Ai in mobile banking

Artificial intelligence is meant to copy human behavior and start mimicking human task performance. It is getting more and more popular in all business spheres, and the financial sphere is not an exception. Leading businesses in this field realize they can cut most of their expenses introducing AI (Artificial intelligence) to their service delivery procedures. User needs are met doing extensive research in the field of User Experience, yet this does not provide an individual approach to customer needs. On the other hand, AI has the potential to draw patterns from individual experiences. The international banking system has long adopted AI tools in their systems, and AI has proven to be utmost efficient in mobile banking. Here is how AI can be used in mobile banking.

AI is great for mobile app personalization. Personalized approach provides users with multiple possibilities to have a better experience while using a mobile application. Personalized chatbots are an example of improved real-time transaction experience. While on a call with a call-center operator the user has to navigate in the application on another device and follow the operator’s instructions. Chatbot can provide the user with necessary links to follow, so the user doesn’t need to leave the application to get support.

AI can notify users about products they specifically are interested in. While the usual marketing strategy is to let users know about all new products available, AI can draw preference patterns and notify users on only those products they specifically will be interested in. Making financial decisions is another important aspect AI can be useful for. It gives investment strategy tips based on user’s earnings, liabilities, investments, contingency, insurance, risk and other factors. One of the most important privileges of AI is that it eliminates possible human bias. All the recommendations and tips that AI gives to the user are driven from rough calculations of trends or behavioral patterns. The human factor is cast out which gives the user more objectivity. AI also sends users reminders on their payment dates. This helps with upcoming expenses or bill payment reminders, allowing people to remain within budget.

Finally, AI biometric systems can be used for security purposes. Face recognition is one way of identifying the user. It works through identifying algorithms of separate parts of a user’s face. For example, AI can calculate the distance between the eyes, or the depth of eye sockets. AI can secure the app through speaker’s voice recognition. Voice recognition includes physical characteristics like the shape of the vocal tract responsible for articulating and controlling speech production. Minutiae, specific features of a fingerprint, are used for fingerprint recognition. A sufficient number of minutiae will decide whether the user is recognized by the system or not.

Most interestingly, behavioral biometrics can also help identify a user. It identifies human activities, for example, accidentally hitting an “ s” instead of a “ d” on three out of every six transaction. This is used for advances security purposes and can be considered to be an additional security layer. Having said all of the above, it’s no wonder more and more financial and particularly banking companies adopt AI solutions for their mobile applications. These solutions are simple yet they solve many everyday user issues and best meet user needs where human intervention is limited or not possible.