Digital transformation for customer communications

Introduction

Expert Insights – Paul Barter on Trends Shaping the Future of Finance, Part 2

Today, I’m sharing more insights from my chat with futurist Paul Barter about the future of community finance. For those just tuning in – Paul is a technology strategy, research and innovation executive with over 30 years of experience in the technology product and services sector. He also teaches Technology Strategy to MBA students, acts as a Venture Services Advisor at MaRS and writes extensively about the intersection of technology and society. You can find the first part of our interview here.

Expert Insights – Paul Barter on Trends Shaping the Future of Finance, Part 2

Today, I’m sharing more insights from my chat with futurist Paul Barter about the future of community finance. For those just tuning in – Paul is a technology strategy, research and innovation executive with over 30 years of experience in the technology product and services sector. He also teaches Technology Strategy to MBA students, acts as a Venture Services Advisor at MaRS and writes extensively about the intersection of technology and society. You can find the first part of our interview here.


By Olga Zakharenkava

Having set the stage for our discussion about the future of banking, Paul shared why banks and credit unions need volume, velocity and variety in their data, how the sector is changing, and why these particular institutions are positioned to gain market share with Millennials – if they make the right moves with their data now. Here are some highlights of our conversation:

Olga Z.: What types of data are the most underused by financial institutions?

Paul Barter: When thinking about data, banks and credit unions need to focus big data and its defining characteristics of volume, velocity and variety. Here’s how that works:

Volume: You’ve always had numeric data, but now you have more of it. Use it, every time you are making decisions.

Velocity: Your data is coming in faster. You’ll need to make differentiated decisions based on instant information. This means rethinking how you access data. Most financial institutions have built a system based on structured query language (SQL). Those are useful, but there’s much more out there.

Variety: Much of today’s available data is unstructured and not numerical. It may consist of video, audio, social media texts or many other things. Learn how to leverage this data in addition to the traditional numerical data you already use.

Artificial Intelligence or Machine Learning systems need data and lots of it, and I perceive them as the banking technology of the future. So to get ready for that, I’d suggest you increase the volume and variety of data you analyze now. This data can be helpful today as well – for example, if you are making decisions about mortgages, you can consider standard risk profiles, and holistic things like the economy, but there’s a lot you can learn about applicant’s behaviour if you look elsewhere, like at social media, as well.

Olga Z.: Paul, you’ve said that there are three big moves that banks and credit unions need to make with regards to data. What are they?

Paul Barter: Banks and credit unions really need to start thinking about their data differently, from the ground up. Here’s what I mean:

1) Move from the assumption that the world is structured. Banks and CUs must move into the big data world – get a Cloudera or Hortonworks big data system as an experiment, set up sandboxes, try new things outside your baseline system. Hire people who work differently. IT people in finance are conservative, and that’s appropriate, but you also need experimentation. Set some recent graduates loose to create prototypes, and see what they come up with. It won’t cost you much.

2) Be aware that as we morph towards AI, we move from traditional math to a world of statistical analysis. There’s not just one right way to make financial decisions. Historically, the folks who have worked in financial IT are arithmetic whizzes, not into statistics.. The people who will thrive in finance in the future will look at analytics to a more in a more statistical context. You need a mix of both types of people to spark vibrant conversations around things like risk.

3) A move towards social science is essential. For example, loan origination is usually done based on metrics and credit, but there are also social factors to consider. For example, applicants care about which FI is most likely to offer a loan, because people hate rejection. Therefore ‘likelihood to approve’ is a metric that might be considered by consumers, and they may be prepared to pay a slightly higher rate in exchange for approval predictability. Working with experts in behavioural psychology can give you an edge here.

Olga Z: What core values around finance matter most today?

Paul Barter: Attitudes change with the day, but some things remain constant. Trust is incredibly important – who do you trust, when and why? Financial institutions need to be sound and stable, acting as stores of value when things go south. Financial CEOs need to balance the conservative approach that makes them trustworthy with transparency and innovation to keep them relevant.

Speaking about credit unions specifically just for a moment here, though – here’s an advantage that CUs have, but may not be fully exploiting. Credit unions aggregate the financial investments of the community and loan it back to the community – just like crowdfunding. In fact, if I were in charge of a big CU, I’d look for an equity position in a Kickstarter or similar, because the brand attributes are the same and it’d be a good fit. People, especially younger people, want an institution that’s not only safe but that also shares their values. Credit unions have that – they just need to communicate it more clearly, through the channels young people pay attention to.

Olga Z: What’s the biggest upcoming trend in finance?

Paul Barter: There is no bigger trend than AI, and you can’t do AI without lots and lots of data, and lots of different types of data. Making headway in data analytics is the only way to compete in an AI world, and without AI you won’t be in business in a decade. So start by solving your data problems, gathering more data today and becoming more data-driven, and you’ll be positioned to strategically grow in the future and be ready for the next wave of innovation.

Paul Barter

About the Contributor

Paul Barter is an adjunct professor of technology strategy at the Schulich School of Business and an advisor for the MaRS ICT Venture Services group. Paul writes and speaks regularly about topics at the intersection of technology and society.

Olga

About the Author

As the VP of Demand Marketing at Doxim, Olga helps financial institutions grow through improved customer experience and increased engagement. She is passionate about helping businesses choose the right technology to solve their challenges.

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