Innovation Lab
Ideas being explored
Open Data Sets
Killed Ideas
Languages Spoken
Patent Pending
Our Story
Creating growth at the edges
Over the last several decades, digital technologies have changed nearly every aspect of our lives. Since the emergence of web, mobile, and cloud computing, the pace of progress has been accelerating - bringing more powerful technologies sooner than we could imagine.
The next big thing.
Technology has always been a part of our DNA. ATB’s Innovation Lab began in 2018 with a small group of engineers who knew that the convergence of data, artificial intelligence, and decentralized technology would revolutionize the way we live, work, and play. As in the case of all great technology, each has the power to do great good or harm; we’ve already seen how the ubiquity of the internet and mobile has created structural advantages for a powerful few.
Delivering the most trusted experiences.
The extent to which we are able to harness the power of these emerging technologies to create the best outcomes for our customers and society depends on the approach we take today. Grounded in ethics, we know that building products that people love and trust is the only way to deliver sustainable value. At the Lab, we use every day to pursue innovations that will benefit our customers, Alberta, and the World.
How we work
Our Approach.
Our People.
The Innovation Lab is grounded in two equally important but divergent disciplines - invention (R&D) and innovation (commercialization) - breakthrough innovation requires a set of cross cutting practices and processes, focusing on the approach and the people, to thrive.
Invention and innovation.
Our job is to think about life in 2030. We invest time and resources into building products and partnerships that harness emerging trends in data and artificial intelligence.
When we see potential we push hard to commercialize and maximize the opportunity, from ideas to growth.
Even though we are macro optimists, we know there are many important problems to be solved close to home. We never forget that we’re here to keep ATB, Albertans, and Alberta businesses at the forefront of innovation.
One team. A world of opportunity.
People are the driving force behind our success. ATB’s innovation team is small and extremely disciplined. Because we are lean, we’re able to move fast and act decisively. We take pride in excellence, always learning and striving to do our best to serve our customers.
At ATB Innovation, diversity is our competitive advantage. Building meaningful solutions requires passion, endurance, and creative thinking that comes from the range of expertise, work approaches, and life experiences that our team prides itself on.
Imagining our future through the lens of these four major technology trends:
Software has emerged as a critical differentiator for financial services while also powering all aspects of our financial lives. Our ambitions extend beyond core banking business models as we apply data networks and machine learning to all our innovations.
As a thesis-driven innovation lab, ATB Innovation embraces a set of operating principles and perspectives that guide all our decision-making and pioneering activities.
Data
Data-to-everything.
Our health, wealth, and environment are intimately intertwined. How can we leverage network effects to stitch rich data and patterns together to create unique products that enhance how people live, work and play while discovering new business models in the process?
Machine learning
AI systems everywhere.
Today, most of us use some form of narrow AI on a regular basis, like Siri or Google. As we progress towards strong AI, how can we create smarter, more powerful services that augment human intelligence and improve decision making while serving the collective intelligence and well-being of all?
Human-machine interactions
Our digital identities merge with the physical world.
As AI-driven personalization, AR/VR interfaces, and sensored-enabled environments converge, commerce embeds itself deeper into our culture, including within us, acting as moving and breathing data platforms. With constant connectivity providing endless amounts of data, how can we keep consumers firmly in mind and make technology as useful as possible while seamlessly integrating it within their daily lives?
Trust
New era of certainty.
The way businesses are built is changing. Our digitized world requires a fundamental shift of core infrastructure with an increasing focus on trust and identity. How can we ensure tamper-resistant transactions while combating inequities in products and services across financial services and beyond?
Leading with data and research
What is Scenario Planning and Foresight?
Corporate foresight and scenario planning is the discipline of developing the details of various potential future realities so businesses can better react to changes within markets and technologies. Scenario planning works by identifying factors central to changing economies and helps scenario participants recognize and confront their preconceptions related to how they believe the future will unfold. Underlying assumptions critical to the success of scenario planning include: multiple futures are possible; change (also known as “drivers”) can be identified and studied; and the future can be influenced. This methodology can contribute to multiple verticals of an organization such as risk management, corporate development, innovation, and strategy.
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Practical data synthesis
In order to build and maintain customer trust, financial institutions are investing millions of dollars in preserving privacy while experimenting with exponential technology to bring best value to their customers. With rapid advancements in artificial intelligence on all fronts, however, there is a dire need in the financial sector to balance customer privacy with the use of transaction data in training robust machine models. This white paper provides a rationale focused on data privacy and also includes suggested algorithmic recipes related to how transaction data could completely eradicate the use of real customer data. A distinction is drawn between data simulation and synthesis. Two discussed synthesis techniques include a bootstrapping framework featuring dynamic time warping and a hidden Markov model fitted with a stochastic gradient version of the Markov chain Monte Carlo method.
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