2019 Banking Trends: How AI and Big Data are Transforming the Industry

You might not be aware, but AI is capable of verifying the individual swiping the card. Significant effort has been dedicated to the creation of systems that can detect suspicious transactions, disabling fraudulent ones immediately before any damage is incurred by the user. All of the technology you own will soon “go smart”, and banking and financial services will be leading this disruption.

Banks can benefit from the use of AI and big data in multiple ways, such as greater personalization of products, tailored financial advice, automation of certain operational processes and the subsequent lowering of costs. Below, we have assessed the most probable directions in which AI and big data will influence the banking industry this year.

1. Personalized Wealth Management Advice

A 2018 Retail Banking Advice Study by J.D. Power’s estimated that 78% of consumers would like to receive financial advice from their bank, yet it is only 28% that actually do. The field of wealth management has undergone dramatic changes in the recent couple of years, which was mainly driven by changing customer needs. The most common directions that interest individuals looking for financial advice are retirement, investment, expenses management and saving opportunities. With the help of AI and precise analysis of big amounts of unstructured data banks can be quite successful in all of the above. Wells Fargo, for instance, gives its customers an opportunity to take full control over personal finances management, receiving alerts about upcoming payments and monitoring the spending activity. The Royal Bank of Canada has also been quite successful in terms of providing personalized financial experience. Banks have finally stopped to underestimate the implications of refusing to integrate innovative technologies in response to growing client needs and are currently discovering all the ways in which AI and big data can help them stay on track.

2. Fraud Prevention and Improved Cybersecurity

Banks lose billions each year in result of non-prevented fraudulent activities. AI and machine learning mechanisms can be applied to train systems to detect potential fraud, which will be beneficial for both, banks and their customers. The technology, in fact, has been around for a while now and keeps being upgraded. The only important step to proceed with is taking advantage of what is already out there. In a nutshell, programs based on deep learning strategies can be applied to detect the types of transactions that are unusual for specific customers. Algorithms that use deep neural networks mechanisms can already be successfully used to fight online fraud and cybercrime. They basically duplicate human thought process, which gives you an idea about their limitless capabilities.

3. Higher Personalization of Customer Experience

The level of customer’s convenience, although not a very concerning matter for banks before, is currently a true competitive battlefield. Numerous customers are, however, still unaware of the underlying bank policies, terms and conditions and all the other processes going on inside a bank. This will not be accepted any longer given the active regulatory environment. AI and big data can be quite helpful in resolving any issues that come along for banks. With the help of the latter banks can provide their customers a high-quality digital banking experience at a non-significant cost. For example, they can integrate or develop in-house technologies that will analyze customer spending patterns and generate insights about their banking behavior. This way, there is a higher chance they will receive personalized products and solutions.

4. Better Customer Service

It is quite challenging to imagine a fast resolution of an issue with your bank through your mobile device. It is much more likely you will end up having to pay a personal visit. With the help of AI banks have a chance to automate various tasks and expand the range of self-service solutions, decreasing the personal involvement of banks personal when possible. This will not only make things faster and more efficient but will also save many pennies to the bank.

It is hard to stay away from the overall excitement and hype around intelligent algorithms and their accomplishments. There is no doubt that in the nearest future banks will put significant effort into adopting more AI and machine learning-based technologies in order to improve their operation and competitiveness.