PegaWorld iNspire 2024: Building a plane while flying: How PegaCDH is driving the ANZ Plus digital coaching experience for financial wellbeing

Smart, secure and designed to help customers manage their money and achieve their financial goals, ANZ Plus is a new digital banking service from ANZ bank. Since launching to the market in 2022, ANZ Plus is now servicing over 500,000 customers and is one of Australia’s fastest growing digital banking solutions.

This presentation will showcase how ANZ Plus and Pega CDH have partnered together to bring to life the ANZ Plus mission to provide customers with the tools, insights and support to improve their overall financial wellbeing. It will explore the ways ANZ Plus has rearchitected the customer experience by providing ‘digital coaching’ through scaling its Next-Best-Action library and adopting AI.

Transcript:

- So thank you all for joining me. I'm really excited to be here today to talk about ANZ Plus journey. It's a journey that I'm really passionate about, and it's very close to my heart. Now I know Alan just mentioned in the keynote that you all wanted to dial the heat up with all the great product announcements, so I thought I'll probably cool it down to talk about all the cool stuff that we have been doing in down under, and that's a hint. I'm from Australia, Melbourne. So I want to start with a very simple question. What should two plus two equate to?

- Five.

- Five.

- Five. I said five.

- Sorry? Five, yes. In my view, it should be greater than four, and that's what today is all about. How do you build a great product? How do you continuously enrich the product while still serving the customers? It's a journey about building a smart, secure bank that helps people manage and achieve their financial goals. All of you may not know about ANZ, but we are one of the big four banks in Australia, and it's an 180-year-old organization. We are serving more than 8.5 million customers with more than 40,000 staffs, and we operate in 29 countries. But banking industry has been going through significant changes lately, and at start of 2020, we were facing increased competition from traditional banks and emerging fintechs. The growth margins were shrinking. Our customer wanted more control and transparency. They wanted better and faster customer experience, but our technology was aging. It wasn't able to adapt to the changing business environment. Our products were difficult and complex to manage, and last but not least, there was a government-led inquiry into banking and superannuation industry that's called Royal Banking Commission that highlighted severe gaps in our controls and processes. Now think of it as if you've been living in the same house for a very long time. Chances are it'll require renovation. One approach is you start by renovating, say, start with your kitchen, move on to the living area, then the dining area, so on and so forth, or the other option is you start from scratch, build a new house that not only supports your current need, but it's also set up for success for your future needs, and that's the approach we took because digital transformation is not only about technology. It's about new products, new propositions. It's about people, it's about culture, and it's about technology. That's how ANZ Plus was born with the mission of building a substantially better Australian bank, one that provide tools, supports, and insights to support customers' financial wellbeing. The purpose at ANZ is to shape a community that thrives, and we put financial wellbeing right at the center of it because we wanted banking to just not be about moving money in and moving money out. We wanted customers to have more control about their money. We wanted to empower them. We wanted to provide financial knowledge so they can make better financial decisions, worry less about money and more about what matters to them, whether it's their life, it's their career, it's their business. So we developed nine financial wellbeing principles, and if you look at it, they're really simple. It starts with one small thing, spend less than you own. So you can put money aside for a rainy day. That helps you protect what matters most to you. You borrow within your means and pay your most expensive debt first. This gives you the stability to build towards your retirement while investing in things that grow, and last but not least, gives you the time to focus on what matters most to you. In order to deliver on these financial wellbeing principle, we wanted to build a small number of purpose-led propositions, products and propositions that people love to use that provide a great customer experience to them, and customers can derive more value out of their banking product. So we wanted to embed some non-banking services along with the small number of propositions. We wanted to deliver this proposition using mobile as our primary distribution channel while still maintaining human touch by providing a limited number of flagship stores and coaches who can support customers with their complex needs, all this to be delivered by a high integrity, highly automated platform, technology platform that has compliance built in and that can help us deliver faster and safer at the same time. We wanted to build a leading workplace and agile mindset within our employees so they can bring their best to work, and all this to be led by a purpose-driven and customer-centric delivery culture. So it can bring all the teams together in order to deliver what matters most. Now, having spoken so much about what ANZ Plus, our objectives and principles were, from marketing technology perspective, it meant we had to reimagine customer communication strategy. We wanted to move away from fragmented experience and siloed customer journey and engineer a cohesive communication platform. This is where we brought Pega in. We've wanted Pega to be the central brain that covers all the touchpoints of customer. Mobile being our primary channel of distribution, we wanted to, you know, provide experience right from day one. When customer joins ANZ Plus, we wanted to talk, you know, send them a welcome pack and take them on a journey with us, whether it's engaging them with the new products that we are offering that helps them improve their financial wellbeing, keeping them engaged and retained, and, in case they need any help, connecting them with the coaches so they can get the help that they need, doing all of this while still providing them with important service and compliance updates, like changes to their interest rates or terms and conditions on their products. The good thing was now that all of this was not going to be ready on day one. Now I know this may sound music to a lot of you, Greenfield implementation starting small, but there was a catch. The disadvantages were we knew that the number of use cases are gonna grow over a period of time, which meant we have to constantly balance building new capability to support broader business units while executing on the use cases that are coming in, doing all of this while ensuring quality and consistent customer experience. Now as they say, it takes a village to raise a child. Same was the case with us. Now, technology is one part of the puzzle. You need much more broader support across the organization. In our case, we had a really strong business proposition led by our business team, a great customer experience team, a robust data strategy, a simplified architecture, and a delivery engine that could make it work like a well-oiled machine. Now that was our plan to bring these forces together to deliver on the strategy. In order to deliver on these milestone and constantly balance these challenges, it was important to keep things simple. In the words of Albert Einstein, "Everything should be made as simple as possible but not simpler," and we imbibe this philosophy because we knew if we don't keep things simple, it's not going to scale. Now what does it mean? For us, it meant providing minimal number of interfaces to deliver actions. It meant minimizing the number of hops within the system, centralized operations to team that they can independently deliver. We wanted to bake in engineering best practices so the teams could deliver faster and safer. The goal was to minimize the cost of BAU change by using simple and scalable interfaces, and that's how we started our foundational journey. Our goal was when we launch our product, we wanted to engage customer in the first 60 days of their journey. Just a quick question. What do we do when we have to launch a great product? What should be our key focus? Any guesses?

- Customer experience.

- Sorry?

- Customer experience.

- Customer experience. Yes? Okay. Acquisition because you want to acquire customers and being a digital proposition, you wanted adoption. So we focus on the first 60 days of customer journey to bring in more customer, but the customers that we bring in should adopt ANZ Plus and love ANZ Plus. Now on the back of this, we wanted to like build three key elements, data, decisioning framework, and channel integration. Coming to data, we started with real time, so we emphasized more on real time events than batch data. In fact, our first set of use cases we delivered were on real-time events. So we went with event-driven architecture and followed cloud event open specification. This gave us an ability to unlock three variety of use cases. Now using events, you can trigger an action on a back of event. You can use an event to just capture data and not trigger and do any decisioning, and last but not least, you can look for an absence of event. To put things into perspective, when customers download ANZ Plus app, they have to go through an onboarding journey that takes about two minutes for them to complete, and our systems emit a series of event ask customer progresses through that journey. So when customer starts, we capture their basic details, marketing consents, things in real time. When customer completes the onboarding journey, we send them a welcome email, all within a matter of two minutes, and if customer drops out in between, we can also derive that context and send in abandoned cart. So using one simple interface and the power of data, we were able to unlock a variety of use cases, and we focused primarily on mobile app as a channel. So as part of first 60 days of customer journey, we have a series of highly personalized and targeted Next Best Action that we call as early month on book within the bank. So using this foundational capability, we saw up to 25% conversion on some of the financial wellbeing NBAs. As of today, we have more than 50% of our data attributes coming from real-time events. Currently, I think for the last six months, like if I average out across all the actions, we are sitting around 15%, which is still a pretty good outcome in terms of conversion rate. Now in terms of talking about business outcomes, we have 47% of our customers using at least one financial wellbeing NBA. So it really did help us, you know, putting that foundation in place that could drive that adoption and help us, you know, bring more customers in. Along with mobile app, we wanted to use email as a complementary channel, not as a primary channel. What I mean by that is for some of our financial and wellbeing NBAs or early month on book NBAs, we complemented mobile app with email as a channel. Using the power of data, we could identify which are the channels customers more active on. So we moved away from omnichannel to a mixed-channel strategy and leverage the power of data to identify the most appropriate channel to connect with the customer. Using that strategy, we saw an uplift of up to 10% on some of our Next Best Action that helped us drive further efficiency in terms of, you know, driving feature adoption. As of today, you could see on the screen we have a image of what Next Best Action looks like. It's called savings goal. So when customer joins, we want them to create a saving goal that links with our financial wellbeing NBA, and we call them as our hero features. So some of our hero features adoption across the board is around 35 to 40%. So pretty good outcome overall, I think, using just foundational pillars of data and setting up the decision framework and channel integration. Now, after working on this foundation phase, we wanted to identify areas of improvement and optimization that links back to our philosophy of keeping things simple. Now if you have worked in a decisioning or marketing automation platform, it's a very fragmented ecosystem. You have lots of tool doing a part of a function. In our case, when we started, we used Pega for decisioning, but we were using another platform to host the template and send emails. We wanted to, again, minimize number of hops, so we decided to bring email templating capability inside Pega so that the same team that is responsible for building Next Best Actions can manage the content and deliver, so helps us fast tracking and, you know, improving our delivery efficiency. To put things into context, our content verification testing currently takes minutes, and team is able to adapt to changing templating our content within a day. So overall, we saw 60% reduction in NBA lifecycle by making that improvement and linking up to a philosophy of keeping things simple. Another thing I would like to mention is around testing. So again, we wanted to centralize the testing function as well, so we expanded the use of Pega where the same team can build an Next Best Action right unit test case for Next Best Action but also for the data that is required for eligibility. So currently, our unit test cases and our regression test suite is all managed within Pega, which can be easily baked into CI/CD pipeline, again, helping us improve efficiency in terms of driving this outcome. Now, like I said earlier, two plus two should be greater than four. I guess at this stage, we felt it was equals to four. So it was important to work on what the next stage looks like that can yield results greater than and greater for the business. In this phase, our philosophy was, "The whole should be greater than sum of its part." How do you work across the organization, connect different systems together that can deliver really great outcomes for our customers? I like to call the stage a setup for scale. Now like I mentioned earlier, there were three key challenges for us. One was as business matures, there'll be new products added, which means we had to manage capacity, whether we build new capability or should we, you know, execute the use cases while ensuring quality. So it was important for us to carve out capacity for the team so they can tackle more complex and build new capabilities. So as part of this stage, our focus was that core team to focus more on the complex scenarios and build new capabilities while we enable and empower our business to manage some of the self-service use cases because in majority of the use cases, you have more high volume simple use cases and very low volume complex use cases. So we wanted to create that segregation. So on one front, continue building more capability, on another front, empower the business that they can take care of simple use cases. So again, using the principles or the foundation that we laid down for real-time events, there was a very massive program that we worked on. It's called Refer a Friend. The idea was that, as an ANZ Plus customer, I can invite up to 10 of my family and friends. Once they receive an invite, they can join ANZ Plus. They need to fulfill a couple of eligibility criteria, like create a savings goal, make transactions on the card, and once they do that, both the parties get a reward, and the customer who just joined as part of Refer a Friend can then further invite any of their family and friends. So we are creating a network effect on how do we get existing customers of ANZ Plus reach out to their family and friends, create that network effort so we can, you know, propagate the financial wellbeing message, and that can attract us and bring quality customers to the bank. So here, we moved from managing state of a customer using data to managing and orchestrating the experience across a network of the customers. So using the same principles of real-time eventing, we were able to scale the foundation without a lot of incremental workload, and this program was such a massive success that we saw 3X increase in onboarding through Refer a Friend during the duration of the campaign. As of today, we have ran three iterations of the campaign that has helped us with acquisition and also bring quality customers to the bank. But that's just one outcome, right? So in order to, you know, just to prove that how some of these foundational capability delivered greater results, so as part of this program, some of the foundational capabilities we built were managing relationship between customers. So whatever we built was reused for future products when we launch joint accounts, when we launch joint home loan application because it's all relationship driven, and the same capability could be used if your business wants to run Refer a Friend on home loans or any other product in the future. Another key win as part of this program was that this was the first time we had automated group payments. So the moment customer completes Refer a Friend journey, which could be within five or 10 minutes, each party can get a reward, which is part. So I think when we ran the first iteration, it was $50 within minutes. So this is how we joined forces with different teams within the bank to yield results greater than, you know, what it was expected. Now I've spoken enough about building the data foundations, bringing data into Pega, and delivering customer experience to Next Best Actions. It's also important that as the number of campaigns increase and Next Best Action increases, we wanted to push data out into the ecosystem so our marketing users or business users can leverage the data for measurement and optimization. At ANZ Plus, we follow data mesh principles. So we want to move away from the philosophy of centralized data lake where one team ends up becoming a bottleneck for everything. We want each domain to be responsible, own their own data products or data sets, and publish it and make it available for rest of the business. So in line with our principles of data mesh as part of marketing technology, we wanted to push interaction history that how customers are interacting with these actions back into the data ecosystem, again, using our foundational principle of eventing. So far, Pega has been consuming events. We just published events that was made available in the data ecosystem. Using the data mesh, I think it empowers the analyst community and the business users because it puts data at their fingertips. It's like Lego blocks. You have multiple Lego blocks available, and business users or analysts can build on top of it to get the data or create a view that they need. So we automated the reporting real-time dashboard, but again, there were much more broader usage of this foundational capability. Now, because we had the data available in the data ecosystem, we could easily compare. Let's say if 1,000 customers joined ANZ Plus Bank, did Pega send 1,000 welcome emails or not? So we could identify deviation in terms of expected results using the same dataset, and we also built reporting and alerting framework to identify breaches to our contact policy. Leveraging the same data set, we can identify that if we are supposed to reach out to a customer once in a week, are we actually doing that or not? So again, using one foundational capability unlocked different capabilities for us, and we're just not stopping here. As part of our data mesh principle, we also wanna bring Pega CAR onto the data mesh node of MarTech. The idea behind that is again moving away from those central dependency where, every time, business comes with a new use case that they wanna run a Next Best Action, a campaign. You go back to the central data team and say, "Hey, I need these four attributes." With data mesh principles, what we want is as soon as the use case comes in, each of the domains have access to their own data set, and we want them to push data into Pega CAR. What we want to build is a framework, a quality control framework that helps maintain the consistency of the data, but the ownership lies with the business team. This has huge implication, and I think it's gonna be an industry-first pattern where we are moving away from centralized data dependency to a more federated environment to add data into CAR that could be used for decisioning. And this is what I meant earlier that, as part of setup for scale, it was important to empower the business users that they can there build their own stuff so we can actually focus more on providing better platforms and better capabilities for them. So Pega CAR, we have just finished up the foundation, and over next two quarters, we are planning to run pilot with couple of source team to net out the governance framework and ensuring our quality standards are meeting expectations, and from there, we wanna scale it across the organization. Having spoken about the data, it was important that once data is available, business users can, you know, leverage the platform to build their own actions. So we launched Biz Ops, which is business operations environment that comes out of the box with Pega SaaS offering, and here again, the idea was that, you know, if we divide, look at the all the use cases that we have, about 80% of them are really simple but are high volume. It could be constant content changes that business expects. It could be just a minor iteration. You want to do an AB testing. You wanna send out a different content to a different cohort of customers. We want to empower business users to start taking advantage of the platform and build it themselves, and as part of that, we rolled out an early version of Biz Ops last year, which was just limited to treatment changes or content changes. This year in April, we launched the version where it has one-to-one operations manager that allows business users to create an action as well and to update an action as well. Now once you have delivered a platform that business users can leverage to build their own actions, you run into dependency bottlenecks, right? The biggest dependency in terms of building actions is, if the teams are ready and your data is not ready, what do you do? You're kind of creating a bottleneck for your central team because they keep on waiting for the data to be available. So in order to mitigate that, we build a functionality called Toggles. Think of it as switches, light switches. We can turn on, light comes on, turn off, light goes down. The idea behind this was that, after the inception and discovery session, the teams can have an alignment on agreement on what does the data structure looks like, and then from there on, teams can deliver independently. So Pega team can ingest the data, make the data available for business users, they can go ahead and build it in business operations environment, and we can safely deploy it using Toggles, and when the source team is ready, you can easily activate the changes in production. So this is, again, our commitment to constantly improve the delivery efficiency so our teams can do more work, create better platforms, better foundation that will help business drive better value out of the marketing technology stack. Using this, we have seen 2X increases throughput in our releases. To put things into perspective, last year in the first half, our team did about 40 releases, and in current financial year first half, we are sitting at about 120 releases by leveraging the power of these automated platforms and solutions that we have delivered for them, and we are just not stopping here. Now I know you have seen already a lot of philosophical line. I think in the words of Robert Frost, "We still have miles to go before we sleep." So we are constantly looking at areas of improvement and opportunities that we can automate more of things using Pega, using out of the box capability, continuing to minimize the number of hops, continue to roll out more simple and scalable interfaces, less of a rework, more about a forward-looking view that can iteratively add on one another to deliver better value. That's all I had for today. Thank you all for joining me, and if you have any question, I'm happy to take it. Yeah.

- [Sam] The presentation, I'm just interested see all sort of future plans. You talk about it being a journey. You obviously couple years into this. What does the next year or two years look like?

- Yeah, thanks, Sam. So as part of, you know, like I said, it's more about a renovation. So we wanted to build a house from scratch. So ANZ Plus started that journey where we wanna build up the foundation, we wanted to build up the modern MarTech stack and make it available so we can start migrating customers from ANZ onto ANZ Plus. We are still working. Like I say, we are building a plane while flying it because there are a lot of products yet to be built. So as we continue to enrich the product and platforms on ANZ Plus and as it gets ready, we're gonna start migrating cohort of customers from ANZ onto ANZ Plus. So that's what the next couple of years looks like for us, Sam.

- [Audience Member 1] Thank you. Nice presentation. A quick question on the roadmap plan for ANZ Plus. So I know this process is currently rolled out as self service, right? So what happens if the ANZ Plus customer comes back and asking questions to the call center, they come through the other channel? How do you actually expand the omnichannel experience for them?

- Yeah.

- Is the-

- Yeah, no, good question. So we already have all our own channels connected at ANZ Plus. For us it's primarily about scale scaling the platform that can meet the demands of across the business unit. In terms of providing that omnichannel or mixed-channel view, it's part of the business rules on how we wanna, you know, connect with the customers. So if customer calls a contact center and they're still eligible for the same action, we can serve it to them on the contact center while still continuing to push it on mobile app, but as part of our plan, we wanna roll out or test out more experimentation on how we wanna show content on which channels to see which channels are working most effectively, and it depends on the program objectives you want to achieve. So I think we have seen early month on book do pretty well when it comes to mobile app, and we are using contact center more for home loans and complex kind of, you know, use cases right now. In terms of roadmap, I guess the next challenge for us is to connect Pega to channel analytics. So we are working on how do we bring channel analytics from website and output into Pega so we can bridge the gap from unauthenticated channel to an authenticated channel by unifying the idea of the customer.

- [Audience Member 1] Okay, thank you, and where do you actually store all these data? Is it part of enterprise data lake model repository for predictive adaptive analytics? I hope you're doing predictive adaptive as well as part of NBA. I see that. The offering, the proportions, the propensity and the business rules, or are these kind of expandable, scalable in the future?

- Yeah, so, again, going back to the data mesh principle, so we are heavy users of Google Cloud, so we use BigQuery as our data repository. So leveraging the data mesh, it's not just one central team building different models. So depending on the use case, we have different lines of business building models on the data that is already available, and again, using the data mesh principle, it's easy for them to push the results of that model to augment or enrich the data that's already available in Pega, which is again sitting in BigQuery.

- [Audience Member 1] And what is the version of platform you're using?

- We are using 8.8 right now, but we are thinking to migrate or upgrade to 24.2 because it's coming with native connection to BigQuery and .

- [Audience Member 1] Got it. I would like to comment on the one you nicely explained as part of the delivery principle or efficiency, the release Toggle. Nice way, and then the unit test case automation pipeline, which everybody wanted to do. Thanks for great presentation.

- Thank you.

- Good afternoon.

- Yeah. Hi.

- [Angelica] I'm Angelica. I'm a journalist with the Australian newspaper. This is possibly related to your previous question, but could you talk about if and when ANZ Plus is looking at incorporating generative AI into your platform and how that will assist customers?

- From what I know so far, we are exploring few use cases in different lines of businesses, but privacy is at the center of what we want to do. So I know there's a lot of work happening to understand how we wanna leverage this and to what extent. I would say we are still exploring the opportunity, A, which are the areas where we could use, and second is how do we use it while still keeping things safe for our customers.

- [Angelica] And can you say which areas you're thinking about, like loan applications, for example?

- I just know that we are exploring few avenues, but I don't know exactly whether it's, I don't think so. It's gonna be customer targeted to begin with, even if it starts with it's gonna be more on the internal use cases to drive productivity, and yeah, not on looking at the customers right now.

- [Audience Member 2] Yeah. Thanks for the great presentation. Going back to the roadmap question, right? So how do you look at the roadmap from a line of business standpoint? So did you start with, say, retail banking or large corporates? Because retail banking is high on volume, but large corporates is high on the transactions that you have to do, right? So what is your roadmap, and what would be your recommendation for the people who want to start on this journey?

- Right, okay. Yeah, that's a good question. So for us, it was to start with the retail because that was what program priorities was, but I think one recommendation would be to working backwards from what business wants to achieve in what line of business and just working backwards right at the granular level on what are the building blocks that will help you get there and how you wanna sequence it. Yes.

- [Audience Member 3] Just at the start, you talked about ANZ Plus being a, what, Greenfield implementation. Do you have to have connections back into classic, and if you do, do you start running into some of the old legacy issues, and how do you address those?

- Yeah, so at ANZ, we don't like to call it as Greenfield. We call it as Bluefield because, yes, we do have some connectivity to the old systems. I think some of our core systems still operate within the bank, but we have seen very limited challenges when it comes to the legacy platform. Having said that, there's still few issues that we are constantly trying to optimize, but I would say for majority of it, leveraging the modern technology stack, like when it comes to integration, when it comes to, you know, delivering customer experience, it has been pretty well. Like one of the example I could give is when we started email delivery, we were using one of the legacy system in the bank. So we wanted to move away from it centralized the operation so it kind of, you know, moved towards more modern stack. What does that look like that we wanna scale in the future?

- [Audience Member 4] You talked about the event-driven strategy. You might have been showing a proposition on the mobile app, but the consumer might still be dialing into the contact center, and you might not really be able to capture the response for that particular proposition. So how do you manage that challenge?

- Yeah. So that's a good question. So I think depending on the type of use cases, like if I look at early month on book, et cetera, I think we consciously made a decision where we wanna target customer only on a specific set of channels. So we wanted to move away from that complexity because it goes back to the question of value versus effort, right? The likelihood of customer calling and for us to deliver that experience because I think call center is an expensive channel. To deliver that kind of experience on a call center doesn't make sense. It's better if customer comes back onto the app and fulfills this because our app has a lot of self-serve capability. So it's not like we need to call the contact center because they again will direct you to the app itself, but we are trying to work, like especially when it comes to home loan and other channels, home loan and other propositions. We are working on what does that omnichannel view look like for those high value propositions.

- [Audience Member 4] Got it. Second question is, in the event-driven view, it's a new thing for you as well for ANZ Plus. So once the thought came up of using adaptive models to really come up with the best offer that we can present to the consumer, did the organization face any challenge? Because I'm assuming it's a new way of actually throwing offers to consumers.

- Yeah, so we are not using adaptive models right now, and that's a conscious decision we made because I feel adaptive models are used to arbitrate between different business priorities. So when you have, say, a deposit product and you wanna cross sell a home loan or you wanna cross sell a credit card, I guess we are just entering that journey right now as we are launching more products. So now we are planning to bring adaptive models. So, so far, it was more about, you know, testing out your foundations on a limited number of channels by leveraging the power of data and analytics. It's only in the future we applying to bring an adaptive model, and obviously, I think technology is one part, which is comparatively simple. I guess it's more to do with the governance and how you wanna set up that process within the organization and bring that alignment across the business stakeholders that they support that vision.

- Got it, got it. Thanks. Thanks so much.

- Yeah.

- [Audience Member 5] You mentioned about of your financial wellbeing and saving goal was one of the . What has been acquisition strategy? It's all sales coming through the journey, like you take them for financial goal and then across open door? actually the product both. So normally how is the client journey, and how much is purely product, and how much is this venture goal in terms of where you see the ANZ company? Where does ?

- Yeah, that's a very tricky problem to solve, actually, in the marketing space, I would say. So we do have our go-to market strategy for a lot of our products, and it's really hard to measure what does a top of the funnel looks like and how much money you put in there. I guess what we are seeing is more like the last touch attribution right now where customer, you know, through diversified sources, they are trying to come onto a channel, and we are seeing the conversion rate, but obviously, there's a lot more to it. Some of the steps we are taking are, you know, bringing a mobile attribution platform into the bank. So especially if customer sees an ad or goes to a branch and decides to join ANZ Plus, so they can scan a QR code. So we know that okay, you know, attribution is coming from the branch. Again, if you're sending them an acquisition email and they click on the link, it again helps us track where customer is coming from. So this is what our next journey looks like that how do we go from last ditch attribution to start identifying what are the other potential areas that customers are coming from and what is their contribution towards the overall conversion? So. Yeah.

- [Audience Member 6] As you had mentioned earlier, you . So what is your basic approach? What's the scale NBA Designer?

- Yeah, we are using NBA Designer, but we have optimized a lot of our actions over past one year or so. So one of the example was when customer joins ANZ Plus, we were triggering an action called Fund Your Account, and it used to get triggered 24 hours after customer joins in. So we, again, did some test and learned based on analytics and tried to do it in real time. So now we deliver that within the first five minutes, and we have seen some further uplift on some of these actions.

- [Audience Member 6] policies. dictionary, so use of NBA Designer or how manually have to .

- So NBA Designer has been a pretty good tool for us. So I think a lot of this gets fleshed out as part of our inception and discovery process. So we have templatized the way we capture requests from business users, like what is their target audience, et cetera, et cetera, and majority of the rules don't need a lot of engagement policy or like when rules to be built in. It could be just part of your, I'm forgetting the term. It's called Expression Builder within NBA Designer. So we do have certain set of common rules that we apply at issue and group level, like marketing related, whether a customer is deceased or we wanna apply marketing consents or not. That applies at a group level, but otherwise, it's all at each and every action level, and it does get captured as part of our, you know, rules dictionary and the requirement templates that we have created.

- And usually, you create the actions just through NBA Designer?

- Yeah.

- Like how engaging the business user ?

- Yeah, so that was one of the friction point for us, and that's why we moved to one-to-one ops because that experience is much more simpler for business users to, you know, build an action on, you know, leveraging the UI, yeah.

- [Audience Member 7] Does it also take into consideration servicing communication or-

- Yeah. No, it's encompassing everything.

- [Audience Member 7] So is it multiple systems?

- One system.

- One system?

- Yeah. So that's why we wanted to move away from those fragmented experience and centralize everything in there. So when your arbitration or your engagement policy runs, it's keeping into customer account and from moving from marketing journey servicing to compliance.

- [Audience Member 7] How is it centralized?

- Yeah.

- [Audience Member 7] But how do you manage? Do you have any ? So in our bank, so we have each product.

- No, actually, Innovate has simplified things for us because everything flows through one platform, but the challenge, like I said is of the scale, right? Because if all the products is funneling through one platform is the same team working on it, and that's very important for us to, you know, roll out the self-serve capability that some of the simple changes can be managed by business users. As the number of products grow, I think we would have some complexity when it comes to the contact strategy and the way we wanna run arbitration. What if the number of services message is higher than what you can deliver to the customer? So I guess the way we are planning to tackle it is like bring in the channel arbitration strategy that if, let's say on mobile app we have figured out these are the five message all servicing, then route the marketing through an email or through some other channel. So I guess as it increases, we have to work with a strategy to meet that.

- [Presenter] So I'm conscious we're just out of time.

- Yes. All right.

- Fantastic, fantastic questions. I'd really like to just thank Karan for his excellent presentation. So thank you so much.