“In digital, if it's not convenient, you will not win” | RadioFinance

“In digital, if it's not convenient, you will not win”

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Senior executives in the financial services industry discussed how the rapidly changing digital ecosystem has necessitated players to design solutions around customer needs and preferences.

As digital transformation deepens, the management of banks is expected to transition towards a leaner, smarter and more efficient business model. Achieving personalisation at scale will become necessary for conventional players to remain connected with customers and enable successful digital journeys.

Aaron Loo, managing director of retail banking at AmBank; Kanags Surendra, managing director and head of transformation at CIMB; Reona Shimada, CEO of Crowdo; Ishan Agrawal, chief technology officer of Funding Societies; together with Ethan Wang, business lead Asia, and Nick Edwards, APAC regional director, of Temenos, shared their perspectives on how the shift towards digitalisation is necessitated by fast-changing consumer expectation for a convenient, inclusive and personalised experience.

Shimada pointed out that financial institutions should not focus only on existing digital capabilities, adding that for players to adapt and defend their market share. Data-driven insights and analytics powered by artificial intelligence and machine learning (AI/ML) will be a key differentiator for providing a superior customer experience.

Agrawal, mentioned that to stay relevant in the digital-first and cloud-native competitive environment, banks and fintech players will need to keep reinventing business processes and embrace technological change. Surendran noted that, although net promoter score (NPS) is still the benchmark indicator to see how businesses react to customers, players must innovate in creating new and effective digital journeys.

Loo added that enhancing real-time processes will enable a more frictionless experience for customers and drive further digital engagement. Edwards underscored convenience as the benchmark for successful digital experiences. Lastly, Wang noted that simplification of the delivery of digital services plays an important role in measuring success in providing a superior customer experience.

The panellists also discussed how industry players are embracing agile data architecture, cloud-native technologies, and advanced analytics to strengthen customer engagement and provide a highly personalised and differentiated experience.

The following key points were discussed:

The following is the edited transcript of the interview:

Mobasher Zein Kazmi (MZK): Good afternoon from Singapore. Welcome to our Radio Finance dialogue. We've assembled a distinguished group of senior executives from business and technology across leading financial institutions (FIs) in Southeast Asia to assess the next steps in strengthening operational resilience, increasing agility and being able to better serve customers digitally. I'm happy that we have a multifaceted virtual dialogue that look at the topic from both a business product and technology perspective. In recent times, the shift to digitalisation has been necessitated by fast-changing consumer expectation to bank whenever and wherever. Customers are taking cues from digital upstarts that offer frictionless transactions and unique experiences through multi-channel access and seamlessly integrated processes across varied needs, whether business, personal or wealth management. Despite the digital shift, many institutions continue to grapple with legacy technology and processes that impede their ability to aggregate and use data effectively. They struggle to scale and match their more digitally transformed peers that provide responsiveness, seamlessness and consistent experiences across channels. The speed of change is key for incumbents to stay relevant and survive in the face of the new digital-first and cloud-native competition. In this session, we will discuss and consider how some of the region's most progressive banks have designed their digital strategy to enable a more consistent banking experience. 

In terms of the topics of discussion today, we'll be looking at redefining business, operating and technology models to be more data driven and customer centric, integrating artificial intelligence and machine learning to create hyper-personalised customer experiences across channels and value chains, automating and building smart processes and IT services to increase operational agility, efficiency, resilience, as well as security and compliance. And finally, we'll be showcasing some best practices in terms of the implementation of agile data architecture, cloud native technology and advanced analytics. I would now like to take this opportunity to introduce our guests. We have Aaron Loo, the managing director for retail banking at AmBank in Malaysia. We also have Reona Shimada, who's the co-founder and group CEO of Crowdo. With us as well is Kanags Surendran, managing director and head of transformation at CIMB. Included in this panel is Ishan Agarwal, chief technology officer at Funding Societies. And with us as well is Nick Edwards, APAC regional director at Temenos. Joining him as well is Ethan Wang, who's the sales lead Asia at Temenos. 

Before we get into the questions, just to give a little bit of context and background in terms of the digital transformation, as we see it deepening the management of banks that we see in terms of their transition towards a leaner, smarter and more efficient business model. Digital transformation has the potential to allow banks to capture a much larger amount of data from an increasing number of sources and to better utilise this data to aid in terms of business decision making. It could also facilitate particular banks in terms of reducing their own costs while increasing both operational efficiency and revenue through innovation in products and services and distribution channels. And more importantly, with the right implementation, customer experience can be greatly enhanced. But underlying all of this, of course, is the power of modern technologies that unlocks numerous possibilities. And banks in the region are making those efforts in terms of the digital transformation as a means to gain a competitive advantage and of course, naturally capture a bigger share of the market. To this end, the majority of lenders have either implemented or are in the process of deploying that agile data architecture with cloud-native technology and advanced analytics to drive their business forward.  

To begin with, we'll look at redefining that business, operating and technology models, and I think generally to keep up with the changing times and to stay ahead of potential disruption, the business models of banks, especially as they relate to the front office, operations need to be adjusted. In addition, modernising your internal systems is one element that can help facilitate the development of personalised omnichannel products and deliver a better customer engagement. To kick things off, we'll probably begin with Aaron and in terms of his experience at AmBank. If you could share with us what competitive advantage that you see in terms of banks, building that data-driven, personalised products and services, and how this is being used for customer acquisition and retention. 

Building the personalised digitisation journey for the consumer

Aaron Loo (AL): What we are seeing really is the usage of digital to really drive a seamless customer experience. It seems easy to say, but it's actually pretty tough to execute. And the reason why is because, especially if you look at the institution I'm working in, we have tremendous legacy systems that we have. For me to do a single change to integrate a single journey for clients, I'm talking to five to ten different systems. That is a challenge for us. And I think that we are now working towards trying to start figuring out how do we develop the capabilities or enablers to allow us to build the right journeys for our clients to address their needs. And the needs are different. When I think of digital, it's not one big blob, it's what are the journeys I'm trying to build, for example, for gig economy workers, or how do I build a journey for micro, small and medium-sized enterprises (MSMEs)? Or how do I build a journey for mass affluent customers, and so on, so forth. And I think that we have today the ability to enable us to do so but it's a journey to get there.  

MB: I'll also ask Kanags to weigh in, in terms of his thinking about how you can actually leverage data. Has this been the experience also at CIMB? 

Kanags Surendran (KS): Every bank across the world is in some stage of figuring out how to wire or rewire the legacy platforms to create a solution that is appropriate for a customer journey. It's a legacy of not just putting the blame on technologies or platforms, but also legacy in terms of cultural mindset, in terms of how banks have operated in a very product thinking rather than a customer-centric thinking. When you look at customers, obviously, you look at customer journeys. And when you look at journeys you have to have the capability to address a wide segment of customers, and take them through the journey. And that's where data personalisation comes in. For banks to get to that scale of a segment-of-one journey is where the challenge and opportunity really lies. And to arrive there at a place or a point where you're able to achieve that at a really low cost to income ratio, where data and personalisation journeys do not end up becoming an operational overhead is going to be the challenge. Every bank has got its own challenges. How you get through that process over the next few years is going to be essentially the competitive advantage for the next half a decade at least. 

MZK: Looking at it from a fintech perspective, Ishan, perhaps we can pass this on to you as well. Kanags mentioned that segment-of-one marketing and the challenges we're seeing in terms of the gaps, at least from the conventional side in terms of delivering those data-driven personalised financial services. How do you see at least the digital-ready counterparts in terms of addressing these gaps, Ishaan? 

Ishan Agrawal (IA): I really like what Kanags mentioned that there's a difference between product and customer thinking. I think traditionally, financial products have been more constrained by what are the internal limitations that will offer this kind of product with these interest rates and so on. But customers don't work that way, right? In our business of SME digital financing, we realise that every SME is unique. So, we cannot offer them a standard bundle of products. Neither can we assess them in a standard scorecard way. If you think of consumer products, Netflix doesn't behave that way. You don't see a set of stuff, like it's heavily personalised based on your viewing experience. So that's how we've tried to think about it at Funding Societies.  

I think the advantage that we have as a fintech is that we do not have a lot of legacy to deal with. We have systems that are native to cloud and use modern technologies. One of the examples perhaps I can give is, we build something that we call Smart Application. The idea is that application form adapts with each new piece of information that we give it. And it's enabled by continuous risk scoring in the background. Those are some of the personalised experiences that we're trying to build for our customers. 

Reona Shimada (RS): In terms of how we're dealing with it, so maybe two examples. One is really changing what delivery means. We never believe that a customer needs to go to a branch or even for that matter, they don't need to go to a financial super app. On demand for us means that relevant financial solutions are prompted trigger points that even business owners wouldn't typically associate with financing. And that could be signing a contract, it could be issuing an invoice, issuing a purchase order, and so on. We're able to prompt and push financial solutions through digital means so that the business owner at that relevant point of time becomes aware and can consider these financial solutions. The second is really around data insights. I think that a lot has been said about no alternative data sets, and so on, I think it's now a given in this day and age. What we're really focusing on is getting data insights through becoming an embedded financing player, really acting as a digital middle or back office, so to say, for all these SMEs, so that we have proprietary insights on their business performance, business cycles, and so on. This is a great way to really customise, truly, the experience for each of our SME clients. 

MZK: The crux essentially is really to have that personalised experience for customers. Given the nature of this, at least the innovation and change that we're seeing, which requires redefining business, operating and technology models, it also necessitates a rethink of the traditional structures and hierarchies in business culture.  

My next question is around technology and leadership, and that relationship that exists in terms of how that can help drive the change, especially in terms of the conventional constructs and mindsets for the traditional players and how they can embrace this change. Kanags, perhaps we'll start with you on this one. 

How can banks better prepare themselves? Should we be expecting this permanent state of reinvention now? What does true digital innovation mean and how does it resonate with customers? What's the interplay between leadership and innovation? 

Improving design thinking and having an agile mindset play an important role in moving faster to market 

KS: The permanent state of reinvention, I guess we're always in a state of change. The world is moving, it just the pace of change has increased in a tremendous way since the digital revolution, or since the time we had a chip that is faster than the Lunar Module on our hands, probably four times as fast as that in our hands now. Essentially, it's Moore's law in action, if you will. It's the pace of change that is changing. There's a double whammy here. One is in terms of the organisation's ability to react to the change, number one. Number two, react to and keep up with the pace of change. They are two different things. If I were to look at it in those two lenses, first is reacting to change, I guess the way things are moved in this fear with the fragmentation of business models where an organisation, why is it able to achieve cross-border transactions at a price which is so competitive compared to traditional organisations. It’s because of the focus that they have. An organisation such as ours, we are a universal bank, and we have 20 different products and building different variety of services, the need of ours is the ability to focus on what is right in terms of a strategic outlook and stay with that focus and and fix that and stay competitive in that particular area. That's number one. Number two is really mindset. There is no more, in my opinion, a phase where you can say, technology is technology and business is business, they're pretty much interlinked now. Businesses are operating in the world of technology and technology needs to understand what the business imperatives are. You need to find people who are able to operate across the spectrum. And you're either a digital native or a data native. And finding these people is a second challenge that needs to be resolved. It's not just having the cultural mindset in the organisation but having the talent pool that is able to operate across these two dimensions and being able to scale. That's number two. Three is the pace of change and to continue to operate and be at the forefront when the pace of change is really high. The way banks are wired and the way we operate need to also change. And that's where we talk about design thinking, we talk about agile mindset and agility. Those things obviously have to be in place because you have to get out of your tech that have legacy platforms, but at the same time, be able to move fast. Agility is not just having the technology platform, but also in the way we operate and the way we are set up to operate. Fundamentally, organisations like us need to change across these levers for us to really be competitive.  

MZK: Ishan, your thoughts in terms of that permanent state of innovation and reinvention, and looking at how you can really consolidate that to provide digital services that really have gained traction with customers. And looking at also the importance of leadership really, and having that cultural shift, or a change in mindset. Any thoughts you would like to add in terms of how this can help businesses and banks, particularly in terms of redefining how they're approaching or thinking about technology and innovation?

IA: I think to build on, the pace of change has been just mind boggling. One of the examples that comes to my mind is a period of four years, 2007 to 2010. In 2007, iPhone came out, which changed the devices that we were operating on. In 2009 was the Bitcoin white paper, which opened up a whole new Pandora's box of just some exciting stuff that we're starting to see a lot more of recently. In 2010 was when Google announced its autonomous cars, which I like to think of as the advent of modern AI, stuff of the AI as we talk about it these days. In just a span of four years, you have these three key landmark events. Since then, there's almost on an annual basis there is exciting stuff happening, but we'll only know in the future, whether it's AR/VR, or a bunch of exciting stuff, metaverses. We only know in the future how that change things. Since the pace of change is so fast, I think the only option is to keep reinventing yourself as a person as well as an organisation. That's the role that I play as a technology leader within my organisation. And I think that's the role that some of us play within our organisation as well. There's no sort of alternative and then making sure that you're reinventing yourself. Even as a fintech, which is about six years old, we start looking at it and we're like, hey, things are changing in the past six years, and then we have to keep reinventing ourselves. So, I can imagine this is a thing that's quite important for the bigger organisations as well. 

MZK: I'd like to bring Ethan in on this as well. Ethan, we've been speaking about the pace of change. What does this mean for all the financial service players, in terms of them being able to build strong customer relationships? And given this pace of change, how can they be positioned to provide a very consistent digital experience?  

Seamless omnichannel experience and easy integration with complicated ecosystems

Ethan Wang (EW): I think technologies involving customers behaviour has been changed a lot and is still changing. Digital firms also raised their bar for customer experience. And as Aaron mentioned earlier, easy to say and tough to execute. I would like to share two of my observations. The first thing I think, we heard about some keywords, personalisation, engagement, data driven. When banks are trying hard to invest complex technology portfolio these days in digital, another important keyword I think is probably I call it simplification. How to simplify the customer journey as well as the staff journeys using digital technologies. How to simplify an omnichannel experience across different digital touchpoints including onboarding, for example, and how to simplify the way that customer insights was being delivered from the backside and even how to simplify your staff, the bank staff experience by managing all the digital channels, security alerts, and also the customer requests. That's my first observation. The second observation apart from the word ‘simplification’, I think ‘measurement’. Measurement is something playing an incrementally and increasingly important role in digital, so how to measure the efficiency and also the financial and non-financial value of banks, let’s say digital onboarding, customising sites and even non-banking services so that a bank can potentially continue to improve their digital customer journeys. A digital banking platform with all the seamless omnichannel experience and easy integration with complicated ecosystems, that's what I see can help banks to simplify their customer journey and potentially making customer buying more products from the bank through the digital channels. If a bank can fix it from the very beginning in the development, I think that they are probably in the halfway to the success to maintain and improve their overall customer relationships through digital channels.

MZK: We're speaking about how banking is becoming quite invisible to the end user. Given the saturated environment now for most markets in the region, there is this pressure on profitability and bottom line numbers on cost control. That's really, as we've been discussing, fast tracked or has pressured banks to really accelerate their customer engagement efforts. One way, we've been speaking about the application of these emerging technologies, but specifically, if we look at AI and machine learning (ML), how these can be deployed to enable customer engagement and achieve that personalisation at scale that we've spoken about it earlier. Kanags, I wanted to get your input on this as well in terms of how you see this space evolving, and what banks can do or the various players can do in terms of leveraging or utilise these capabilities to drive better products services and being able to connect with their customers better. 

Customer-first strategy in deploying AI/ML 

KS: AI/ML is again an overused and underutilised word inside banks. And we are probably just scratching the surface on this. To achieve personalisation at scale, you will not be able to achieve personalisation at scale at the cost point that is meaningful if you're not going to be using an AI/ML-based technologies. That's fundamentally the first rule of law when it comes to this and cost. The second piece is not just about implementing but figuring out what you're going to use these technologies for and why they make sense. Rather than talking about why a technology is relevant, the right thing to ask is, what is the business outcome that is actually being solved for and what appropriate use AI/ML technology that's going to solve and provide for. That should be the way to approach this rather than force fitting a square peg into a round hole, which is probably what is happening across most organisations right now. The place where at least we have tried using this is specifically around database personalisation and real time personalisation that we have been engaging with over the last year and a half with our customers. It's been quite useful because when we are able to track how we are able to increase usage for some of our products with a customer, some of the solutions with our customers based on these personalised interventions that happen on a real-time basis. It's quite phenomenal what you see in terms of the uplift in both customer satisfaction and Net Promoter Score (NPS) as well as top line, because of the customers using your product. It sustains even after you stopped that particular engagement for that customer because they have seen that relationship being a lot more meaningful, which is what these capabilities and these technologies enable us to provide.

MZK: Ishan, your thoughts also in terms of utilising AI/ML from a fintech perspective in really driving customer engagement.

IA: I think one of the points that I mentioned earlier is a good example like the Smart Application that we were able to do. But the way I see AI/ML is, if you've implemented it right, it should just be obvious. Like you were talking about banking being invisible. If you've implemented AI/ML right, the customer shouldn't care about it. The customer really doesn't care what technology you're using, at the end of the day. That's kind of our problem. Similarly, like when you use Google Maps, you don't really know what technology is behind it. We try to think of it that way as well, keeping the customer first. And if AI is required, sure. If a simple piece of code does the job, sure. I think sometimes we oversell the whole AI/ML aspect. While I think there's tremendous use cases. I'm not denying that. But I think there's also a strong need to look at what the customer needs, and then just kind of build those solutions for the customer.

MZK: Reona, your thoughts in terms of how they can also address those customer pain points and these advanced analytics being used as a differentiator.

RS: Our hypothesis has always been that improving customer experience is not only about making the funnel more efficient, but using AI/ML to get more people into that funnel. The challenge that a lot of the conventional banks actually face is that despite the high rejection to mean loan applicants. We see 40-60% of SMEs of our sample as being denied loans. And this is for a segment which has close to 5-8% non-performing loans (NPLs) for the last like 12 to 18 months. It doesn't really encourage a lot of banks to open up the funnel due to the risk and return profile. From a customer's point of view that the pain point is clearly that they just don't get into that Promised Land of getting into a funnel where everything's personalised and everything's customised for them. We really view AI/ML as a critical way for widening that customer funnel, the entry point, and using it as a key differentiator. 

MZK: Nick, looking at the application of AI and advanced analytics, how do you view this in terms of providing a safer, more robust set up for financial institutions? And what value does that provide in terms of potentially new digital opportunities for both banks and fintech players? 

Advanced analytics as an enabler of frictionless engagement between the bank and customer

Nick Edwards (NE): Probably the first point to make is that I agree, I think Ishan was saying before, AI/ML can be a bit of a tagline, a bit of a trend. I think that's true. I also think that it's not new in our industry. Using advanced analytics and computers to execute those models has been done for many, many years. What's different now is this level of sophistication, the kind of use cases that you can target, and the kinds of tools that are available to make this more accessible across a banking organisation or indeed an ecosystem for that matter. How does this make it safer and more robust? If we take an example, I'm going to use the lending decision, it’s probably the biggest, most important decision that banks make day in day out across the world. And in the past, if I get credit will be a function of how well I know the bank manager. That was then superseded by a branch transaction that was back ended by a paper process in an operations team. That kind of a process is open to bias. Everyone has bias in how they interpret information. That kind of a process is slow, it's expensive. Kanags before was talking about the efficiency that's available now. And that kind of process as well, because it's driven by humans, can only consume so much data that we can that we can comprehend. And as a result, the outcomes of those decisions aren't necessarily optimal or the most predictive. If you kind of fast forward, in some banks today, and for other banks, the opportunity that exists in the future, that kind of end-to-end process, if it's underpinned by automated decisions, and the right kinds of technologies and models, throughout that process, we got an opportunity to reduce bias, to reduce the costs and the speed at which the decisions are made, giving you an opportunity to scale, giving you an opportunity to reduce the cost to serve and consume infinitely more data. It's interesting, listening to Reona, talk about the kinds of data that are looking beyond the traditional data sources to broaden out the funnel. And all those things are huge opportunities and provide us huge upside in terms of security in our industry. That little example there can be extrapolated across the board, across KYC, across portfolio management and marketing chatbots, many, many more. The potential is huge. There's no doubt about that. But probably, for me, the thing that makes this relevant for this conversation beyond anything else, is that it's an enabler of convenient interactions with a bank. And for me, I'm very passionate about this. In digital, if it's not convenient, you will not win, you will not win your customer, you will not win their loyalty because it's too easy to change. And so for me, above all of those things, that opportunity now in the future, with these technologies and other technologies is about what is the optimal convenient experience we can enable for our customers in that digital channel.

MZK: If it's not convenient, you will not win on digital. And I'd like to bring Aaron in on this because it's quite relevant in terms of how banks can help their customers to complete these complex digital transactions and ideally in a seamless, frictionless manner. Aaron, your thoughts on that convenience piece, and essentially ensuring a frictionless digital experience for customers. 

AL: First of all, I really like what Ishan and Nick mentioned earlier, AI/ML is really an enabler for us to implement something, or timely convenience or timely intervention for clients. I look at it in two dimensions. From a client's perspective, and Kanags had mentioned earlier a little bit about creating real-time interventions to the client in a timely manner. For example, things that we are working on now or my end, quite similar to what Kanags is looking at is just going through the client, users or transactions and trying to understand and identify things like if it is timely. For example, you have a little bit of excess cash, you spend a little bit less this month than you normally do in the last couple of months, can I encourage you to move it over to a more higher yielding depository product, or to save it for a future rainy day, in a small unit trust fund. Or, for example, remind you to pay your bills. I think these are things that are real time and useful. It creates a personalisation and brings the engagement of the client. If you see when you have high engagement levels, typically, from our data anyway, we are seeing product holdings going about maybe 20% higher on a blended basis. If you're moving up the food chain or higher up in the value chain, it could be as high as 30%. Those are things that I think are really positive in terms of enabling this sort of timing interventions using the right capabilities. The other way I look at is also from the bank's perspective, I think one of the things I think, a bit hard for us and I think some some of the panellists mentioned about, how do we intelligently underwrite some companies or some individuals. Because the traditional model that we are seeing is beginning to really shift. You're seeing the gig economy starting to come up, a lot more different types of economies are starting to grow, social media influences, part-time income coming in. And the traditional underwriting models probably don't really capture that as well as we'd like to. And so it's really using capabilities to first understand something as simple as can I use social media information that is so readily available out there to figure out whether when you apply for a loan for me, can I use that to figure out whether your credit is good, rather than a traditional way of let me look at your income dock, let me look at your bureau score, let me look at your negative bureau, and figure out whether you are a great customer for us to onboard. So those are things that I think we are looking at to create a more frictionless engagement between the client with us. On top of that, it's really about something as simple as onboarding. I'll give you an example. It's also about the mindset channelling, it's also within the organisation, the mindset change to do this, it's not just the technology. It’s the entire organisation. The product managers, the risk managers, the compliance guys, we had to start really rethinking the way we traditionally look at things in order to execute these. A classic example is, we launched this ability to onboard an SME fully digitally. But we faced a bit of a snag, this was already quite a while back, we faced a snag because the regulation said you need a signboard resolution stamped by the company secretary before you could do that. We took a while for it to get through. But we get past that obstacle. And that kind of extends really to that larger, whether the regulations of the land that we operate in are even ready to start help enable these experiences for our clients.

MZK: Reona, from your side, if you'd like to also share with us in terms of how you've approached this, and probably just follow up also on the points you were making earlier in terms of the application of AI/ML, but broadly in terms of advanced analytics and how are you using that to survive. 

RS: Okay, thanks. We really use AI/ML as a differentiator to really widen the entry point. This is by using alternative data like Aaron mentioned, but also about getting deep in propriety data as an embedded finance player. The numbers really speak for themselves. On a comparable basis, the approval rates, you can actually improve your approval rates by two to three times now versus traditional banking acceptance rates. You could achieve this without any compromising credit asset quality as well. Our NPLS are 40-60% lower than the banking sector on the comparable period. You could imagine a world where you combine all initiatives on this panel, one is widening the entry point, getting credit-worthy customers digitally through the door. And then you have the timely interventions and also the customisation recommendations that Aaron and Kanags have also talked about. I think that's an amazing potential of really using AI. This is something that customers truly appreciate. I could tell you with 80-90% retention of new customer monthly cohorts, that basically means that, look, they don't see it, they don't see this AI engine and so on, But customers, once they actually go through the experience, and once they do appreciate it through financing to grow their business, and so on, once they enter the system, they just never leave. And I think that this is something that is important, solving customer pain points and improving business as well. 

MZK: Kanags, if you'd like to weigh in as well in terms of how you're applying this and what results you're seeing in terms of the service enhancements and the improvements. Certainly, there's been a great deal of automation, like the deployment of smart processes, and we discussed that earlier as well. From your perspective, in terms of having that agility, the efficiency, would there be specific results that you would share with us from CIMB’s perspective, Kanags?

KS: Automation AI/ML is a very broad spectrum and solutions inside banks would vary from simple back-office automation all the way to front-end eKYC solution, which is still reliant on, your facial identification and a whole bunch of other parameters. Of course, there's fraud, there is scoring. There's a lot of different applications. I can talk about two specific areas. One is simple automation using robotic process automation (RPA), which has significantly reduced the amount of time it takes for us to gain data into our loan origination platforms, especially when we talk about SMEs and mid-sized corporations, when we have to issue loans of ticket sizes about MYR 1 million ($240,500) and above, you need to have a way to process their bank statements, their financial statements. Those are non-value-added activities that you're forcing humans to put up with, when you have enough RPA and optical character recognition (OCR) systems out there that can do a better job, and you upskill these resources into doing something a lot more meaningful. That’s one simple area that has shown tremendous outputs. The second one is using eKYC for onboarding new-to-bank current account and savings customers. Thanks to Bank Negara’s new policy we were able to do that. And that obviously needs facial recognition and needs the ability for us to compare and authenticate your identity card (IC) that it is actually the right card and is not a forged one, as well as compare your face against what is on the card. Those things are again AI/ML solutions, which we use to speed up the process of onboarding new customers into our system. 

MZK: Can you give us a sense in terms of the impact these service improvements are having on your costs or potentially your profitability? Perhaps impact in terms of incremental revenue? How are you measuring the success of this internally?

Focus on the business outcome to measure success

KS: Any other day, any digital project or any transformation project needs to be focused on business outcome and not a tech-for-tech, which is not what it is. When you look at, for example, the SME loan onboarding platform cloud journey that we looked at, our aim was to reduce the turnaround time for these loans from what used to be four to six days now on average for our customers. These are loan sizes about $1 million and above. Those used to take a really long time. And by creating a journey that has digitised a solution for our sales staff, as well as reduced the need for the sales staff to meet our SME customers face to face in this COVID-19 environment. The streamlined OCR in the back-office processes, it has reduced our turnaround time quite a bit. That obviously means improved productivity because you're able to pre-score, you are able to pre-analyse these customers so that you don't have to send an application to the back office to see only two get processed. The relationship manager (RM) upfront knows which of these is going to get processed or has a better probability of getting processed. He's able to focus his efforts as well. So it's productivity benefits all through across the whole chain. Same thing with with eKYC again, enabling that solution, we get about 10% of our accounts open per month right now from our eKYC solution in Malaysia. That obviously reduces footfall in the branches, which has helped us take away that cost associated with that opening that account and it's completely made that digital. It's not really a cost game over there, it's about a skill game that has to be played. Because once you digitise obviously cost is going to go down, but it's the ability to scale that is critical.

MZK: Ishan, perhaps you can share your perspective on that and give us a sense also in terms of how you see the impact of regulation, potentially around data as well and security. Given that we could potentially use advanced analytics more ethically. And you've got different jurisdictions looking at it from different perspectives. 

Challenges to building customers’ trust with digital experiences  

IA: One of the things to be aware of is, for example, I think we all talked about AI there. If you're looking at credit scoring, like AI, of course, is a product. You can have things like deep learning, which are slightly more relevant for facial recognition, text analysis, and that kind of technology. But when you feed in a lot of data to a deep learning model, you are actually not quite sure of how the accuracy or you know what, what led to a certain prediction, that may even introduce a certain bias, which you're trying to remove from your underwriting models. And it is pretty much a black box. If there is any conversation with the regulator, you basically can't say that what actually led to the result. You definitely have to be aware of what kind of regulatory requirements are there, how do you enable the implementation in the kind of environment that you're in. For fintechs that is very important. I think when we're making these technology choices, we also have been very aware of the regulatory environment. And similarly, for security, I think all of us in the call are in the banking space. And trust is a huge aspect of what we do, building that trust. When you move these experiences digitally, building that trust becomes much harder. Because you only interact with a website or an app, you're not seeing anyone in person. Whether it's through KYC or applications and so on. I think cybersecurity plays a huge role in building that trust out with your users. It can be through small prompts, while they're in the process of application of a loan or onboarding on to an account where it could be small prompts, it could be constant engagement with the users reaching out to them via various channels on what are you doing in the form of cybersecurity. It's very common to hear a hack happened and millions of users’ data is lost. In the long run, it does hurt your brand a lot, and the value of your company as well. This is something that especially startups tend to take a bit lightly, but something that I feel like we've sort of thought about a lot and invested very heavily in.

MZK: Absolutely, I like to get Reona as well to weigh in and looking at it from those potential risks that fintech players would need to be across. We had Ishan also bringing some very good points, especially around trust. Reona, your views in terms of how we can at least create a system or setup that is not really unfair or discriminatory for customers and really wanted to understand what your thinking is around that. Is this a priority for you as well in terms of preventing biases?

Understanding the interdependencies to prevent biases

RS: Either you're refining your data, your credit quality and credit scores are getting so accurate, you just know that the model is creating it's bias towards a certain segment or certain attributes. Or you get into an area where you just don't know what the results are. There's no perfect answer, but the way we've dealt with it is really by expanding or understanding the interdependencies between what looked like independent communities on the surface. We focus a lot on supply chains. You can say that look, if we deal with trading companies, those trading companies are linked to manufacturing companies, logistic companies, and so on. Expanding through some kind of interdependencies is a way that we don't just focus on trading companies. I think that's one really good example. I think it doesn't need to be traditional businesses which are in the traditional value chain or supply chain. It could be independent merchants as well, but sitting on independent merchants, broadening out to online marketplaces where there are related categories and so on is another way to branch out. It's really acknowledging first that there are biases, your AI/ML is not perfect. But really just kind of like having that manual hand to guide the development of the AI, so to say. I think that's the way you basically negate the biases that the system is creating. 

MZK: We spoke about the biases, we spoke about trust as well, getting the digital proposition, the digital experience right is of course fundamental and critical. You learn to navigate all these potential pitfalls. It's essential. I wanted to get also your thoughts, Nick or Ethan, on this.

EW: So eKYC, onboarding and automation, visual connection, I just think there's one thing I probably want to add on in terms of process automation and other things. For me, what is critical, it's not just about how to automate the process, but also it's about how flexible the digital infrastructure can make all the changes to the process into the future. As we know, the customer requirements are changing monthly and daily, the onboarding, workflow, all these sort of things are changing, and the ecosystem is changing. We need an infrastructure to have the flexibility. That's what we've seen in the past and also now, for banks to have the flexibility and also the scalability to potentially adapt the changes without disrupting the customer experience. In the end, the bank can potentially help to enable the frictionless experience today and also tomorrow. 

NE: I think the only other thing I'd add, and just kind of reflecting on the conversation and the different perspectives of incumbent banks versus fintechs, as you hear in particular from the fintech perspective, it's a little bit more around digital banking is not just around banking. And I think it's super interesting to think of the risks for our industry. And let's face it, our industry is a super risk-averse industry, as we are led outside of the train tracks that we've spent the last 200 years in, and really fast. And I think that it's inevitable, it comes back to my point around convenience. But it creates a huge shock factor potentially for banks, some of the more progressive banks are there or getting there. We speak with lots of banks in our jobs. And I can tell you that there's a huge middle sector in the industry that is far more traditional in their thinking, and when they have to get to that point of change, and we were talking before, rapid change, that cultural influence is going to be super important. 

MKZ: Looking at how rapidly and how quickly we've been speaking about this change and how this ecosystem has been evolving, in getting that experience right, getting the digital journey right, of course, has necessitated a rethink by financial institutions. And important, of course, connection that we need to draw is the use of agile data architecture, cloud-native technology, what that means in terms of being able to aggregate all this vast amount of data, and to really drive that superior customer experience and to build that personalisation at scale. Given all of these advanced analytics, I will probably bring in Aaron on this one, if he could share, some of the use cases or best practices that have also generated very successful customer journeys in terms of the application of agile or cloud native or advanced analytics. 

Using advanced analytics and digital solutions amid the existing legacy systems 

AL: So, to me, if we look at, say cloud-native technologies, it’s an area that I'm actively exploring right now because when I look at the capabilities that some people call it fourth generation core banking solutions and the ability to hyper-personalise a product from the client's needs perspective, it's actually quite interesting for us, because that then allows the clients to actively manage his own personal finances without having to talk to someone at the branch or to even restructure his loan, for example. It's interesting for me, because what we are seeing evolving outside of Malaysia, and in some ways coming to Malaysia, abilities for, for example, customers for something simple, take a personal loan. Right now, if you wanted to change your tenure, change your interest rate, restructure it, it's actually quite difficult, you have to talk to someone, sign a bunch of documents, and then maybe we'll let you do that. What we're seeing coming on shore is complete ability for them to choose what they can and want to do. They can choose when they want to pay, what dates they want to pay, rather than a bank telling them when to pay, they can choose a payment holiday. I want payment holidays, then I want to maybe actively say instead of 24 months, I want 36 months, then a couple months later change my mind to 24 months. That's just one use case. We're seeing that coming in and that's the competition. Now the question is, how do we then compete on that one, with the capabilities that we have. That's why we're starting to explore looking at cloud native, for example, as well as advanced analytics, where we are then able to then mine the data that makes up tremendous amounts of data, we just don't know what to do with it. So that's where the advanced analytics comes in. I like to bring it back to the customer, it’s just building that customer experience and using these enablers for it. That's an area I think that we are actively exploring, but it's not so easy to do. It sounds easy, sounds great. But the execution is again tricky, because we still have this legacy. I still have a core banking solution, I have a credit card solution, I got a workflow solution. What do I do? It's one of three states, it's either A, we say, bite the bullet, migrate everything. B, we basically say, do a hybrid, potentially say, hey, let's launch X, Y, Z, powered by AmBank. And then essentially say, hey, new capabilities, new products, new segments of customers will power through this engine, and then the more traditional customers stay on. And the third one, of course, is just, you know, try and build those capabilities within the existing legacy infrastructure, which is not impossible, I suspect, but might be a bit challenging. So those are things that we are grappling with, and there's no real answer that I can give, except to say that's something that we're taking time to think about on how we want to move forward. 

MZK: Ishan, I wanted to get your perspective from Funding Societies, this application of agile and cloud native and advanced analytics, and what that means for strong customer engagement. 

IS: I think it's a very different experience for us, because we were born in all of these cloud-native technologies. We didn't have to deal with a lot of legacy systems and stuff. Cloud or cloud native makes sense, because you want to focus. Ultimately, it's about providing a very strong customer experience. These technologies enable you to do that. For instance, if you're looking at Apple stores, they provide you one of the best in-store customer experience. But they don't necessarily own the building, they just rent out the space. And similarly, being cloud native to me is very similar to that. You focus on the problem that you're best at and use the most cutting-edge technology to enable that.

MZK: Kanags, I wanted to also get your sense in terms of what those key benchmarks would be or markers that you are using to measure your success, given the pace of change and how fluid and dynamic the environment that you're working in. Any thoughts on how you're measuring the success?

KS: NPS obviously is a good old benchmark that makes sense irrespective of whether you're a traditional organisation or an agile organisation. It's a question of how you're reacting to customers’ needs and how fast you are. That overall covers a significant benchmark. The second piece is obviously as banks, we look at our price-earnings (P/E) ratio, we look at our return on equities (ROEs) and those things, which I think if you're doing the right thing, those levers may move in the right direction. When you look at these transformation initiatives, how those initiatives are playing out, and if those are really creating an impact in terms of measurable impact in terms of how those solutions are provided to our customers or to our internal staff. It's multiple layers of metrics that you typically use. But I don't think you can necessarily measure this in one particular way. Because you're in a place where the opposition needs to transform, you don't have a way, are you going to be a laggard, like Nicolas was saying, you end up catching up at some point in time. And by the time it might be too late. You have to move fast, quick and keep up the pace. That's the only way. 

MZK: Reona, playing catch up when you're certainly well placed or well positioned from that perspective, you're thinking in terms of hitting the sweet spot in terms of delivery of digital banking experiences. 

RS: We have this kind of advantage of not having a legacy system or infrastructure. For us, we're a bit spoilt for choice. And I think that hitting that sweet spot is kind of like how we actually are able to maintain the fundamental. When we originally started this business, and what our guiding principle is that, as I think Ethan mentioned earlier, the banking experience needs to be simple. I always like to say that, look, I can literally run my bank on my mobile phone. I haven't been to Indonesia in the last 18 months. During that time, the customer base, everything has quadrupled over time in the last six months, because at any given time, I could pick up my mobile phone, look at what's happening, and also manage some of the internal processes on my phone as well. And I think that's on the simplicity side, and then the other thing is about being able to adopt these technologies in an economical way. We've pride ourselves that, look, we didn't really think that we needed to reach scale to be profitable. We said that, look, we want to be a technology company, super productive, adopt new technologies and have a real business profitable from day one and keep on scaling. As we scale and go faster, and are faced by new technology choices. Someone was mentioning about choices daily on what technologies to adopt, it's true. I used to work in consulting, when I went to a client we would do, if I build like capex decisions for the next few years. We finish it and then we do high fives and a year later we come back. Now, it's more like every day or every week, okay, we have this decision, we need to make analysis, we have five minutes to make up our mind, and these are the things that we're grappling with. In terms of what we figured out in the end, one is that there are a lot of great technologies out there that we should be very fast in adopting. The second thing is that we shouldn't be too prideful about our own development capabilities. As a fintech startup, we're like we're number one, we're number one at everything. But there is a time and place where you need to decide that, look, there are actually really great solutions out there which plug in really well with your existing systems. And I think that, lastly, just bringing it back and not forgetting that, look, it's not eKYC, it’s not an OCR, it's not an NLP, it's about customer experience. It’s kind of like bringing it down back to that perspective helps us guide us on these product decisions as well. 

MZK: Nick, Ethan, any final thoughts on this in terms of hitting that digital delivery of superior customer experience? 

EW: First, I would like to clarify one thing about the earlier question. When we talk about the cloud-native technology and architecture, I think it does not only apply to core banking or back-end systems. We constantly see increasingly how cloud-native architecture plays a key role in the bank's digital channels. That's one thing. Now back to the question. I agree with all of what Reona says about how to measure, how important the customer experience is. For me, what are the key markers for a successful digital experience? There's no global standard in terms of benchmark for a successful digital experience. Apart from those fundamental things like security, safety, risk management, there are still some key elements that I personally think banks should probably consider. I’ll quickly mentioned a couple of things. First, is something probably some banks are already doing, it is about the value of the digital engagement, financial and non-financial. For example, how many transactions customers are having through the digital channels? And what percentage is your customer engagement through the digital touch points? And how about your customer experience ratings through the digital apps. The second thing, which is probably some banks are missing in the current measurement today, for example, the value of the digital efficiency, how fast a customer can complete an onboarding process and how relevant your customer insights or personalised offerings could be. The third thing could be very interesting. The third interesting point, from my perspective is about the value of digital ecosystem. There are more services and transaction nowadays are potentially initialised through a third-party ecosystem, website or some banks are actually taking approach to offer some non-banking products. A measurement or an impact from this perspective could be something we're interested in. 

Convenience and having optimal processes in place for customers is the ultimate gauge for the success of a digital platform

NE: The concept of traditional metrics of success versus non-traditional metrics of success become very important here. And in our industry, we're beholden to financial metrics of success and product distribution metrics and successes as a general common theme. As we adopt more digital services, as we engage with more customers more digitally, we're going to have to think of different ways that we measure success. If you forget banking for a moment, and you look at what some of those leading lights, and new platform businesses or digital businesses that are that are in the world, how they measure their success, obviously, there's financial metrics, but the measures of success are much more tied to digital engagement. How many times has a customer actually performing a specific task? How many times are they going back? Real-time feedback as part of that, as well. So that direct line of communication. That was the first thing I wanted to say. The concept of legacy and changed and shifting to the future is really interesting. I always think of whenever anyone talks to me about legacy, all those decisions were made within a bank for the right reasons at the right point in time. But I think it's super interesting now to see how different banks deal with those hurdles that they have to combine. Kanags talked about a couple, I'd add one more to the list there, which is around stratifying the bank's architecture. It's not easy, we all know it's not easy to move off your core banking system. But if you can protect your core banking system with a layered architecture with a loosely coupled architecture, this is obviously for incumbent banks, you enable innovation in the front without necessarily impacting your back-end systems. There are ways to limit the function that your core banking system has within your institution, beyond one of those mass migration type of scenarios. I think that the second part of that is that what's really pleasing in all of this is that banks realise that what got them to here is not what's going to get them to there. There's a huge amount of thought, probably more than I've ever seen in my career around, trying to tackle that challenge and trying to tackle the challenge of how to embed agility into an organisation that actually hasn't really changed that much in the last 100 years.

MZK: Absolutely, I think this is certainly going to be quite impactful to the industry, Nick, and given the pace and speed at which digitalisation is taking place in this very complex, competitive environment, then being future proof and being ready is going to be paramount for the traditional players. Being able to provide, as we've discussed, those highly personalised experiences at scale, engaging with customers, looking at those different, as Nick just pointed out, in terms of the non-traditional metrics as well. There are learnings from other industries in getting that customer experience right. Certainly, you've got different players bringing that value to customers. And really, it's built around addressing their pain points and forging and developing new business models. It’s really institutions having a rethink in terms of their traditional setup, and using technologies as an enabler. Given the low barriers of entry and the fact that different new emerging competitors who are operating and playing by their own rules and different rules, really, traditional banks, they have their work cut out for them. Being able to upgrade, enhance and provide those operational enhancements and service delivery, I think is going to be fundamental across the entire chain. I would really like to thank all of our guests today, Aaron, Kanags, Ishan, Reona, Nick and Ethan, for joining us.

Keywords: Smart Application, Digitisation, Banking, Artificial Intelligence, Machine Learning, Personalisation, Cloud, Fintech, Digital, Segment Of One, Ekyc, Analytics


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