On this episode from our “Reinventing Customer Experience” podcast, ZS Principal Arun Shastri and Associate Principal Gopi Vikranth chat with Murli Buluswar, head of analytics, U.S. consumer bank, for Citi, about how the financial giant uses digital to boost its customer experience and keep customers connected across channels.
On this episode from our “Reinventing Customer Experience” podcast, ZS Principal Arun Shastri and Associate Principal Gopi Vikranth chat with Murli Buluswar, head of analytics, U.S. consumer bank, for Citi, about how the financial giant uses digital to boost its customer experience and keep customers connected across channels.
Gopi:
Hello, and welcome. I am Gopi Vikranth and I lead Personalization and Customer Experience Analytics at ZS.
Arun:
And I’m Arun Shastri, I lead the Artificial Intelligence Practice at ZS.
Gopi:
We both work at ZS, where we leverage industry expertise, cutting edge analytics, technology, and strategy to create real world solutions for our clients. In this executive series, we will be talking to leaders about how they are re-imagining customer experiences at their organization, and the role personalization plays to drive customer loyalty.
Gopi:
Arun and I are very passionate about this topic as it is that one our clients wrestle with and, as a consumer, we are constantly re-imagining how businesses can do a better job of engaging us. We hope you’ll join us to explore the answer to these questions through our conversation.
Gopi:
Today, we have a very special guest, Murli Buluswar, who heads Analytics at U.S. Consumer Bank Citi, joining us. Citi needs no introduction, it is the leading global bank and its U.S. consumer bank serves tens of millions of customers nationwide. Arun?
Arun:
When you think of analytics leaders, Murli quickly comes to mind as a thought leader and an influencer. He’s always at the leading edge of innovative analytics practices and he has been responsible for many firsts at Farmers, AIG, and now Citi. An interesting fact about Murli, when he was at Auburn, he was a radio show host. Is that right, Murli?
Murli:
Thank you Arun and Gopi. A pleasure to be on this podcast with you. Yes, indeed, I had the privilege of hosting my own international music radio show when I was at Auburn University. I was often told that I’ve got sort of that very calm, soothing, monotonic voice that’s perfect for NPR and stations of that ilk, and sometimes I was also told that I had the perfect face for radio, so there you have it.
Arun:
Well, the world of analytics is happy that you chose this path and not the path of the radio. But Murli, a pleasure having you here and for talking to us. Let me begin, Murli, by asking you, how has your philosophy and approach to analytics evolved over the past 10 years?
Murli:
Very good question, Arun. Where I have grown the most as an analytics professional in the past decade is in recognizing that when we think about the role of advanced analytics, we’re actually getting to the crux of how people think about their careers and their expertise and their professional legacies. And so in large mature organizations, analytics, it cannot be separated from the role of culture, cannot be separated from the power of how are decisions made and what decisions are going to be made differently as a consequence of analytics.
Murli:
Too often in my younger days, I used to focus on data and insights and facts and objective truth as being the sole driver of decision-making. Over the last decade, I’ve come to realize that ethos and pathos are just as powerful, in fact even more powerful, in shaping human decisions as is logic or logos.
Arun:
Ethos and pathos, that’s a very interesting takeaway. I love it. Murli, I think this pandemic came out of the blue, it’s taken a lot of us by surprise, and there’s been a rapid shift to digital since the onset of the pandemic. I’m sure that this is front and center for you. What are your thoughts on this?
Murli:
That constant of engaging with customers where they want to, when they want to, how they want to, is very much at the crux of how Citi thinks of its consumer strategy in the U.S. Too often, Arun, I find that firms sort of think about digital and bricks and mortar as being either/or. We think of it as really sort of a seamless harmony of channels, because it’s not just about saving costs or how we would like to interact with the customers, it’s all about what channel preferences does the customer have and at what point in time might that be different for what particular type of transactions and how can we be best positioned in order to serve them in that context at that moment that is most relevant to them. That’s how we think about it.
Murli:
Obviously with the onslaught of the pandemic it has certainly created, at a minimum, a midterm shift in how we as consumers think and how we engage with a whole host of firms that we do business with, certainly banking being one of them. And I’ll give you one simple example of that, if I may, is I remember back in March and April, when we were in the throes of the onslaught of COVID-19, much like many other firm, we had a challenge with human staffing of our call centers, both here in the U.S. and internationally, and the wait times were getting way too exorbitant, and we had customers that were unfortunately dropping off the calls.
Murli:
What we figured out was we could actually engage with them when they reconnected through a digital channel. When they logged on to their mobile app, we figured out how do we pick up the journey thread and connect with them and serve them in that channel at that point in time, recognizing that they weren’t able to connect with a call center rep at that point in time.
Murli:
What it created was a fundamental, I would say, shift in the pace at which we thought about engaging and connecting and building greater relevance in serving our customers in their time of need. And if there’s one sort of silver lining of this, is that COVID-19 really accelerated the speed at which firms, including ours, adapted.
Arun:
Murli, I heard you say two things that I think are very, very interesting. One is this idea that digital as well as brick and mortar are not two separate channels. In fact, they somehow have to come together. And the second thing I heard you say is this notion of personalization. Can you talk a little bit more about what role you think personalization plays in unlocking customer growth and customer value?
Murli:
Thank you, Arun. And look, as consumers we expect the firms that we interact with, regardless of which sector, to have a baseline intelligence of us and to be able to demonstrate that in their interactions and to build more connectivity, and banking is no different.
Murli:
One big step that we were able to take in the recent months was to stitch together our interactions with our customers across every channel, and we’re in the process of drawing meaning and relevance from that to build deeper relevance and to serve customers in more profound ways.
Murli:
To make that even more concrete, historically, imagine if you were to call a call center, there’s an interaction that you would have had and then if you were to go to a physical branch and have some form of a transaction, whatever that might be, that data and the richness of that interaction remained in those individual channels. We now have the capability to be able to connect that and to draw meaning and inference from that to serve you as a customer in more profound ways than ever before.
Arun:
That’s great, Murli. I think a few things I’ve learned already is it’s more than insight, it’s about ethos and pathos. It’s more than simply stitching together the journey but drawing the insight and being able to direct the customer in that journey. So what is your role? How do you think of your role at Citi and what do you think of the role of analytics at Citi?
Murli:
Gosh, at a very simple level, if you think about what’s happening in the world around us, data and technology are very much at the heart of how customer experiences and business models are being reinvented or created from scratch. And so Citi is no different. We do collect quite a bit of data based on our interactions with our customers across channels, and a challenge and opportunity for us is, how can we understand and serve our customers more deeply than ever before?
Murli:
You can very well imagine the role that analytics plays as a critical enabler of that. And the challenge and opportunity for every analytics function is to find a balance across three dimensions. The first dimension is answering critical but time-bound questions in the here and now. The second is serving the customer needs in the short and median term through more deeper insights. And the third is in delivering transformative insights that could drive a step change of intelligence in how we deliver what we deliver for our clients.
Murli:
The way I think about my role is to find a balanced portfolio approach across all three of those dimensions and to connect the insights to deeper change. Too often, if you think about mature firms in particular, which may not have analytics in their DNA right from the get go, the storyline that you see is if you were to ask a CXO in many mature organizations across industries, do you believe that this capability is critical to your growth and success? The answer is yes. If you were to ask them, are you making investments? You’ll hear some form of a narrative. If you ask them, what successes have you had? They’ll give you a one or two one-off anecdotes. And then if you ask them, help me understand three years from now, or two years from now, how will the what and the how of decision-making look different in your firm as a consequence of data-driven intelligence? You probably don’t have a particularly compelling view.
Murli:
The challenge, the reason for that, in my view, is that there’s almost a little bit of a dichotomy of to what extent is analytics answering the questions that are being asked and to what extent is analytics asking those deeper questions, applying more advanced analytics, and harnessing more data to solve for problems in ways that people may not have thought about before or perhaps aren’t proactively asking?
Arun:
Very interesting. Gopi, you had some questions for Murli.
Gopi:
Yeah. Murli, as we are talking about analytics and technology, AI and machine learning seems to be on everyone’s mind, yet they also seem to be a little bit elusive in terms of adoption and value. Can you share your thoughts on this?
Murli:
Yes. So I think the reason that the value, or the quantification of the value, is inconsistent is a couple of things. Number one, with any form of innovation, we tend to overstate or over amplify the benefit in the near term, and we tend to understate the degree of innovation in the longer term. And where you are on that adoption curve varies from industry to industry, and frankly within that from firm to firm.
Murli:
I have this fundamental belief that as senior analytics executives think about their roles across industries and across firms, they should be tackling a portfolio of problem statements or opportunity statements that cut across time, value, and certainty. In other words, being able to deliver insights that may not be as impactful, but the insight itself and the decision that that will influence has a high degree of certainty and starts building credibility and trust and a connectivity and a recognition that the analytics team has an appropriate amount of commercial acumen is really critical.
Murli:
At the same time, being able to sort of think about that whole spectrum of innovation and working on problems that can have more profound implications in the medium term may not quite be as certain and do require change management, is probably that second dimension. And then the third dimension is thinking about how this capability can more fundamentally disrupt or transform the business model itself.
Murli:
My recommendation to any senior analytics executive or a CEO or CXO, is to be thinking about the role of this team across all three of those dimensions in parallel. And one way to gain some traction and progress pretty quickly and thoughtfully is by asking questions such as, hey, where is the process a bit too manual that could create opportunities for automation? Where has a process not really changed or evolved in the last, call it couple of decades? In what aspect of one’s operations or customer interactions might we be collecting new forms of data that could further inform the intelligence with which we engage with our customers or solve for a particular piece of our operations? And last but not the least is, what known customer pain points do we have that we could solve for in more creative ways by harnessing the power of data driven intelligence?
Murli:
Putting a framework to the role of analytics and thinking more deeply on what is the change you’re trying to affect and translating that broader vision into more concrete mile markers, to me, is absolutely critical to winning hearts and minds of your colleagues.
Gopi:
That’s very interesting, Murli. Thanks for sharing that. As you were talking about how senior executives need to think about this and the framework, can you share an example from your experience on how this has manifested and how this framework has evolved in your experience?
Murli:
Certainly. I’ll give you an example from a different sector, if I may. When I was in the insurance sector, one of the challenges that the insurance sector faces, particularly on the commercial side of the business, is billions and billions of dollars of risk capital decisions were made on a regular basis based on what I would largely describe as heuristics and art with a nod to historic experience, but largely based on, frankly, individual expertise.
Murli:
We all know that individual expertise can be very powerful and, frankly, cannot necessarily always be represented in data, so I certainly do not mean to diminish the power of expertise in shaping some of these decisions. On the other hand, the counterpoint to that is, if you take any of these large insurance firms, they’ve collected a lot of historic data on experiences that they’ve had, whether it is on underwriting large complex deals, or whether it is on the judication of complex claims, and the question really is, how could they harness the power of that historic enterprise level experience going back multiple decades, perhaps, and connect that to inform the human judgment in the here and now?
Murli:
The magic really, Gopi, is in finding, again, I’ll come back to this word harmony, because oftentimes we use the word balance implying that they’re sort of competing forces. But they don’t have to be competing forces, they can actually be intertwined forces of human intuition and expertise augmented by data driven intelligence.
Murli:
In my previous life, I’ve actually built out solutions with my team where we harness the historic experience and put that in decision tools that helped underwriters and claims adjusters put some parameters around their decision-making with an eye on reducing the volatility of decision-making and reducing the thickness of the tail of the outcomes, both on the far left and the far right. And what we saw was that that sort of intersection, the integration of data-driven insight with human judgment, was far superior than any model unto itself or any human unto himself or herself. Which, by the way, has actually been proven out time and time again if you think about the good old sort of chess analogy with IBM Watson and such, and how that has morphed with teams that are really combining multidisciplinary expertise with data with, with computers, are the ones that are really winning over computers only or humans only.
Gopi:
Thanks for that, Murli. That’s fascinating, especially about the underwriting and the complexities that are involved in there. Now, coming back to the earlier example that you’re sharing about how we are stitching a single customer journey. Can you tell us how you’re leveraging AI to scale personalized experiences at Citi?
Murli:
I can actually talk more broadly, Gopi, to the role of advanced analytics. I have a preference not to use the phrase AI, and the reason I actually shy away from the phrase AI is it actually means different things to different people. I’ll give you one simple example is, a couple of years ago, I was advising a well-known mid-stage firm that was essentially harnessing the power of unstructured data to draw deeper insights in the life insurance space, and they started sort of changing their nomenclature to talk about AI. And when I dug deeper, I realized it was good old advanced analytics. Solid analytics, but really not much more than that. And I do fear that we live in a world where AI is a little bit of a taboo phrase, or is grossly misunderstood or loosely used. So I’m going to stay away from that phrase, not to pontificate on the definition of AI, but coming back to your core question is, how do we harness power of advanced analytics?
Murli:
In my interpretation, the way we think about it is asking questions that maybe weren’t being asked before, and I’ll give you an example of this, perhaps. Second is being able to tap into more data and more of our customer interactions to be able to know the customer better. And in this instance, I alluded to the fact that historically any interaction with a customer would remain in that particular channel and we now have that ability to stitch those customer journeys across channels to build that omnichannel relevance and orchestration of customer engagement.
Murli:
The third is more sophisticated analytics, which, in my mind, connects to this notion of analytics-as-a-service. But both analytics-as-a service and real-time insights, so we are on a mission to say, look, let’s rethink the paradigm of where we see opportunities to ask and answer deeper questions.
Murli:
One example could be, do we have a deeper understanding on a 360 level of a customer in their full form relationship across all of their financial services needs, and how are we continuing to build relevance to understand that more deeply in a way that cuts across products and channels. That’s one instance where you could imagine the role of analytics can be very, very powerful.
Murli:
Another big, big piece of it is this notion of speed of decision-making, speed of insights, and whether it is retrospective insights or prospective insights, we are on a mission to fundamentally accelerate the speed at which we deliver customer insights, because we think that that contextual timely engagement with our customers is huge. And also internally being able to provide that intelligence and informed decision-making in a much more dynamic way is mission critical. Again, whether that is forward-looking or retrospective.
Murli:
That’s a huge part of our mission, and as we think about that, we’re harnessing the power of natural language processing, we’re harnessing the power of natural language generation, and we’re harnessing the power of computer vision with an eye on recognizing that data as we know it. Obviously, it has a much broader definition than ever before.
Murli:
Part of the problem we’re also trying to solve for is. Within our organization people don’t necessarily lack for data or reports, but how do you translate that data and those reports into more dynamic and interactive insights? And that’s where we see the power of natural language generation, is to be able to provide that context and to provide tools that allow our key executives to interact with data in much more dynamic ways that is much more powerful than receiving an Excel spreadsheet with a bunch of numbers. So it’s really getting at that speed and granularity and intelligence of data driven insights that is at the core of the change that we’re looking to contribute to at Citi. Some of that is focused on our internal colleagues, some of that is how we connect and build greater relevance with our customers.
Gopi:
That’s great, Murli. So delivering personalized experiences from advanced analytics, from a range of data that’s available, treating analytics as a service, and focusing on faster time to insight so the business is able to consume the signals and then act appropriately. I think that seems to be a big theme there.
Gopi:
Murli, imagine five years from now in the broader consumer industry, and let’s assume that there are no constraints on technology and data, and they’ve evolved to where they need to be, what are your top three to five predictions on how customer experience will change fundamentally?
Murli:
Gosh, I have a crystal ball. Could you hold on for a minute, I’m going to look at it and have a think. Okay, got it. Three themes that I’d like to offer up to you, Gopi, and to the listeners. Number one is, and this is perhaps more aspirational than a perfect prediction, number one is I do believe that we need to evolve to a world of opt-in. For those of you who’ve had a chance to read the book on Mark Zuckerberg and perhaps seen the movie “The Social Dilemma,” those are sort of illustrative, and there are obviously many, many, many players in this space, but I think the core question that we need to grapple with as a society across countries, frankly, is how do we think about our data being monetized and how comfortable are we with sharing data about us?
Murli:
The challenge that I see is if we don’t know what’s being sold, then we’re being sold, i.e., that we’re either paying for a subscription of some sort, or our data is being monetized, to state the obvious. And I would like to see an evolution where consumers have the opportunity to have a much more closed loop approach to their data for their privacy, and to be able to pay for it and have consumers make the choice on whether they would like a free service where their data is monetized or where they’re actually able to pay and get different layers of privacy. That’s sort of prediction number one or aspiration number one.
Murli:
Prediction number two is across firms, across industries, there will absolutely be an integration of data and insights cutting across products and channels. One simple example is if you think about the concept of personalization of medicine, it’s a phrase that is bandied around quite a bit for those of us who read the literature, but at the end of the day, there’s an enormous amount of art that is exercised by our medical practitioners, particularly as you get to more and more complex health conditions, on what regimen works and what doesn’t. But quite a bit of this can actually be, I wouldn’t say solved for, but enabled in a powerful way by being able to tap into the consumers individual data and guide what regimen might work for them versus a different patient.
Murli:
This notion of being able to use data across products, across channels, and possibly sometimes across industries, to serve the consumers in more thoughtful, intelligent ways, I think is an aspiration number two that I have.
Murli:
The third one is almost a little bit not an aspiration as much as perhaps a potential fear that I have is that firms will sometimes know us better than we know ourselves. And how do we kind of draw the distinction between needs and wants and how do we sort of find that balance between having offers and services put in front of us that are hugely relevant to us versus being subject to a version of the new millennium’s subliminal advertising, except it’s probably even more profound than that.
Murli:
I don’t know the answer to that, but I do think that these are some themes as it relates to the world of advanced analytics that we should build some more consistent consciousness around.
Gopi:
Thank you for that, Murli. And especially subliminal advertising is something that I fear about too, and hopefully that’s not the one which is going to come out the soonest. So, I’ll tell you by quickly summarizing of the themes that came across today.
Gopi:
I think there was a lot of emphasis on taking a portfolio approach to solving the problems that a large organization might face. How do we balance out time value to innovation at the core and transformation of the business model seems to be a very key advice from you, Murli, to some of the executives.
Gopi:
As far as personalization is concerned, and the customer experiences are concerned, looking at how do we take advantage of the fact that there are insights and signals that customers are providing across many, many, many channels, and how do we bring that together in a timely fashion for the business to take interesting steps, whether it’s intervention that they can do with the customer, whether it’s digital or in a physical manner, and that can drive really great experiences for customers.
Gopi:
And last but not the least, I think AI, yes, it’s a term that everyone is using, but looking at how advanced analytics as a whole can bring things together, harmonize how data and human experience and expertise is brought together so that the business can take better actions and provide better experiences to its customers. Is that a fair summary in terms of the big ticket items that you shared as insights?
Murli:
You said it better than I could have, so thank you for that, Gopi. And one sort of finer point I might add to that is this notion of ethos, pathos, and logos is getting at this core concept of, at the end of the day, particularly as we think about more mature industries, the potential and promise of this capability is around rewiring the what and how of decision-making.
Murli:
Let’s not underestimate the new muscle building that that requires and how much that’ll challenge existing norms and beliefs around what decisions should be made and how decisions should be made. So there’s a very powerful culture component to this. So as much as we all like to think that data and insights and truth shall set us free, some might argue that in the last few years we’ve learned that there’s so much more to human behavior and how societies evolve that goes beyond data and objectivity. And it’s, again, that intersection of ethos, pathos, and logos that I think is where the magic happens, whether it’s within a broad society or whether it’s in an individual firm.
Gopi:
Murli, thank you so much for joining us. I think every conversation I have with you I walk away with some insight, some wisdom, and this is no different. So thank you very much for joining us and for sharing your thoughts with our listeners.
Murli:
Arun and Gopi, it’s been a real delight. Thank you for the opportunity and best wishes for this series, and I look forward to listening to the subsequent episodes. So I appreciate the opportunity. Thank you again. Bye, everybody.
Gopi:
Thank you, Murli.