Will Artificial Intelligence earn its place in business models of financial institutions?

Will Artificial Intelligence earn its place in business models of financial institutions
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We recently interviewed Ivan Sergienko, Director of Data Science & Analytics at Global Banking & Markets, Scotiabank ahead of the upcoming Chief Analytics Officer, Spring happening on May 2-4, 2017 in Scottsdale, Arizona. In this stimulating interview, we discussed the journey to becoming an analytics leader, the challenges of the role and the place of artificial intelligence (AI) in financial institutions.

 

Corinium: Please tell us about your journey to becoming a data and analytics leader.

Will Artificial Intelligence earn its place in business models of financial institutions

Ivan Sergienko: I started my professional career in Physics research. The computational physics work I did at Oak Ridge National Laboratory proved most useful later in banking.

I joined Risk Management Analytics group at Scotiabank about a year before the financial crisis. The years that followed forever charged the approach to risk management in financial institutions. The industry, our bank included, has built sophisticated risk management models. In my most recent assignment, I was leading a team in charge of counterparty credit risk metrics, calculating which required a Monte-Carlo simulation of thousands of market variables more than 50 years into the future. Which gets one thinking: why wouldn’t we apply the same rigor to forecasting the needs of our customers to serve them better and benefit in the process.

So when the opportunity came up to build a customer analytics modelling team, I was happy to take it.

Corinium: Do you see your role changing/evolving in the next 5 years? If so, how?

Ivan Sergienko: Much buzz about Data Science, Machine Learning, and more recently, Artificial Intelligence may give people a premature impression that these are universal technologies that can be readily applied to nearly every business problem. We are discovering that quite a bit of critical thinking is required in making these statistics-based models work in business applications. Besides, we frequently come across problems that have no ready solutions in academic or industry literature, and therefore require careful research. Which is why many businesses partner with universities these days, Scotiabank included. This is a very positive trend that, I believe, will continue. I think that more research will be done by business organisations themselves to speed up the research cycle and gain competitive advantage. I see the mandate of my group evolving in that direction – from applied data science to research-based frontier development.

Corinium: What are the main objectives for data/analytics within your organisation?

Ivan Sergienko: Our objective is to better serve our customers. Customer focus is one of Scotiabank’s strategic priorities. Learning about our customers is almost exclusively possible through analysis of data that we have about them. Therefore, data analytics is not a luxury. It is pretty much a necessity for the organisation.

Corinium: What is the biggest challenge you face within your role today and how are you looking to tackle it?

Ivan Sergienko: The rate of adoption of analytic solutions is not quite where we want it to be. Increasing that rate will require efforts on both sides: teams producing analytics should make every effort to make their models relevant to the business, and business leaders should be willing to experiment with new ways of creating value. Innovation is a lot easier said than done when one has to produce tangible results and meet their KPIs.

Corinium: What do you feel is the biggest challenge faced by the analytics/big data industry currently and in what ways does this affect your business?

Ivan Sergienko: There is a risk for the data industry to become a victim of its own success. The hype has raised expectations very high, and now the data science community needs to deliver. This may be difficult without deep understanding of the business domain and statistical principles of advanced algorithms such as deep learning (pun intended). Financial industry is quickly becoming one of the industries driven by algorithms, so the above applies fully.

Corinium: Where do you see being the biggest area of investment in analytics within your industry over the next 12 months?

Ivan Sergienko: Artificial Intelligence seems set to be a big story in Finance over the next year and beyond. It remains to be seen which flavours of AI technology will earn their place in business models of financial institutions. For example, natural language processing promises large efficiency gains. Leading financial companies have been exploring AI and will continue to do so over the near future.

Corinium: If you could have one piece of technology which would revolutionise you and/or your department’s activities, what would it be? It could be something that already exists, or not.

Ivan Sergienko: Well, getting my hands on a quantum computer would definitely be an exciting experience. But, seriously, with so much fascination on technology in the past couple of decades, we have somewhat lost focus on humanity. We often say these days that data is the most valuable asset a business has, and it is quite correct. No less important, though, are the people who work for the organisation. I work with an incredible team of human beings who are talented in many ways and have integrity. My biggest desire is to have more of that.

Corinium: What is your ultimate goal as a data and analytics leader?

Ivan Sergienko: “Ultimate” sounds limiting. Aristotle said “life requires movement”. I prefer to set achievable goals. And then, there is still always something new and exciting to explore. As a mid-term goal, I’d love to build a research practice focused on exploring the frontier of business innovation, as mentioned above.

Hear Ivan speak at the Chief Analytics Officer, Spring event on May 2-4 in Scottsdale You can register for the event HERE.

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