Interview: Luis Uguina, CDO, Macquarie Bank

FStech’s Chris Lemmon sat down for an in-depth chat with Luis Uguina, the chief digital officer at Macquarie Bank, when he left his usual base in Sydney for a recent trip to London. They discussed the bank’s technology strategy, how the FI develops its systems, and why channels such as SMS and Facebook are relevant to today’s banking customers.

Chris Lemmon: Macquarie is a global financial services group, so how do the retail bank, its Australian operations and your role fit into it?

Luis Uguina: Macquarie Group is worldwide and Macquarie Banking and Financial Services (BFS) is the retail arm, which has operations in Australia, providing retail banking services to customers there. Macquarie decided three or four years ago that it wants to transform the way it does banking and provide financial services to customers through a purely digital approach.

We are not planning to have any branch network, but we do have a customer contact centre to help customers and provide services. We also have direct business with customers, as well as broker intermediaries and white labels that are using Macquarie products.

My role at Macquarie is quite a unique role in the financial industry as I am the chief digital officer and inventive architect. So I have the business hat and the idea hat. The reason we decided to do this is because it is difficult to align agendas between ideas and businesses when communicating within banks. Many different banks are struggling to deliver a consistent customer experience as they cannot manage the complexity of the two different angles.

CL: Last year you implemented a new core banking platform – what stage of that process are you at now?

LU: Yes, SAP – which is now finished. All of the different services and products that we are delivering to the market are now based on the SAP platform. Right now we are either implementing the functionalities or improving the systems, but the core banking platform as a project is already complete.

CL: And what stage are you at in terms of the roll-out of new features and functionalities for customers?

LU: All of the projects are live. Obviously a bank is never finished, but the core banking functionalities and the outcomes we were expecting have all been delivered with customers using the products as we speak.

We have the SAP core banking system which is providing all of the back-end capabilities, coupled with some legacy products that we still utilise. Instead of trying to untangle the spaghetti of a system that has been working for many years, we decided to create a layer to sit on top of the legacy systems, called the CX (customer experience) layer. This layer is going to provide the data and the capabilities for all of our different consumers – through e-banking, mobile banking, the customer contact centre, or through a chatbot that we have developed for Facebook Messenger.

We hosted a series of sessions with customers to find out what they wanted, and we found that one thing customers wanted was to communicate with the bank in ‘natural language’. Banks should be able to easily answer questions such as “how much have I spent on groceries in the last 10 years’?” So we decided that we could deliver natural language processing into a banking website, on a mobile or any other platform. The reality is that with today’s technologies – and through Datastax Enterprise which we are using for the CX layer – you can deliver those capabilities. And now we are the first bank to develop real natural language processing.

This is how we are different from the rest of the banking industry. As we are using the same technology as Netflix, Apple or Facebook, so we should be able to deliver exactly the same customer experience as them. Netflix is using Cassandra to process around three trillion interactions per day, using machine learning tools to provide real-time recommendations based on programmes viewed and user ratings.

CL: You have built your own machine learning tools in-house. Why did you choose to do that, rather than go elsewhere?

LU: We are using open source solutions to build the machine learning and decided to have the engineers inside the company to develop the machine learning algorithm. So we have a group of new graduates that are coming from Australian universities who are passionate about machine learning and all of the capabilities that are possible with this technology. We also have experts in machine learning and mathematicians to support the development process.

We want to deliver the best possible customer experience through digital-only channels. We are dealing with database records that we are interchanging every night with the financial industry worldwide. By definition right now, we are a fully digital company. The only thing that is different is that we still have processes that are from the last century.

We are also developing machine learning tools with other companies too – right now we have a model called ‘algorithm as a service’, which works with other companies to develop problem-solving algorithms. We are using open source software to speed up the process of delivering products to our customers.

CL: Are you using biometrics or any other emerging technologies?

LU: We are testing almost all of them. Many of them are going to be in the lab for a long time and some of them are going to be real products in the markets over the next few months. The use of voice biometrics forms an important part of our business, as it can deliver good customer experience in terms of a customer efficiently identifying themselves and as a second-factor authentication method. We also launched Apple Pay last February, which has received really good feedback from customers. Android Pay was rolled out to our customers in June last year, and those customers are also very pleased.

CL: How is Macquarie Bank using Big Data?

LU: We have a traditional approach to Big Data in that we have a data warehouse, where we have all customer information, banking processes and analytics tools;and then we have a system called SDS, or Smart Data Storage, which supports all of the transactional information and is based on DataStax.

We are delivering Big Data outcomes in a few different teams, so we do not have a specific Big Data team as such. We have teams that are building the new machine learning algorithms and the artificial intelligence algorithms based on the transactional data of the customer.

Many banks in the world are working on algorithms that provide good customer experience for users who are similar in terms of age, mobile handset and so on. We think that this approach is not sustainable in the future. The bank should be able to understand your behaviour and should be able to adapt the outcome specifically to your behaviour.

One example of this is: My mum loves the push alerts that the bank sends every time she uses her card, as it makes her feel comfortable and secure. I love the push alerts too, but receiving the same “hey, you have spent $3.50 on a coffee” message each morning, in the same coffee bar, at the same time, can become annoying.

Users are able to opt out of recurring transaction notifications, but will receive a push alert if, for example, the cashier typed in $35.00 rather than $3.50 into the point of sale terminal. The bank should be able to learn which transactions the customer usually swipes to delete or swipes to see more information about. If a customer swipes to delete the message six or seven times, our bank will send them a message asking if they wish to continue to receive those notifications every morning, unless there is something unusual to report. That is when a bank is providing the right service for me. This is an approach where technology needs to be able to self-create the solutions to customer problems.

CL: Can you sign up for the bank’s services through a mobile app?

LU: We have different services available on both mobile and desktop. We have a mobile-first approach that is different to what people would usually understand by mobile-first. By mobile-first, our approach is that every system we design needs to work in a way that the consumer can be out of coverage at any given moment.

Everything that we deliver must be able to work on a four-inch screen, and we need to minimise the bandwidth that we are using for those processes – as every kilobyte costs money. To give you an example, on a desktop a customer can view their last 100 or 200 transactions on one screen instantly. On mobile, we have algorithms that deliver 10 or 15 of your most recent transactions, with the option to view more.

The system needs to be able to behave in two different ways. We needed to design a system in which mobile, the most constrained channel, needs to be able to fit the approach. Mobile is about execution; if a customer wants to check their balance or recent transaction, the majority of customers will do so via their mobile device. When the customer needs to complete more in-depth banking tasks, such as applying for a home loan or putting their money in a timed deposit or fund, customers will generally research this on their computer as it is not a casual interaction.

The attention span on mobile is around four or five minutes – if you asked the customer to do something in 10 minutes on their mobile, you will probably lose that customer. The attention span on desktop is much higher, and the attention span for tablets is also quite long. However, if you provide tablet users with tasks which require a lot of brain power, you will probably lose that customer too.

We are not going to put home loan applications or similar tasks on our mobile app, unless we are able to develop a system which includes all of the relevant information required – we are not going to deliver a bad experience on mobile for our customers, just because everything needs to be on both channels.

CL: You mentioned chatbots earlier and that you have recently rolled one out on Facebook. Could you tell me more about that?

LU: We are testing many different technologies in many different channels, and our mission is to make life easier for our customers all of the time by integrating our financial products in a seamless way. Now we have customers that want to use chatbots to complete some banking tasks. We are not doing chatbots because it is cool, or because we want to save money in other channels – we are testing chatbot technology because we have customers that are asking us that they would like to be using this technology.

We also have customers, especially young customers, who are telling us that they would like to make a payment to their friend via Facebook. Many customers do not want to have to leave Facebook and open their mobile banking app to complete such tasks, so we had to provide the technology to do that.

We also have users who have told us that they want to use their banking services through SMS messages. People like my mother are unable to download and use the mobile banking app as she still owns a Nokia device, so customers like her are now able to complete a transaction with us through SMS. People like my mother are not ever going to use a chatbot, so we have to provide the best customer experience for them – which may be through an SMS banking service.

All of the big corporations have spent billions of dollars in trying to teach our language to the customer, but now I think the new customer generation is saying: “I am not going to speak your language anymore. What I am expecting is that you start speaking our language”. So my mission is to provide the products using that language. If that language is through Facebook, then let’s do it. If it is SMS, then let’s do it.

CL: You said that you are still working with some legacy systems. Do you have a target of when you would like to be completely upgraded?

LU: As soon as we are moving workloads onto the new systems, we are decommissioning the old ones. Some systems are going to stay with us for a long time, because they are working really well and there is no need to change something that is not broken. Obviously we have plans to decommission all systems at some point, but only when we have a valid substitution.

CL: Where do you see Macquarie Bank in five years’ time?

LU: It is very difficult for me to say where we are going to be in five years. In a couple of years, we will probably have the best technological infrastructure in the worldwide banking industry. We have the best technical team in the financial industry worldwide, in terms of talent, passion and capabilities. That is why we have been able to deliver amazing results in 16 months. In terms of technology, in two or three years we will have best-in-class infrastructure and architecture. We are going to be exactly where the customer wants us to be and it is going to be an interesting journey.

    Share Story:

Recent Stories

New Business Frontiers
FStech’s Mark Evans discusses the future of financial services with Liu Jianning of Huawei, covering the limitations that current thinking can impose, how financial institutions can embrace technology to be both agile and resilient, and making space for the organisation to focus on the job of creating innovative business models and on delivering business value for their customers.

The Future of Intelligent Finance
FStech Group Editor Mark Evans sits down with Jason Cao, President of Global Financial Services Business Unit, Enterprise BG at Huawei ahead of its Intelligent Finance Summit which was held on 3rd and 4th of June in Shanghai. This Q&A delves into key trends in digital transformation of the financial services industry as well as a look at how data, robotic infrastructure, intelligent storage and innovative technologies are shaping the future for FSIs.

Cracking down on fraud
In this webinar a panel of expert speakers explored the ways in which high-volume PSPs and FinTechs are preventing fraud while providing a seamless customer experience.