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AI has revolutionized every industry and has changed the way businesses function. Everyone is finding ways to adopt AI into their work. Similarly, the banking, financial services, and insurance sector is also looking to integrate AI into their business and one major reason for doing that is the security of customers.

Customers expect banks to deliver flawless experiences and improve methods of interaction. In the last few years, banks have faced a rise in security threats which is why the banks had to come up with new ways of tightening the security because they were starting to lose clients.

A global study indicates that 85% of respondents have already implemented AI within their organizations and expect to use AI in the new use cases that come and 77% of respondents are anticipating the use of AI processes in their business in the next 2 years.

How is AI strengthening the competitiveness of banks?

Artificial Intelligence and machine learning is the future of banking as it has the power to combat fraudulent activities and improve customer service. Here are some examples of what changes AI has brought about in the banking industry –

  1. Mobile banking – Mobile apps are becoming more advanced and personalized. Banks can generate more revenue with mobile banking services than they generate from customers visiting the branches. This has also saved a lot of time for consumers and improved the quality of services provided.
  2. AI chatbots – In banking, chatbots are used to create an interactive experience for the customers. Bots can communicate with the customers and solve their queries while staying within reason and following the rules. Chatbots can also work 24 hours a day without breaks, which increases the productivity of the banks.
  3. Enhanced security – With the unlimited amount of personal data that is digitized and the number of digital frauds that are happening, it is customary for the banks to keep the client’s money and confidential information safe, and AI helps with that. They have come up with cybersecurity measures like fingerprints, iris, and voice recognition. These measures are almost impossible to forge, therefore everything is safe.
  4. Conformity – It is important to regulate data constantly. There are different processes like “Know Your Customer (KYC)” or “Anti Money Laundering (AML)” that can gather data and transactions digitally, which makes the work faster and easier. If done manually, this process can take up a lot of time. AI algorithms can integrate data very accurately and efficiently.
  5. Financial evaluation – Banks usually earn their profits through the interest they receive on loans. To keep a check that the loans are given back on time with proper interest, they have machine learning algorithms that analyze millions of data and assess whether the client is a risk or not, and then come up with a decision.

Conclusion

People are looking for exceptional services at the click of a button, they don’t want to wait for days for a transaction or money transfer. AI is not only the future of banking, it is also the present. It is advised that all financial institutions start investing in AI right now so that they can optimize their services. With the help of AI certification that is offered by AI and machine learning courses, people can make this revolutionary change in their businesses.

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