Understand FinTech software with an AI TutorBot

Trading software comes in many forms, from simple buy/sell at the push of a button packages to navigating crypto markets and the significantly more complex algorithms involved in predictions – minutes, hours or even days ahead.

When trading stocks, a few seconds of delay can mean a potentially significant loss, so it’s important that software operators can be as fluent on their workstation keyboards as a virtuoso pianist playing a Bach prelude. Now imagine if the pianist’s notes suddenly changed. He is used to playing a certain part of a piece with his eyes closed, but suddenly he hesitates and loses his flow. For the musician, it’s a little embarrassing and inconvenient, but for a financial trader, the same workflow error is costly.

Fortunately, artificial intelligence (AI) comes to the rescue, in the form of a TutorBot, a “learning layer” of software that runs alongside the primary platform it’s assigned to, offering help to the human operator if they run into problems. It is what is known as a digital adoption platform or DAP.

Switch places

DAPs are likely to become one of the most funded fintech software models in the world very soon, as they can remove inefficiencies in business processes, especially in larger organizations using an enterprise-wide CRM or on trading floors when hesitation caused by software updates can cause significant losses. Also think how much business must be lost daily to accommodation sourcing platforms like Airbnb or flight finders like Skyscanner, when customers can’t understand the technology and go to another site they may find less complicated to navigate.

For example, in the workplace, let’s imagine a sales office using the fictitious Acme Widget Inc CRM to enter sales numbers and orders into the system.

Our clerk may be a new hire, in which case they have to learn CRM from scratch, or may be an experienced operator who suddenly faces a change in workflow due to an update in the system’s UX. As for the beginner, they are bound to struggle from the very beginning. Of course, if they’re in a large, open-plan office environment and the input screen won’t accept their numbers, they can always head over to a colleague’s desk and ask for help. But they can only do it so many times before they appear to colleagues as a pain in the neck – so some newbies may take shortcuts and put anything on their screen just to hide their embarrassment.

A personal AI assistant

DAP changes all that. It’s hyper-personalization, powered by AI, treats every employee on a one-to-one basis, like a friendly, knowledgeable colleague sitting over your shoulder, but it only intervenes if you ask, or proactively if it expects you to going to struggle. It is this proactivity and analysis of an operator’s approach to their workflow that is the key to people learning new software so quickly when using a DAP.

The AI ​​will detect when the employee first makes a mistake and can offer a “tooltip” to help the person solve the problem — something like “Sarah, two decimal places are required to enter this field” or whatever. If the employee makes the same mistake again in the same place in the next workflow session, the AI ​​remembers this and the next time the operator goes into the next screen, it is decisive for they make the same mistake, DAP will offer proactive help: ‘Sarah, on the next screen remember to use two decimal places in your input…’. After a few sessions, the human operator will learn that screen X needs a specific input format and will stop making the same mistake; likewise, the AI ​​will have learned that the operator has learned, so will no longer offer questions if they would be unnecessary and distracting. The ability to be able to do this for all employees in a large organization, regardless of which workstation they may be logged on to, allows for much faster adoption of changed workflows due to software changes or updates.

The next gold rush for fintech startups?

Of course, DAPs are not limited to Enterprise-wide Software as a Service (SaaS) platforms such as payment software or CRM systems. There’s no reason why a DAP can’t be installed on a standalone laptop, tablet or even a mobile phone. The net result is the same, whenever an operator encounters problems achieving something on the device they’re using, a DAP can jump in to the rescue – whether it’s grandpa struggling with his laptop, an art and design student getting hold of a photo editing suite or a consulting surgeon using MedTech for patient diagnosis.

It won’t be long before all software has a DAP running alongside it, whether it appears as a metaverse avatar or a simple text that pops up on the screen, it’s going to make life a lot easier for anyone who uses technology. When it comes to FinTech startup funding and navigating the complex regulations of the banking world, it is very likely the beginning of the next techno gold rush.

Connect the wagons, friends…