Where banking meets technology. RBS sees rapid digital transformation in the financial sector

Claire Thompson Claire Thompson

The financial services sector, an industry that contributed £132bn to the UK economy in 2018, has drastically changed its digitalisation process over the past few years as a matter of urgency, but also as a direct response to the changing habits of consumers and new competitive environments. Amongst the frontrunners of change in the banking industry is RBS.

Claire Thompson, Head of Data & Analytics for Commercial and Private Banking at RBS, who was recognised this year by DataIQ as one of the 100 most influential people in data and analytics in the UK, sits down with Abigail Opiah to break down the collaborative effect the tech industry has on the financial sector.

In her role, Thompson is accountable for the vision and strategy of data and analytics and the leadership and development of around 230 people both off and onshore.

Her remit covers all customers in the Commercial and Private bank across all channels with teams focused on key areas such as data science, data engineering, digital, decisioning, software engineering, data governance and performance insights.

“Given the size and remit of the team, no two days are ever the same; this variety is just one of the reasons why I love the job so much. My day can involve anything from advising senior stakeholders about innovative ways data can be used to solve complex problems, helping individuals achieve their career aspirations, setting the vision and strategy for the team and many things in between,” she says.

Thompson started her career as an SAS analyst and quickly navigated herself to working for some of the biggest names in the sector including the likes of Barclays. Thompson reveals that one of the key skills she brought along with her throughout her career journey is problem-solving.

“One of my major strengths is the ability to ask questions and use data to understand why something is happening,” adds Thompson.

“It means I’m good at quickly spotting patterns and connections, sorting through the clutter to find the best solution; helping make informed and balanced decisions. It’s this analytical skillset that has helped me in all of my roles since my early days as a SAS analyst, even though I no longer code.”

As more consumers have adapted to digital interaction in several areas of their lives, there has also been a calling for financial services to follow suit. And the changes haven’t gone unnoticed.

When discussing some of the key trends, Thompson has witnessed regarding the digitalisation of the industry, she explains that it all boils down to increasing expectations of real-time and effortless banking from a customer lens.

“In a few years, I would expect to see most interactions between customers and banks to be hyper-personalised. I would also expect real-time Artificial Intelligence (AI) to become widely utilised in some form. Intelligent automation will emerge as a big trend and become a cost differentiator between firms – reducing basic tasks and data processing, where Machine Learning can be used to do a better, quicker and more reliable job. That said, human oversight will remain critical,” she explains.

“In terms of the technical side of this, we are seeing increasing use of Natural Language Processing not only for chatbots, but also to gain a deeper understanding of customers’ intentions and needs across a range of digital channels. This, combined with traditional structured data, has huge potential power.”

Speaking of AI, this is certainly providing a significant basis for future technological innovation, but there is lots of groundwork that still needs to be done. One main thing that Thompson points out is that it’s imperative to change society’s perception about the realistic abilities of AI as it exists today.

“Whilst there are risks associated with using big data and AI, the main misconception is that AI is too clever and is going to take over the world. As humans, we tend to anthropomorphise – attribute human traits, emotions and intentions to non-human things. For example, dogs or robots,” she explains.


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“AI can do some very specific things amazingly well, like detect cancer from body scans. However, we’re probably decades away from sentient beings. I would expect that there will be an ever-increasing variety and velocity of data processing. It also gets more complex as companies engage in more partnership-driven approaches, requiring complex data and process integration.

“Technologies such as APIs help massively in this regard, providing standardised connectivity. There is also an increasing focus on ethical use of bigger data in Financial Services, as well as specifically on managing the risks and potential public harm from the potential irresponsible use of AI – beyond current legislation. This is an emerging field and we are actively engaging with UK bodies on this agenda.”

When asked about the one thing Thompson is looking forward to in the new decade, she reveals that she is looking forward to seeing what more can be achieved with the continued growth on data as well as the continuous evolution in both tools and techniques.

“This will mean companies can dramatically change the way they work and ultimately it will be customers who will benefit from this changing landscape. I’m most excited about the continual advances being made with AI, particularly in supporting healthcare,” she said.

“For example, in helping patients recover the ability to walk. It’s amazing to see this become a reality, as through undoubted evolution, it will significantly change the lives of millions of people.”

Myths regarding Data Scientists

Thompson’s remit covers all customers in the Commercial and Private bank across all channels with teams focused on key areas such as data science as well as data engineering. In the nascent field of Data Science, myths abound.

When asked to list a few prominent ones, she says: “One of the myths is that if you recruit a data scientist, you’ll be able to do to AI. The reality is that it takes far more than just data science to make AI a reality. Depending on what you’re looking to do you will need a variety of different skills as the hard part is actually getting the model into production.

“The other is that you have to be an ‘egghead’ to become a data scientist!
You don’t have to be a great statistician, or mathematician to become a Data Scientist; however, it does help. Data Science for me is all about teamwork and embracing a diversity of skills. As well as working with data, you’ve got to be able to communicate – share the results of your amazing analysis with colleagues in an understandable way.

The twenty awardees at Women in Data

“Many Data Scientists are cross-disciplinarians, with some knowledge of stats and coding, plus a dash of business acumen/ethics/interpersonal skills thrown in. It’s very rare to find an individual that has all the skills necessary to wear all of the Data Science hats at the same time.”

Women in Data

Last year, Thompson was amongst ambassadors of the ‘Twenty in Data
and Technology’ collection for 2019 in collaboration with NBrown.
“Currently, for every four men that enter the data industry, there is just one woman. I believe movements like this are vital for making positive role models more visible. This can only help in inspiring more females and future generations into the industry,” she adds.

“Using our own personal career paths stories helps others on their own journey and can change the face of data and technology in the future. When I first started out in my career, there weren’t very many women at a senior level, so it’s great that things are changing. For me personally, I feel incredibly proud to be working for the first bank, out of the big four in the UK, with a female CEO and a female CFO.”

Women in Data UK works to connect women across the profession, providing mentoring and showcasing for real-world female role models.

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