Blockchain, machine learning, artificial intelligence, automation, natural language processing … the world is full of big predictions around the transformative impacts these technologies may have in the coming years. Although many assume these are on the distant horizon, we often forget that these are tools being put into MVP, pilot and practice across industries today. At ATB, one of our explorations into the combination of AI, Blockchain and automation is our application EVA, that has been deployed for more than 6 months across the organization.
EVA (Easy Voice Autonomation) is one of the most nimble and effective projects related to AI, blockchain, and automation, and has the ability to exponentially transform banking. EVA is currently being leveraged within ATB to help us with our commitment to listen to our customers. Based on this commitment, we are focusing on improving the customer transactions experience that has resulted in negative feedback due to mistakes being made or the time taken to complete the task. We’re also taking an “inside out” approach with EVA, by experimenting with EVA internally and gaining feedback from our team members prior to making it directly available to customers.
The blockchain we are using records processes, but not customer data. These processes are recorded where everything is secure and encrypted, as well as restricted by access permissions. This technology was chosen to enable solutions that are open and scalable, while ensuring its not dependent on a singular platform that could prevent us from expanding in the future. We chose to take on the challenges of blockchain to be at the forefront of this technology, exploring how we can use it to do what we do best: serve our customers.
A current use case for EVA is the ability to save team members time and repetitive work when it comes to something as simple as changing an address. Connecting to the Canada Post API ensures the proper format of the address, saving ATB time and money on address remediation that many companies face in their customer records. Team members are able to enter address updates in one place and have that disseminated by the software robots who are fulfilling the request to each individual book of record where the information is required. Be it a customer profile, Mastercard or Investment account, customers can rest assured that all their accounts are updated accordingly.
In the future, the goal is for EVA to anticipate our customers needs and take the onus off the customer for things such as address updates. Observables will allow for people to choose who can see and share their information and allow companies to pre-emptively update requirements when customer share. Imagine not having to call every company with whom you interact to update your address when you move, just simply allow these companies to listen for the updates you choose to share.
The goal of EVA within ATB is to be able to rapidly create solutions that can transform the way we work and ultimately provide better customer service. It is because of this that we’ve also chosen to incorporate natural language processing to better capture, translate, and figure out what the user is trying to accomplish when working with a given solution. The aim is to simplify every day tasks and make us more efficient.
EVA has been embraced by our robotics processing team and they are using EVA to build solutions for team members. As these solutions have been rolled out throughout the organization, it has allowed us to determine what features people inherently use, and which features need prompting, encouragement and education.
EVA allows branches and departments to solution for themselves, as opposed to being dependent on traditional IT departments or software development teams. This “self serve” ability saves time, money and manpower. EVA enables everyone to be part of the solution. We currently have 24 processes deployed internally to our team members that are fulfilled on the backend by our software robots.
The future of EVA could be in a myriad of directions, as what we’ve built is malleable and scalable which allows for future pivots and iterations. We could look at different use case applications within ATB, or even give back to the open source community by sharing knowledge with (and learning from), the incredible developer talent in our own backyard.
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