Transcription:
Banking on AI: How AI is Transforming the Banking Industry

Bill Klaproth (Host):  When you’ve been searching for the right insight, advice and information on financial marketing; you know where to go, the Speak Easy. The exclusive source for financial marketing insights with a shot of human, starring Kelly Hellickson and Hilary Reed from EmpowerFi. Strategy infused, data driven marketing solutions for financial institutions nationwide. I’m your host, Bill Klaproth. One this episode, we talk with Riley Dickie, Director of Business Development and Sales Operations for Faraday as we continue our series on artificial intelligence in the financial marketing landscape. This is our second of three podcasts on this topic. And on this episode, we’re going to discuss how AI is transforming the banking industry. Kelly and Hilary so great to be talking with you again on the Speak Easy podcast. And Riley, welcome once again.

Riley Dickie (Guest):  Great to be back.

Host:  So let’s jump in Riley. So, how is AI transforming the banking industry? Give us the overlook.

Riley:  I think the biggest way that AI is transforming this landscape is that it’s predicting consumer behavior like never before. Whether a credit union strategy is around acquisition, it’s around BEEP conversion, engagement, retention, there’s a million things in between those four lifecycle categories as well. We are able to use this technology to predict that human behavior to understand the humans whether it’s members, or prospects, it’s family or friends of these folks and using that data, using machine learning and modelling to have that full grasp to personalize every interaction at every step of the member journey. It’s pretty damn exciting and it’s something that is going to just completely revolutionize consumer banking, credit union banking as we know it.

Hilary Reed (Guest):  I think that artificial intelligence has really transformed the banking, really every aspect of the banking process. The technologies, they can make processes faster, safer, back end operations more efficient, your money goes farther in terms of marketing ROI. So, in all aspects of a financial institution, artificial intelligence is transforming things.

Riley:  Hilary, that’s a great point. Computers whether we like to admit it or not, they’re better and faster than humans at solving specific problems. So, if we can harness that technology, harness that energy and be able to apply it to targeting the right prospect with the right messaging, the right creative and content, and that right product recommendation or we can better engage with existing members. We know who loves to be targeted with personalized email campaigns versus who prefers that the brick and mortar experience if and when that comes back under this current situation and who prefers the call center engagement. All that is so valuable especially in this 2020 world where we all expect that one to one personalization and that one to one engagement. AI, machine learning and these data science processes can do that for credit unions of all shapes and sizes and that’s what is so exciting about this world and this technology that we have in it today.

Kelly Hellickson (Guest):  Yeah, and I think that today, is the algorithmic age and I think that artificial intelligence is going to allow us and does – is allowing us to embrace the uncertainty, right because we all know in the last four months, that’s there’s been a hell of a lot of uncertainty. And if we embrace it, we look to learn from all that we have from a data and tech stack resource standpoint. When we add in artificial intelligence, we’re solving for purpose not just for profit and that’s huge in today’s day and age.

Riley:  One hundred percent and I think if I look back at all the credit union clients that I’ve worked with over the years now and seeing how they’ve gone from what was a four years ago let’s say where it was really all about marketing automation, those types of systems. And now they’re the early adopters of this technology. We’re seeing them use artificial intelligence for audience targeting. So, which membership they should be focusing on for specific initiatives or lead scoring. How do we reply to Riley in a certain way that is different than Kelly or Hilary? No different than when the three of us log into Netflix and have different recommended TV shows or movies. Now a credit union can apply that technology to their products, their services in that one to one fashion or you think of product offerings. Who gets a home equity line of credit versus who gets a signature credit card. All of those things, if we can just target the right people, at the right time, with the right message; you are taking your dollars a heck of a lot further and I can promise you, your members are going to be so much happier because they are only seeing what is right for them and all that extra fluff, all that extra noise that was traditionally sometimes in there, is no longer and we can all thank AI for that ability and those capabilities.

Hilary:  I think that was really important what you said about the members – you’re using this to get to know your members, you’re personalizing the offer. So, we’re seeing credit unions utilize AI to get to know their members but vice versa too. It allows your members to get to know you because you’re only offering them that one on one product that they need in that moment of need. So, the entire marketing lifecycle can be AI can be utilized in the entire marketing lifecycle from outreach to prospects to getting more from your current members, maybe there’s a home equity line of credit that’s not being utilized or maybe they don’t even have a home equity line of credit but we’re seeing credit unions use this in the likelihood to purchase and sometimes without even the use of credit data. So, Kelly I know you say a lot that you think that this can replace credit data down the road and we’re not making any promises I know but maybe you can speak to that a little bit too.

Kelly:  Yeah and I guess we can’t make promises but I have said all along in the past 18 months, I firmly believe that artificial intelligence and the platforms and the solutions that we provide and offer nowadays are going to completely eliminate the need for prescreen mailers because everything, all of what we are doing is based on behavioral and machine data learning and the machine learns hand over fist every single month, month after month and it’s all about behavior right now. It’s not about credit scores. So, I look great on a piece of paper but what does that tell you, what doe my credit score indicate in terms of when I’m going to need to purchase a vehicle for my 15 and a half year old. Or when I’m going to need to refinance. I hope that I’m always going to have great credit but that just – it’s not even a factor anymore in how consumers are making purchases and the decisions to purchase X, Y, Z.

Hilary:  Right and how to find those people.

Riley:  Yeah and I think one of the things that we always tell our credit union clients here at Faraday is if you’re maybe doing the more traditional method of you buy some lead data, well if that’s coming from somebody, let’s say Riley Dickie goes on Credit Karma and searches auto loans. You are already way too late and behind the game. What you need to be able to do is predict six, nine, twelve months ago that at this given time, I would have fallen into a propensity bucket that says I’d be a right fit and if we can do that, apply that to every service, every offering and even more so; every time that maybe an individual shouldn’t be contacted, I think right now is a perfect example under these COVID situations of sometimes as a credit union, you need your machine learning to say heh, this individual just needs you to reach out and say I’m here for you when you’re ready. That is equally as valuable and that’s what this technology is giving credit unions.

Those small and medium sized institutions that once could never compete to even have access to this technology, now they can and now they can utilize it to best engage with their members, with their prospects and with their communities.

Host:  I like what you said there. This really allows local credit unions to compete with big bank budgets, right and find new members and keep them engaged. So, as you’re talking, I’m just wondering someone listening may have a question. We talk about machine learning and predictive modelling. How does this work? Do you put all your contacts into a computer, or do you geographically survey an area? How do you get all of this information, this data, how does this work?

Riley:  Yeah, it’s a great question. And I’m speaking on behalf of the Faraday and the IntelliFi processes, because that’s what I know but what happens is it’s basically taking all of the member data a credit union sits on, those that are still with you, those that have left, those that saw marketing information and never did anything and then obviously, it ties in the products and services they have. All that is valuable because if we can truly understand it, we can then begin to predict future outcomes. Now what IntelliFi powered by Faraday is doing that makes us unique in this space is a big value prop on our end, is that we are partnering with quite few data brokers out there, not any sensitive PIIs but what we do know is hundreds of things about each individual, where they are spending their money, how they’re spending their money, what’s their property look like, do they have a dog or a cat and do they sit inside with a fireplace or do they have a pool.

All these things that as Kelly and Hilary mentioned, are not tied to your credit score. But if you can take all of these added data attributes in rich, that existing member data that sits in your systems whether it’s a fancy data warehouse, a core, MCIS or it’s simply in the Legacy system with exportable spreadsheets; it can be enriched and then instead of hiring data scientists in house, you can plug it into a machine learning software like Intell05 powered by Faraday and it is going to spit out the answers to your business questions. So, what you’re doing is now basically becoming a data scientist. You’re saying heh, I have this home equity line of credit campaign, who should I be targeting that looks like my best members or I’ve got 50,000 members in my local community, and I want to send each of them an email blast. Well which product should I recommend to them and which visual and personalized creative should they see.

And it’s that simplicity of enriched data and putting it through software with algorithms and then pushing results to your systems, to your marketing channels or simply the reports to your C suite and board and I don’t want you to downplay the sophistication of the machine learning but that’s our job to handle building the software and the technology behind it. It’s the credit unions’ job to understand how valuable it is and how easy it is to use on kind of the fingertips of your computer. And that’s kind of the high level of classical machine learning.

Hilary:  I think that in – gosh Riley, that was so amazing. I think I even learned somethings. And I thought I knew a lot. That was really great. Thank you. And for those of you listening who aren’t sure what PIIs are because I wasn’t sure in the beginning, that’s personally identifiable information. So, in this case, you’re not providing social security numbers and things like that. And we’re still able to utilize the data. And my final thought really on the how financial institutions are using this, ultimately the way it truly should be used the right way, is developing a holistic AI strategy that really extends across all of the credit unions, departments, verticals, business lines. I mean AI isn’t just for marketing. Yes, that’s how we use it regularly. But it’s not just for marketing. So, developing an artificial intelligence strategy that’s holistic, that can work among all of the business lines is really the right way to be using it.

Kelly:  I think so too, Hil and I think that’s a really good point because day in and day out we always say marketing touches every aspect of an organization, internal communications, external communications and culture. So, what have we learned in the past three to four months with the pandemic? We’ve learned that we better hope to heck that we have an in case of emergency plan and that we also better take a look at our culture and make sure that every single one of us is being taken care of and through the artificial intelligence lens; that’s what this is all about. It’s taking care of people, the members and your staff. And I think that’s really powerful and that’s something that those folks that are using AI are going to find that they’re going to be able to not only keep up but improve their operations system wide.

Host:  Yeah, that makes sense. And I think that’s a great place to wrap this up. Well Riley, Kelly and Hilary, great discussion. Thank you for your time today. This has really been great.

Hilary:  Yeah, thank you Bill.

Kelly:  Thanks guys.

Riley:  Thank you everyone.

Host:  And that wraps up part two of this three part series. Please join us for part three next. And to connect with Hilary or Kelly please visit www.empowerfi.org and to learn more about artificial intelligence marketing, please visit www.empowerfi.org/services/data. This is the Speak Easy Financial Marketing podcast. Thanks for listening.