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Russ Kole and Matt Swain discuss how the financial services industry is ripe for digital innovation in this Reimagining Communications episode.
Matt: I'm Matt Swain, and you're listening to the "Reimagining Communications" podcast, where we discuss the opportunities and challenges facing companies on the road to optimizing their communications for the future. Today, I'm joined by Russ Kole, Head of Customer Engineering for Financial Services at Google Cloud. Russ, thanks for joining me today.
Russ: Thanks, Matt. Very happy to be chatting with you today. I think even under current worldwide health concerns, we still need to be able to connect and share experience and knowledge with each other to keep progressing. And the limitation on face-to-face interaction has certainly strengthened the impetus to bring more effective digital interactions to all industries, especially critical ones like banking and finance. So happy to keep us moving forward.
Matt: Well said. And for context for our listeners, can you share a little bit about your background and how you ended up in this role at Google Cloud?
Russ: Sure. So, I started my career in banking working in a consumer bank at Citigroup. So, there I worked on digital initiatives of the day back then, namely digitizing the front and middle office operations, working on rolling out digitization of checking with check image capture in the front middle office as well as digitization of employee identification with biometrics. From there, I took on some roles in the consumer internet space, working on health information systems. And then the cloud really started to resonate with me. I dreamed of a day where I didn't need to concern myself with physical infrastructure and data centers, the delay in getting things done. Ordering, racking, configuring hardware was a maddening delay in progress. So, if I never see the inside of a data center again, I'm going to be happy. In cloud, I spent four years with Amazon Web Services. I worked with digital natives and early adopters growing a very large business there. However, I yearned for more transformational approach to cloud, instead of just doing what you do in the data center on someone else's hardware, and that's what really attracted me to Google. At Google, we're not just enabling customers to run their existing stacks on our hardware, but we're really enabling customers to leverage the pioneering work we've done in data science, AI, machine learning, and hyperscale computation. Google's infrastructure fundamentals enable systems to scale and operate globally in a way, unlike other infrastructure. It truly operates, we like to call it internally, as a planet-scale computer.
Matt: And I was curious, Russ, if you could dive into some of those problems that you're specifically trying to solve with your financial services clients.
Russ: Yeah. So, financial services is ripe for digital innovation. If you've ever taken out a mortgage, called your bank, or interacted with an asset manager, you may have experienced less than optimal information exchange that leaves you thinking there has to be a better way, so this is what we're working on.
Matt: When we think about COVID as an accelerant to digital transformation, I can't emphasize enough how many times we're hearing from our clients around their desire to go paperless. Some of the recent research that we've done with financial advisors show that 91% want better automation to manage their paperwork, 70% think of leaving their firm for one with better technology tools, and actually, 48% said that they've lost business because their firm lacks the appropriate technology tools. As these paper-based processes in financial services give way to fully digital processes. What do you see as the next phase of innovation in document processing?
Russ: Yeah. So, paper is expensive. Paper processes are expensive to banks and it's a time burden on consumers as well. So, how you can optimize paper-based processes is really a win-win for everybody. At the beginning of a relationship, there's a lot of intake, and there's different regulations depending on what type of account or what type of engagement you're having with your financial institution that require different types of documents to be exchanged to either validate who you are, or validate your assets, or validate your ownership over certain assets. And those processes take a lot of intake, take a lot of analysis looking at this paperwork, pulling out the information, transposing that information from the paper to another system. It's a time-consuming process. It's an expensive process, and it's also error-prone. You have humans in there that have to read things, that have to make interpretations, that have to then enter that information into another system. There are multiple points of failure in that process that digitization can help solve for.
Matt: Thinking about OCR, optical character recognition, the inside joke was always “occasional character recognition” in the sense that, it's not a perfect process, it requires a lot of manual oversight, which, to your point, is error-prone.
Russ: That's right. And it required a lot of supplying input as to exactly where the field began. What kind of field was it? How many positions do you need to read? What are you expecting? If you see a decimal point in the wrong place, it throws the whole thing off. Because of the innovation that we've had around machine learning, we can actually create models that know how to read a document and can tell you what it sees as opposed to you having to tell it what it's going to look for. So, when it sees a dollar value, it knows it's a dollar value. When it sees a bunch of numbers with two decimal places after it, it knows that that's a dollar amount. It sees the dollar sign in front of it. Or when it looks at a table and sees columns of a table, it knows that that's a pair and can extract that information with its context as a pair. Having a system that can look at a document and see a character set that matches a phone number format and can automatically tell you this is a phone number, and in some cases validate that it's a valid phone number, or a social security number, and automatically redact that information from the screen and prevent personal information leakage. Whereas in days past, that information would have to be either redacted manually, or you would need to trust the people that were looking at that information not to disclose it to unauthorized individuals. So, there's a lot of opportunities for the capability that we have that really enables a computer to read a document. There's a lot of ways that we can use that not only in the intake process but in the servicing process and in other downstream processes.
Matt: Well, I think your point around the various processes is important because of the way working with paper has been in the past and the way organizations have been siloed, you do have this opportunity to bridge the divide and disparate processes within organizations as you noted onboarding and servicing.
Russ: Yeah. So, I think a huge opportunity is to take the human out of the input pipeline. Intake the documents digitally enable your customers to either email them in or submit them electronically. I know we have some firms that are actually doing electronic fax to digital. Take the document, you get it digitally, you can bring it in, you can then derive the data out of that document you need if you're reading a bank statement, or if you're reading an income statement, or tax return. Whatever that is, pull that information out, associate it with that applicant or that consumer, and then automatically feed it into the downstream system. There's a tremendous amount of error-prone processes that you can eliminate by taking the human out of that. And you also take the risk out because now you're not exposing that information to people. Studies have shown the largest risk to information theft doesn't come from external threats to organizations. It comes from insider threat, and the best way to prevent insider threat is to actually eliminate the ability to see sensitive information. So, when you take the human out of the intake process and you take them out of the reading of a document and inputting sensitive information like social security number, and account numbers, and personally identifiable information, you're removing a tremendous amount of attack surface from which information can be stolen.
Matt: What are you seeing in the capital market space? How are you supporting that market?
Russ: So, on the capital market side is a very interesting problem. There's a tremendous amount of volume in every market. There are more participants, there's a lot of machine-based transaction going on that increases the volume of transactions, the speed of transactions, creates a tremendous pressure on the middle and back office to get through settlement operations. And we see a huge opportunity to be able to optimize and increase the accuracy and speed of those processes using artificial intelligence and machine learning. One of the ways that we're doing that is helping a firm predict transaction settlement failures in the treasury market. So, it's one of the largest voluminous markets out there and there's a tremendous amount of failures that occur, tremendous in a dollar figure, and it impacts market operation, and it impacts counterparties ability to complete operations that require collateral for various different types of things. So, being able to improve the function of that market is a tremendous improvement in efficiency. So, what we are working on is creating a model that can help predict whether a transaction will settle or not, and if it has a likelihood of failure, we can warn the counterparties early that the settlement may not go through. And there's obviously a deadline. There's a fed wire cut off at 3 p.m. that these things need to get done by. So, if we can give three hours' notice that this transaction is going to fail to settle or likely to fail to settle, that could potentially help those counterparties significantly. And it's something that we hear from all sides. We hear it from asset managers, we hear it from the custody side. Everybody is interested in solving this problem. And that's sort of what Google looks for is things where we can apply some really targeted expertise to a very specific problem with a very definable outcome that has a tremendous impact.
Matt: And Russ, how about with asset and portfolio managers?
Russ: Yeah. So, it's interesting there. Data is really what's driving everybody's decision-making, and there's a tremendous amount of data, news data, news flow, activity, economic activity data, consumer activity data. You can read about asset managers trying to analyze industrial output data, looking at the electrical consumption of countries to estimate GDP, looking at volumes in shipping ports. Everyone is trying to get ahead of everybody else by looking at data and trying to find early indicators. This is a classic reason to use compute power to mine data for signal. So, we're working with asset managers, and portfolio managers, and quantitative researchers on building models that can input tremendous quantities of data across multiple sources, alternative datasets, news data, company filing information, and being able to predict what the impact on securities is going to be with the changes that are occurring or the events that are happening, and being able to act on that very, very quickly as close to real-time as possible. That's where we see capital markets firms investing tremendous amounts of resources and time to try to get ahead of the changes in the market, not only for increased alpha, but also being able to hedge against tail risk and being able to go back and study and say, "When these events happened in the past, these were the impact on these markets," and being able to position for those sort of things that seemingly are occurring on a daily basis in 2020 at least.
Matt: I had teed up a couple points from our financial advisor research. And whether it's financial advisors, investors, or general consumers, while it could be in generalization, the younger investor or consumer is more interested in communicating with their providers in the latest, greatest ways, right? They tend to be more tech-savvy, their expectations of their providers are different. I'd be curious and, you know, through your lens, when you look at the brokerage space, how are you helping companies prepare for that next generation of investor?
Russ: Yeah. It's a great question. So, it's interesting, you know, you look back at the invention of the cell phone. We created a device that allows you to have voice communication anywhere in the world, and everybody wants to use it for text communication.
Russ: And that's sort of indicator of people want to be efficient, right? Even myself. Phone calls are expensive. They're expensive because they take time, and sometimes you want to have that casual conversation. You want to have some banter, you want to make small talk, but oftentimes, when you're trying to transact or you're trying to get something done with a bank, with your brokerage, with whoever, you just want to get it done. You're not interested in everything else. Everybody is moving at a much faster pace these days. Time is always of the essence. So, making a communication efficient and making really operationally being able to work with a financial services firm in an efficient manner, in a way that doesn't require a trip to a branch, or a trip to your asset manager, or your financial advisor, and being able to say, "Hey, you know, I saw this on the news. I want to get exposed to this market," or, "I want to take my position out of this company," or, "I want to invest in this particular market over here." Those are things that people want to make those decisions quickly. They want to act on those decisions quickly, I should say. They've made them quickly. They want to act on them, or maybe they've taken a while to think about it, but once they've come to that decision, they want it done.
And Google has been building digital experiences for the consumer market for two decades. We operate nine applications with a billion daily active users. Our applications are ubiquitous. It all just works, and it works seamlessly across all platforms. That takes a lot of ingenuity. It takes a lot of engineering, and quite frankly, it's way more engineering overhead than I think any financial services institution would want to invest, nor should they, because it's not core to what they do. It's not core to the fiduciary responsibilities that they provide. They're the brains behind how to manage assets. They don't need to learn how to create digital experiences.
So, you know, when we look at the opportunity around consumer brokerage, there's a tremendous transfer of wealth occurring. The baby boomer generation is bequeathing their wealth to their children and their children's children. The Gen X and the millennial generation have dramatically different expectations of how they're going to interact with their fiduciaries than the traditional means that their parents and grandparents had. No longer is the shake of a hand and sitting at the wooden desk in the nice office the mark of an effective and trustworthy asset manager. It's the person that communicates with you timely, that gives you information when you ask for, that is informed on what's going on out in the market. And people that are going to be inheriting this wealth have a very high expectation for what they can do digitally because they don't even want to talk to a person most of the time. They want to just do their research, make their decisions, and take the action. There's a tremendous amount of self-service mentality in the younger generations.
Matt: Even just looking at the last few months, Bank of America, for instance, showed that 22% of its mobile check deposit new users were age 55 plus in the second quarter, and PayPal was talking about, you know, the majority of new PayPal users were boomers and older. So, you know, it's interesting even just...We talk about this wealth transfer and positioning for the millennial, but I think we're also at this inflection point where Gen X, Gen Y are also being forced into digital experiences that they haven't experienced before, and it's, important for all of the organizations supporting them, not only to have the good technology in the background supporting it, but to have the front-end customer and user experience really being super intuitive and better than the experiences that they're accustomed to.
Matt: Russ, I ask this question of many of my guests. If you tie back to the way that account holders, investors, borrowers, consumers in general, are going to interact with their financial services firms in the future, how do you expect these communications will continue to evolve in the coming years?
Russ: Well, I think there's going to be a focus on reducing human-to-human interaction in general. I think in the consumer industry we’re aligned that if we can handle an issue, or an inquiry, or a sales process digitally, without people, it's going to be better for everyone. It's going to increase the speed. It's going to reduce the cost, and it's going to create a better experience for the client. So, take, for example, you call into your call center. You're talking to another human let's say in a bank, and you say, "Hey, I'm calling because my credit card payment is due in three days and I'm short on cash." But what if instead of calling in and talking to a human, or maybe you call in and talk to a human but that human has Assistants that can look through your transaction history, understands that your credit card payment is due in three days It knows that you have a low balance in your checking account, much lower than you traditionally would have at the time you make this payment. That system might automatically determine your credit risk. It might pre-populate an approval for forbearance, or a deferral, or a reduced minimum payment amount. It might offer you a product to potentially refinance that, and that can happen in the time it takes you to make that phone call or the time it takes you from the time you were identified on the call to the time you get dropped down to a person. And at some point, maybe that entire transaction can occur without a person being involved at all on the institution side. I think that's where we're headed, and I think that's ultimately what's going to drive a better customer experience, and a better cost basis for operating a consumer operation. These are examples that are prevalent in many different industries across financial services – whether it’s consumer banking, consumer cards, brokerage. If you can train a human to know it, you can train a system to know it. And in many cases, the system is going to be more accurate and less biased than the human. But there needs to be robust conversation among regulators, financial firms, and AI providers to ensure such systems can be deployed responsibly. And that’s important to achieve because there’s significant benefits to be had vis-a-vie rigid rules-based system. I think that's where a lot of time is being spent currently because we have a lot of firms that want to utilize machine-based decisioning, but not all regulators fully understand it and are comfortable with it yet. Well we're getting there. We're working on research and tooling to detect unfair bias. We’re working on explainability techniques for AI-based systems, and I think that’s where most of the innovation is occurring in machine learning today.
Matt: Well, Russ, Thank you so much for sharing those insights today. Very interesting.
Russ: All right, Matt, it was a pleasure. Thank you.
Matt: I'm Matt Swain, and you've been listening to the "Reimagining Communications" podcast. If you like this episode and think someone else would too, please share it, leave a review, and don't forget to subscribe. And if you're ready to reimagine customer experiences, consider the Broadridge Communications Cloud, an end-to-end platform for creating, delivering, and managing omnichannel communications and customer engagement. To learn more about Broadridge, our insights, and our innovations, visit broadridge.com or find us on Twitter and LinkedIn.
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