I have lead, architected and developed consumer facing applications, especially in Financial sector, for a long time and have seen a lot of evolution.
Current state of things
The movement towards designing UX with what the customer is likely looking to achieve is the right track. There has been a lot of design innovations towards this.
One of the primary approaches that is used today is to have a sort of landing page / dashboard with the summary of various information and then the most common links that are easy to access. Some times the links are deep links into other parts of the application.
This works ok for most parts. But the experience could be even better and here is some thoughts on where it might be heading, specifically powered by AI insights.
Understanding what the user wants
The holy grail of best UX would be if we can know what any user is looking to achieve and take them to the right place and present them with the right information and/or tools. This of course will be different for each user and each time they login.
Sometimes, it might be check balance, sometimes to pay a bill, sometimes to deposit a check, sometimes to check on a alert, sometimes to look for a new product, sometimes to find help from support… There are a lot of possibilities.
Here is where AI could help.
Financial institutions typically have access to a lot of data about their users, especially existing users. This could range from transaction history including metadata about transactions such as time, location, price range etc. Also past patterns of login activity, spending activity, recent transaction types/categories and much more.
Applying AI to analyze these sets of data could then be used come up predictions with degrees of confidence on what the user’s intention might be. These predictions can then be used to present a customized UX to the user.
Once a determination has been made by the system regarding the likely intent of the user, then a UX can be presented that will help the user achieve their intended goal with minimal effort. This could include showing the right information, taking them directly to a particular page etc.
For example, if based on past activity, it is determined that the user is likely going to do a paycheck deposit, then take them to mobile deposit. Another one, if based on recent transactions analysis, it is determined user could be planning a upcoming travel, ask about travel notification setting etc
These are just a couple of example but the options could be pretty varied.
Executive / Product Management – The first challenge is for product management to realize the potential with this sort of personalized UX approach. The areas of application to be determined and initiated
AI – The data is there. Once a determination has been made, then the AI engineers can start working with the business data owners to understand and work on creating outcomes and building the prediction engine.
UX Designers – UX design in these sectors (Finance, Utilities etc) are relatively static. The UX designers need to start thinking of how to create flexible UX that could take advantage of the predictions from AI and present seamless experience to users.
Developers / Tools – The frontend and backend developers also have to work through to evolve libraries and technologies that would facilitate the development of these dynamic UI structures and the varying data requirements for these.
I have already heard of some organizations starting to work towards these goals. If done right, this could drive up user engagement and satisfaction significantly. I am very interested to see how this evolves and how our experiences would transform.