Dr Geraldine Wong is Chief Data Officer at GXS Bank (GXS), one of the two successful digital full bank licence applicants in Singapore. GXS is backed by a consortium consisting of Grab and Singtel. At GXS, Dr Wong is responsible for driving and building the bank’s AI and data strategy with the goal of leveraging ecosystem data assets, promoting data-driven financial inclusion and reimagining the way customers engage and experience the digital economy. Her career spans across industry and academia, where she has led teams in developing and executing regional AI initiatives across the public, transport and info-communications sectors.
Dr Wong was named in the SG100 Women in Tech list by Infocomm Media Development Authority (IMDA) (2021) in recognition of her contributions to Singapore’s technology industry. For her achievements in data analytics, she was recently named one of the global top 100 Innovators in Data and Analytics by Business of Data in 2022.
She is currently a member of the Tech Advisory Committee of Synapxe and an Adjunct Associate Professor at NUS Faculty of Science. Geraldine seeks to inspire and nurture the next generation, through her active mentoring for Girls in Tech and NUS Uplift mentorship programme and being an ExCo member of the Free and Open-source software group at the Singapore Computer Society.
In an exclusive interview with Digital First Magazine, Dr Wong shared her professional trajectory, her most favorite part about working at GXS Bank, insights on diversity and inclusion in the tech world, significant career milestones, future plans, pearls of wisdom, and much more. The following excerpts are taken from the interview.
Dr. Wong, could you please share your background and areas of interest? What got you excited about AI and data science in the first place and how your work has evolved?
I am currently Group Chief Data Officer at GXS Bank, one of the 2 successful applicants of Singapore’s Digital Full Bank License, where I am responsible for driving and building GXS’s AI and data strategy with the goal of leveraging ecosystem data assets, to promote data-driven financial inclusion and reimagining the way customers engage and experience the digital economy. The bank is a consortium consisting of Grab – Southeast Asia’s leading super app, and Singtel – Asia’s leading communications technology group. Our aim is to make banking better for everyday consumers and small businesses. This includes Singapore’s underserved individuals and businesses. We also aim to improve financial inclusion and drive financial revolution for our customers through the secure and ethical use of technology and data.
My journey with data started as a PhD student in Statistics where my research leveraged on novel statistical and data science techniques on predicting the occurrence and impact of drought in Australia. Ten years ago, I took a leap of faith to move from academia research to industry and became a data scientist with a newly formed spatio-temporal mobility data intelligence (a spin-off of Singtel). Since then, I have both worked as a consultant at Accenture applied intelligence consulting to lead teams to craft, establish and deliver on AI initiatives and projects across public, transport and info communications sectors and more recently in my previous role as Head of Data Science and ML Engineering at Singtel Consumer Group. I have been very fortunate to not only remain in the field that I am passionate in and was originally trained in, but to constantly learn and grow in the emerging AI technologies.
What can organizational leaders do to promote a data driven decision-making culture in organizations?
I have had the unique opportunity of creating a data team from the ground up at GXS. From Day one, my key priorities were to establish GXS’ data strategy. This included aligning the data vision and mission to that of the bank’s strategy and to set in place the governance and oversight of driving the data strategy consistently across all levels from the board to the working level. This demonstrates the strong commitment to data-driven decision making and sets the tone for the rest of the organisation and is a crucial step for leaders who wish to promote data driven decision culture in an organisation.
The next step is then to invest in the right data infrastructure, tools and platform that would facilitate in the entire data lifecycle from collection, management to processing of data, to provide the insights and capabilities that the organisation is aiming to build.
With this also comes the importance of driving data literacy across the organisation. This can be challenging at the start and requires consistent and constant engagement, driving awareness and buy-ins from business users and technology teams across the bank. This requires creativity to encourage data literacy. For example, at the start in GXS, we needed the help of business users to provide definitions of the metadata of the data that their system was sending to the data lake. To encourage users to do this, we turned this initiative into a bank-wide competition. To increase the awareness and drive adoption of data, we frequently run roadshows, data governance clinics and data visualisation training to provide the opportunities for business users to identify gaps within their area where data is able to provide solutions. This provided many opportunities for cross-functional data collaboration between data and business/operational/technology teams.
Finally, it is also essential to have alignment on the metrics of success for which the team will be measured upon. This allows an objective assessment of the role of data within the use cases. Socialising such success stories on the positive use of data goes some way in helping propagate the importance of applying data analytics across the organisation.
What is your most favorite part about working at GXS Bank?
What I love most about working at GXS Bank is the vibrant culture of innovation. It is incredibly inspiring to work alongside a team of highly skilled and high performing data scientists, analysts and professionals who are always pushing the boundaries and thinking outside the box. At GXS, we are always seeking out new and innovative ways to solve complex problems with data and it’s truly an exciting and dynamic environment to be part of.
Working alongside a bench of high performing and intelligent professionals is both challenging and rewarding and it has really helped me to grow and develop my own hard and soft skills. I’m excited to see where our work as a team will take us next.
Please tell us about the topic/course taught by you as Adjunct Associate Professor at National University of Singapore.
I take on various responsibilities as an Adjunct Associate Professor at National University of Singapore (NUS). One of which is the opportunity to teach a third-year module in the Department of Statistics and Data Science, namely Data Science in Practice. The objective of this course is to introduce undergraduates to practical applications of data science concepts and techniques in real world scenarios. Through this course, students are guided through the entire data science lifecycle and equipped with the skills to identify and formulate data-driven problems, collect and analyze data and finally effectively communicate their insights. As aspiring data scientists, it is equally important for them to be aware of the considerations when operationalising Machine Learning (ML) models and key components required for model monitoring.
One aspect that I find particularly engaging is the group project, where students work in teams of eight to tackle real-world problem statements. This project requires them to incorporate user research and interviews, data collection, predictive modelling and both front-end and back-end engineering work to deploy an application for the user that addresses the problem statement. This practical exercise brings to life the purpose of the entire course and provide students with hands-on experience in applying their newfound skills for them to thrive as data professionals in an ever-evolving industry.
Another role which I have recently taken on is to be a mentor as part of NUS Uplift Mentorship programme, to support students with lower income backgrounds and provide guidance to accelerate their personal and professional development.
Are there still hurdles chief data officers have to overcome in their roles or are CDOs now accepted in parts of the organizational hierarchy?
Although the CDO role has gained widespread acceptance and there is greater awareness of its necessity, there remain differences in opinion about where this position should be placed within an organisation. The placement of the CDO role and its scope establishes the level of commitment an organisation has to data. This is often one of the challenges that CDOs must confront, particularly because it depends on the data maturity of the organisation.
Another challenge that CDOs encounter is the need to demonstrate and measure the impact that data has on the organisation, while also ensuring that this impact can be scaled effectively.
Lastly, CDOs must contend with the shortage and retention of data talent and their evolving role, in particular with emerging technologies such as Gen AI.
As one of the SG 100 Women in Tech, what are your thoughts on diversity and inclusion in the tech world? How important is it to have authentic conversations with leaders, professionals, and changemakers to create more acceptance across the globe?
While I do think that we are making progress in creating diversity in the field of data and AI, there is still work to be done. As data professionals, it is crucial to have a diverse workforce in order to reflect a range of perspectives and incorporate insights from various backgrounds when developing models, insights and recommendations. In my role as a hiring manager, I prioritise diversity throughout the hiring process by including members of my team on the interviewing panel. This approach ensures that we consider multiple perspectives and receive diverse feedback on each candidate. As a result, our team comprise individuals with different educational backgrounds, industry experiences, demographics, and nationalities.
I do think that it is important to advocate for a more diverse and accepting environment, by openly having such discussions with leaders and professionals. By doing so, we can identify areas where we need to improve and work together to create meaningful change. However, it is also important to recognise that actions speak louder than words. As leaders, we must take tangible steps to reduce unconscious bias and promote diversity in meaningful ways, even if they may seem small at first. By being catalysts for change in our own organisations, we can set an example for others to follow and help create a more equitable and diverse industry for all.
What has been your most career-defining moment that you are proud of?
There have been many defining moments in my career, but one that particularly clearly stands out to me is a conversation I had with one of my former managers. During one of our regular catch-ups, I shared my aspirations and individual development goals and laid out my plan for achieving them over the course of five years, which I conservatively thought was reasonable. However, he left me with a challenge to do it in three years. This challenge inspired me to seek out how I could grow my skills and achieve my goals and gave me the confidence to take on my current role. And I am eternally grateful for such a mentor who not only encouraged me to take chances but recognised my potential.
What is the top data issue that kept you awake at night as a CDO?
As CDO, there are number of data-related issues that can keep me up at night. Top of mind would be data security and privacy. With increasing amounts of data being collected, stored and used in the organisations, the risk of data breaches is a constant concern. Therefore, it is essential for organisations to have strong data security and privacy measures in place.
Another concern that keeps me up, is how the emergence of Gen AI will transform the way we engage with data and how organisations can leverage its full potential. Additionally, I am curious about how the new ways of working will be impacted by Gen AI.
Where do you see yourself in the next 5 years?
This year has proven to be very exciting with GenAI making waves into various parts of the organisations. I am really passionate about this work, so I do see myself continuing to grow and develop my skills in this area of AI and data, advocating for a safer, more responsible and wider adoption of AI within organisations.
Along the same vein, I am also passionate about helping organisations in their digital and AI journey. I hope to be able to play an advisory role to boards, in particular in organisations where AI and digital are just beginning to mature. I believe that data science and AI have the potential to transform the way businesses operate efficiently and effectively.
Lastly, with the recent unveiling of the second edition of Singapore’s National AI strategy and efforts to prepare the economy to embrace AI, I hope to play a more active role in reskilling and growing the next generation of data talents, through my role as an Adjunct Assoc. Professor at National University of Singapore
What advice would you give to aspiring data scientists?
Top advice I would give to aspiring data scientists:
- Be curious and have a growth mindset beyond what you have been trained in. Brace yourself to unlearn and relearn the new tools, concepts and problem statements.
- Develop your communication skills to “sell” your results. One must be able to communicate the impact of your findings and insights to the business.
- Seek out your tribe and mentors: I was fortunate to grow alongside my network of data friends where I could rely on them as sounding boards for data science related advice and seek career advice from my mentors.