Evy Theunis of DBS: Consumer digital banking strategies
Inside the Sell Side
Evy Theunis
Head of Customer Segment & Customer Science | DBS
Evy is responsible for driving scalable business growth by delivering data-led customer and distribution operating models, frontline tooling, and hyper-personalised digital offerings to the bank’s wealth segments.
Prior to joining DBS, Evy worked as a consultant in financial services for over 10 years, leading design, delivery and deployment of digital platforms across Europe and Asia. She is passionate about her healthy lifestyle, spending time outdoors, and being with her family. Evy has a Master of Science in Information Technology obtained at the Catholic University of Leuven, Belgium.
The ability to scale is key to the consumer business’s success, and with the evolution of digital and data, there are new avenues to do this.
Q. What do you do as the Head of Customer Segment & Customer Science at DBS?
Our consumer digital banking strategy is centered around 4 key pillars: automation banking, which enables operations to be performed digitally; augmented banking, which powers technologically strong capabilities like DBS digiPortfolio, our hybrid human-robo investment solution; open banking, which revolves around our ecosystem of partnerships; and intelligent banking, which uses digital and data to scale the business, and is what I have been focusing on.
More specifically, intelligent banking harnesses advanced technologies such as big data, predictive analytics, AI/ML and customer-centric design to transform data into personalised insights for our customers, build scale and tailored customer experiences, and transform the way our business works – both online or offline.
Ability to scale is key to the consumer business’s success, and with the evolution of digital and data, there are new avenues to do this. So, I took a transformational approach to the way we look at our online & offline business and holistically changed the way we operate, with digital & data at the heart of the change.
Q. Tell us about your top digital transformation priorities at DBS.
The foremost priority is to be able to personalise experiences for customers. All customers, whether in retail or private banking, have a personalized navigation journey on our digital platforms. Beyond that, they also receive personalised, relevant and intuitive nudges be it about their everyday banking, financial planning, investments or protection needs – we call these ‘smart triggers’, which seek to help them to manage their finances better and more effortlessly.
Secondly, we also embed digital and data in the way our offline business operates, which ensures that we’re providing consistent advice regardless of the customer touchpoint. For example, we equip our relationship managers with data-driven conversation pointers through what we call ‘Next Best Conversation’, to enhance discussions that require more complex advice.
Lastly, we have looked at how we can use data to improve the quality of our service. As an example, our relationship managers receive personalised training and coaching based on data insights about their training needs, e.g. on specific products, customer communication, digital, etc.
Bringing the business, data and technology teams together gives us a better understanding of how all the dots are connected. Deciphering data trends is difficult if you’re in siloed teams, but when teams work together the insights come fast.
Q. Who or what shapes the data used at DBS?
Fundamentally, it required the bank to view digital and data as being focal to the business rather than a ‘side project’. This requires buy-in and advocacy from the top-down. At DBS, we have our senior management to thank for fostering a strong digital-first culture, which has since taken root throughout the organization. With this foundation and commitment in place, things get done much more effectively.
From a data point of view, we’ve gone beyond giving our relationship managers access to data and regular management information, to also provide them with insights. Traditionally, insight generation was not only time consuming, but also very much dependent on the relationship manager’s individual capabilities. Today, we harness AI and machine learning to empower them to have more informed and effective conversations, and at scale. We want our customers to have relevant conversations with us, and done as efficiently as possible, so they can spend more time on other things in life that matter.
This wasn’t done overnight. It was the result of ongoing close collaboration between teams, instead of working as separate project teams that don’t have oversight of each other’s day-to-day work. We had deep conversations with the frontline staff to understand how they engage existing and new customers, the pain points they face, etc.; this helped us to define the job to be done and what we need to develop next. After which, we harnessed data into useful and actionable insights for our customers and relationship managers, ultimately enabling our customers to make better financial decisions.
Q. Is there a magic formula to ensuring data is standardized especially when it comes to machine learning?
Having the infrastructure ready is definitely a prerequisite. We invested in a bank-wide data lake, ADA, to ensure consistency, speed, and re-usability, and migrated data from all our different systems into it. Our technology team also built an architecture focused on scale and reusability, so that it’s the same Application Programming Interface (APIs) pulling data and delivering it to customers, be it from digibank or employee tools. This is 100% reusable for customers and employees.
Raw data is not necessarily usable most of the time, so we have built reusable assets – a value that is created by one team and reused by subsequent teams. ADA has enabled us to ensure consistency as we build and scale up these capabilities. Bringing the business, data and technology teams together gives us a better understanding of how all the dots are connected. Deciphering data trends is difficult if you’re in siloed teams, but when teams work together the insights come fast.
It is also very important to continuously gather feedback. For example, we’ve been asking customers to rate the usefulness of our intelligent banking features on our digiBank app, ever since we launched them last year. Collecting feedback helps us to know what works and what doesn’t. This enables our data scientists to make the necessary refinements and enhancements, and accelerate further across our markets.
Q. What have the results been since DBS started on its digital transformation journey?
We have been building our digital capabilities and infrastructure for a long time, which left us fully ready to quickly pivot and scale when Covid-19 hit last year, and to continue serving our customers seamlessly. Whilst adoption and usage of our digital services have been on the rise over the years, we saw an uptick after the pandemic emerged and numbers have continued to remain robust, suggesting that the changes in digital behaviour are here to stay. There was also a big jump in tele-advisory as some products (e.g. protection products) are not available through digital platforms. With tele-advisory, customers can speak with our relationship managers directly, without the need to meet face to face.
All in all, the number of people coming online is growing, which suggests that customers find our insights useful and are acting on them. Our priority has always been to focus on customer needs, and that is something you will continue to see from us.