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Citi keynote at PegaWorld iNspire 2023: Citi: Driving Omni-channel, Customer-centric Experiences with Decision Science

For a bank that was founded more than 200 years ago, Citi sets the standard for digital-first client services. Join Dr. Promiti Dutta, Citi’s Head of Analytics Technology & Innovation, to hear how one of our first and oldest clients is using Pega’s latest technology to deliver on its mission of being a trusted Financial Services partner. Get the details on how decision science enables faster, deeper, wider data-driven insights to achieve superior decisions and outcomes.


Thank you so much. It is such a pleasure to be here. Since the time I joined Citi, there hasn't been a PegaWorld in person, so this is actually my first PegaWorld live and I'm so excited to share it with all of you. I'm also hoping that in the last 40 years, Alan, you've noticed some change that we've driven at Citi. I think we're coming a long way. There's still more to go do. There's always more to do, but we're making progress and I also hope that there's some cake served later today. I'm hungry for the cake. So let's go ahead and get started.

As head of analytics technology and innovation for the US Personal Bank, I'm responsible for driving and creating data and analytics solutions that enable faster, deeper, wider, data-driven insights to achieve superior decisions and outcomes at scale, and we'll talk about that throughout the process throughout the next 15 minutes that I have up here. But before we go any further, let me start with what will perhaps be the shortest introduction to Citi that I can provide. We were founded 200 years ago, more than 200 years ago, actually with the same mission that guides us today. To serve as a trusted partner to our clients by responsibly providing financial services that enable growth and economic progress.

The US Personal Bank is comprised of three main parts, our branded cards, our retail services, and our retail banking, and our vision is to provide a client-centric experience for today's digital world. Citi is setting the standard for digital-first client services and is invested in using the best available technology to do so, and in order to drive operational excellence and growth. Our strategic goal is to drive bespoke personalized experiences for customers in the US Personal Bank that meet the customer in moments of truth, to offer seamless experiences that help form a true relationship with our financial institution.

We call this our customer 360 approach. It's an approach that uses analytics and decision sciences to truly harness the power of the data to understand the customer needs and wants. This in turn enables our real-time decisioning across all our channels. It's used in concert with human judgment to provide a personal connection into every interaction. To provide a client experience that is continuous, seamless and always present, and to do it in a way that both supports our growth and complies with our guidelines for risk and controls. To do this, we're building out new capabilities, harnessing our customer data, driving actionable insights, and fully connecting our end-to-end delivery of these experiences. Let's start by discussing what I mean by taking full advantage of our internal data.

Our client-centric firm mission also means that we need to make sure we have our data in a fit-for-purpose manner in which we can truly understand our customer. So we first have to make sure that our data is not in silos by products, but in a true customer 360 fashion across all the products. We have developed what we affectionately refer to as the customer analytic record or CAR. It is a curated data stream that has thousands and thousands of elements and is consistently growing. Some of these elements even flow in real time and are curated attributes and insights that provide a few of our customer across all interactions, products and channels.

Of course, you can imagine that there's qualitative information that we have like zip codes, home ownership, household member accounts and whatnot, but we also quantitative attributes. Attributes like customer-level transactions, number of times they engage with us, the channels they use and how of course their money moves because after all, it shouldn't be surprising. We are a financial institution. But added to these elements are additional attributes that truly let us understand the behavior of the customer. This serves as the foundation to enable our superior decisions at scale for us and the US Personal Bank. For example, if we know that a customer spent $457.67, exactly what was it spent on? Was it at a hardware store? That's quite a hardware bill. Was it at a restaurant? Was it for travel? Is it a common pattern for our customer or is this something that we're noticing as an anomaly?

We have also focused on integrating the more qualitative human parts of our customer interactions into this larger repository. For example, did the customer just call a call center? Is it the first time they're calling or do they keep calling us for the same reason over and over again? Maybe they like talking to us, but I'm assuming it's not that. I think they need some help with something. The juxtapositioning of all our current customer data, both structured and unstructured across all interactions and touch points, all channels and all products, truly puts us in a state to uniquely utilize our data to harness actionable insights at scale like never before.

This is what we refer to as our on-us data. On-us data is the data that our customers have trusted with us. It's actually the foundation of what drives CAR today. Using this, we can derive insights such as we see that the customer has spent on a hotel reservation today. The dates happen to correspond with their birthday, and so we know that it's a special event. What can we do to surprise our customer on that special day? Hey, maybe we can get some cake. All this is enabled using only our on-us data. Just imagine the world of possibilities as we start harnessing the world of external data. Office data is that external data, data that we don't directly collect, but oftentimes there are many firms out there that do. We think of this office data as credit bureau data or social media, but there's so much more information out there.

Let's imagine the potential of that for a moment. Did you know that today it is possible to purchase granular information on individual transactions? How does that matter to us at Citi? Well, going back to our original example, we know that the customer made a transaction at a hotel vendor, but to make this more real, where did they book and for how long? We know that a hotel reservation means travel, which means that they likely need some form of transportation, whether it's by plane, train, or automobile. In an ideal situation, we would be able to proactively assist the customer in making such a booking.

And then to take that one step further, if we know from their past interactions that the customer has a preference for certain types of shows or events, we can even connect them to our merchant offers and priority event tickets for relevant events during their trip. Imagine how that changes the customer experience end to end. The explosion of this type of granularity of information will truly change how companies are able to trustfully use data provided by customers to gain intelligence for Uber personalization for their customers.

We're also enhancing the way we utilize and maximize the value of our data through robust analytics. Let's briefly think through the life cycle of how an offer reaches a customer. In this case, let's focus on customer marketing offers. We first identify the population of the eligible universe, and then we have several internal developed advanced analytic methodologies and capabilities that we've built to hone in on what a customer should be given. Then we take those inputs and run them through the Pega Customer Decision Hub or what we refer to internally as the Omni-channel Decision Engine or ODE to determine the when and where to approach the customer with those offers.

We utilize the Omni-channel Decision Engine as a single real-time decision authority to provide transparent next best decision-making and handle the scale of operations. Our customer 360 approach will empower our frontline staff in our branches and contact centers to have more personalized conversations with customers and enable contextual interactions on self-service channels. But most of all, we're breaking away from always focusing on marketing offers to having conversations and to be able to focus on what the customer needs at that moment of interaction, which could include proactive engagement and delights. It's the theme song to my new favorite Broadway musical. It's not just about marketing offers anymore. Wouldn't we all like to be delighted by small tokens of appreciation during critical moments of truth?

Now, let me take a few moments to share the journey we've had so far. We are not new to customer decisioning. In fact, we had the original Chordiant decision engine running on our digital channels for over a decade. As that engine was hitting its end of life with no vendor support available... Thanks, Alan... we knew we had to adapt to the future, and of course the customer decision hub was a logical progression since Chordiant was the predecessor to it. For our initial implementation, we were live on our post-login web and mobile channels within weeks with a subset of our customers, which was a great start. And we've continued to build the program over the past three years to expand functionality to a range of channels.

As with any project though, there were a few lessons that we learned along the way. For a project of this scale and magnitude to succeed, you need the right combination of technology and data. We worked very hard to get our data to a fit-for-purpose state through our customer analytic record or CAR, and we worked even harder to make sure that we had the proper end-to-end technology execution capabilities at hand to drive that data.

There's also a lot of understanding and change that needs to happen when you bring in new technology. Change is implicitly an iterative, humbling process, which requires us to embrace the past while designing the future. The new decision engine comes with many more capabilities than our original one. Imagine we now have the Tesla of decisioning, which comes with self-driving capabilities. I mean literally self-driving. We have to learn to adapt and adopt this new way of thinking. This means as a firm, we need to learn how to truly adopt a data-driven culture of curiosity because for the first time, we're able to break down the silos between channel interactions, enabling true omnichannel decisioning.

Finally, new skills and education is the last pillar I have to stress. We need to account for the new skills and process differences that will occur. What makes this challenging is that during this phase of transition, we have to make sure that none of the lights go off anywhere. And in the mindset of a zero tolerance policy for execution errors, imagine that you're on a racetrack and having to change the tires of your vehicle while the car is in motion at fast speeds. That is a tall order. As an institution, though we have grown. We have held hands through the tough times and celebrated the successes. We can see the path ahead with more clarity than before. We embrace the challenges by committing to learn from them and well, we continue to understand that we will have to learn to face challenges as true with any change.

For instance, we now understand the importance of foolproof training modules for the ops manager, especially when onboarding new team members. I'm sure many of you CDH users out there can relate to that one. It's these types of large coordinated efforts that need to happen to get your project to full speed and scale. So buy-in alignment and agreement from all stakeholders and partners is critical to success. The results have been worth it. We have committed as a firm to challenge ourselves, and the Omni-channel Decision Engine offers us the opportunity to think of a data-driven future. One that is powered through insights at scale and focused on adding meaningful positive moments in our customer's busy lives. I also want to point out that our success is possible because Pega is not just a transactional software vendor to us. We're true partners sharing ideas and information to harness the technology in a way that is mutually beneficial. Thanks, Pega. Citi has successfully deployed the Omni-channel Decision Engine to our US Personal Bank post-login, web, mobile branch, and agent channels. We're at 100% traffic on web and mobile and are ramping in the other channels. We're now accelerating the adoption across other channels, so in the not-so-distant future, we can further our contextual customer conversations through true Omni-channel decisioning. Overall, I'm really proud of the change we're embracing by shifting to a client-centric Omni-channel experience. But our transformation is just a stepping stone. We're looking to use the Omni-channel Decision Engine to help us proactively engage with customers in a truly Omni-channel manner so that we exceed the needs of our customers no matter how they choose to engage with us. As a digital first company, our goal is to differentiate our digital experiences, and that means that we need to be able to resolve all customer needs digitally. But if and when a customer should choose to speak to us using an alternative method, we're ready to meet them in context versus having to have them start from the beginning. We truly believe that personalized engagement is always on and is the essential foundation for relationship banking. But before I continue to bore you with any more car and driving puns, I want him to take a moment to thank the entire team that has been working endlessly on helping make this vision come true. Starting with my own team.

My gratitude for their gratitude for their relentless passion and drive and never letting anything overcome their belief in doing what's right for Citi and for our customers. Thank you team. But it takes an army for any large transformation at this scale, and even size two font on this large 90 foot screen would not enable us to list each and every member of the Citi and Pega teams that have played a critical part in making execution for a program this size come to reality. Thank you all for your contribution to making this program a success.

Last but not least, Pega has partnered with us through our transformations over the past 40 years, and we are excited to continue to work with Pega to help us build the future of digital first client services. We've got a breakout session later today that will cover even more work Citi has been doing if you're interested. Thanks everyone, and I hope you enjoy your time here at Vegas at PegaWorld iNspire.


Industry: Financial Services Solution Area: Customer Service Topic: AI and Decisioning Topic: Customer Engagement Topic: Customer Service Topic: PegaWorld

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