The future is FinTech
From the invention of the credit card and ATMs in the 1950s, to mainstream adoption of online banking and more recent excitement surrounding cryptocurrencies, there has been a rapid evolution in the way we interact with financial services, especially in the last 10 years.
However, with consumers confined to their homes and increasingly turning to online shopping, food ordering apps and contactless payments throughout the pandemic, Covid-19 may have brought about the biggest change to the way we navigate our finances. Experts are suggesting we may even be nearing the end of cash altogether. So as money becomes ever-more digitised, the need for experts to manage, analyse and explain data has never been greater. We spoke to a data scientist about why now is such an exciting time to work in FinTech.
The global pandemic is thought to have sped up digital adoption in some regions by as much as five years. A study conducted by the World Bank found that most types of FinTech firms reported strong growth for the first half of 2020, despite the global economic downturn. Many experts highlight the potential for FinTech to make finance more accessible for those most in need and the FinTech sector in emerging markets and developing economies saw particularly strong growth – as much as 40% in the Middle East and North Africa. Globally, finance apps alone were downloaded more than four billion times in 2020.
With so much financial data being produced, data scientists have a much-needed skill set and in the UK alone demand for data scientists and data engineers has tripled over the past five years, rising by more than 200 per cent.
From educating them as to the power of data science, to understanding their problems, building a model to fix that problem and then seeing the benefit that it brings makes it all worth it. Data science can be a win/win for both the company and their customers.
The University of London, in partnership with Member Institution Goldsmiths, offers an online MSc in Data Science with a specialism in Financial Technology. Modules include topics such as ‘Blockchain Programming’ and ‘Big Data Analysis’ and this flexible programme allows you to study while you work, preparing for an exciting future career. But what’s it really like to work in the booming FinTech sector? We spoke to Will Jackson, a British data scientist working in the Netherlands.
Having completed his degree in mathematics and statistics, Will was weighing up possible career paths. A summer internship at an investment bank helped him to realise that it wasn’t the sector for him, but one of his professors suggested he would be well suited to data science.
“I had been considering actuarial science and when I started researching data science I realised there were a lot of similarities – both fields aim to make predictive models about things happening in the future. But while actuarial science focuses on insurance and pension risk, with data science you’re not limited to one sector or industry. When I’d finished my master’s I was offered the option of staying on to study a PhD but I was excited to get into the industry and apply what I had learned.”
Will’s previous roles include Dunnhumby, a leader in customer data science who helped establish one of the first and most successful loyalty cards (The Clubcard for Tesco).
He now works for Dutch FinTech unicorn, Mollie, who announced in June 2021 that they had raised a further $800 million as part of their Series C funding round. Mollie is a Payment Service Provider (PSP) and offers companies with webshops competitive rates for all known payment methods used in the European market.
Will said: “My job is to assist teams in meeting their KPI's, whether that’s saving money, increasing sales, improving customer satisfaction or automating processes to help the extreme scaling process that is currently underway here. I usually spend the bulk of my time working hands-on on projects, interacting with stakeholders and end-users and ensuring that we build something that suits their needs.
“For me, the interaction with people who can use my models is something I love. From educating them as to the power of data science, to understanding their problems, building a model to fix that problem and then seeing the benefit that it brings makes it all worth it. Data science can be a win/win for both the company and their customers.”
I see a gap in the industry for people with a data mindset to help translate technical and complex problems into terms that non-technical people can understand. I think this will be necessary for all successful companies if they want to navigate the ever-changing world and remain competitive in their industry.
While lockdowns are now beginning to ease and economies have started to recover, consumers are continuing to enjoy the ease, speed and security of digital finances. Will believes this has been a wake-up call for a lot of companies.
He said: “I think a lot of businesses claim to be 'data-driven’, but the reality is that their actions don't match their words. I see a gap in the industry for people with a data mindset to help translate technical and complex problems into terms that non-technical people can understand. I think this will be necessary for all successful companies if they want to navigate the ever-changing world and remain competitive in their industry.”
So what advice did Will have for future data scientists?
“I always encourage people to find a topic in the field that they are interested in and think about potential problems that could be solved with data science. Even inside the FinTech domain you can still work on such a wide range of data science projects. See if you can get your hands on some data at university or on a site like Kaggle and have a go at building a model to solve a problem. Once you’ve done that, search through other projects that people have shared using the same data to get further inspiration. Talks and conferences are also really useful – DataScienceFestival had a FinTech month earlier in the year, which had some great speakers.”
Explore an exciting future in FinTech with the University of London’s MSc in Data Science.