Trading software takes many forms, from simple buy/ sell at the push of a button packages to navigating crypto markets and the considerably more complex algorithms involved in predictions – minutes, hours or even days ahead.
When trading in stocks, a few seconds lag can mean a potential significant loss, so it’s important that software operators can be as fluent on their workstation keyboards as a virtuoso pianist plays a Bach prelude. Now imagine if the pianist’s sheet music suddenly changed. He’s accustomed to playing a particular section of a piece with his eyes closed, but suddenly he hesitates and loses the flow. For the musician, that’s slightly embarrassing and inconvenient, but the same workflow glitch for a financial trader gets expensive.
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 to which it’s assigned, offering help to the human operator if they encounter difficulty. It’s what’s known as a digital adoption platform or DAP.
Trading places
DAPs are likely to become one the most funded fintech software models in the world pretty soon, as they can remove inefficiencies in business processes, especially in larger organizations using an enterprise-wide CRM or on trading floors when any hesitancy caused by software updates could cause significant losses. Think also about how much business must be lost daily by accommodation sourcing platforms like Airbnb or flight finders like Skyscanner, when customers can’t understand the tech and go to another site they might find less complex to navigate.
By way of example in the workplace, let’s imagine a sales ledger clerk using the fictional Acme Widget Inc CRM to input sales figures and orders fulfilled into the system.
Our clerk might be a new hire, in which case they must learn the CRM from scratch, or might be a seasoned operative who suddenly encounters a workflow change due to an update in the system’s UX. In the case of the rookie employee, they’re bound to struggle from the very outset. Naturally, if they’re in a large open-plan office environment and the input screen won’t accept their figures, they can always walk across to a co-worker’s desk and ask for help. But they can only do that so many times before appearing to co-workers as a pain in the neck – so some newbies can take shortcuts and enter anything onto their screens just to hide their embarrassment.
An AI personal assistant
The DAP changes all this. It’s hyper-personalization, powered by AI, treats every employee on a one-to-one basis, like a friendly, knowledgeable colleague sitting at your shoulder, but it only interjects if you ask, or proactively if it anticipates you are going to struggle. It is this proactivity and the analysis of an operator’s approach to their workflow which is key to having humans learn new software so quickly when using a DAP.
The AI will detect when the employee first makes a mistake and might offer a ‘tooltip’ prompt to help the person solve the problem – something like ‘Sarah, two decimal places are required to input into 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 operative is about to enter the subsequent screen, crucially before they make the same mistake, the DAP will offer proactive help: ‘Sarah, please remember on the next screen to use two decimal places in your input…’. After a few sessions, the human operative will learn that screen X needs a certain 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 prompts if they would be unnecessary and distracting. The facility to be able to do this for every employee in a large organization, irrespective of whatever workstation they may be logged into, makes for much faster adoption of changed workflows due to software changes or updates.
The next gold rush for fintech startups?
Of course, DAPs aren’t limited to enterprise-wide Software as a Service (SaaS) platforms like payment software or CRM systems. There’s no reason why a DAP can’t be installed onto a stand-alone laptop, tablet or even a mobile phone. The net result is the same, whenever an operator encounters difficulty in 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 to grips with a photo editing package or a consultant surgeon using MedTech for patient diagnostics.
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 pop up on the screen , it’s going to make life a lot easier with anyone who uses technology. In terms of FinTech start-up funding and navigating the complex regulations of the banking world, it’s highly likely to be the beginning of the next techno gold rush.
Hitch up your wagons, friends…