I have always been fascinated by technology and mathematical models. When I was a credit officer for example I knew the importance of data. However, at that time data analytics, artificial intelligence (AI) and high performance computing (HPC) weren’t that developed.

Technology has fundamentally reshaped our economy and the way companies interact with their customers. This wave of digitisation has touched nearly every industry, and banking is no exception.

Banks have embraced these changes and are continuously investing in new technologies to bring their customers the latest innovations. Data centres – such as my blog hosts, Kao Data – have become fundamental cogs in the machine as technology and the data behind this increasingly determines our industry’s forward trajectory.

The International Banking Federation has recently conducted an extensive piece of research with Oliver Wyman on the impact of BigTech and FinTech entering the market of Financial Services, looking not only at the challenges and opportunities for traditional banks but also how regulation and supervision should adapt to make sure customers benefit from competition and innovation while preserving the highest standards in terms of data privacy, anti-money laundering and so on.

Scale is everything. You need large databases to be able to develop models and create added value.

Banks have a lot of data but they can expand their database even more by working together with other companies. Cutting edge technology requires huge investments. All this makes it critical to find the right allies and business partners.

To create a sustainable business you have to focus on customer needs and experiences. Tech companies are good at creating ecosystems to serve clients in all aspects of life, hence increasing the “stickiness” to their core platforms. They are also successful in so called – “blue ocean strategies”, charting new territory, untapped by traditional banks, either with novel services or – by addressing underserved or unbanked customer segments. In some markets, this “grows the pie”, increasing the size of the market for all players.

So far however, the entry of tech companies in financial services has been focused on retail clients, small- and medium sized companies and specific parts of the value chain such as customer-facing functions, data analytics, artificial intelligence, high performance and grid computing, infrastructure and cloud computing.

Amazon for example began its lending business in 2015, using SME transaction records on the platform to assess credit worthiness, set optimal interest rates and credit limits. But as they have no banking license, they work together with banks for the onboarding of loans on their balance sheet.

Same for most mobile payment apps, that run on existing payment rails from traditional providers.

There are multiple examples of successful application of data analytics and artificial intelligence in banking: know your client checks, algorithmic trading, quantitative research, risk analytics, loan decision algorithms, AML checks on payments.

Cooperation can bring huge benefits to clients in terms of innovation, speed, efficiency, financial inclusion and so on. However, it also creates new types of risk, diffusing accountability, data privacy issues or regulatory breaches.

The global financial services industry is reaching a crossroads. Technology will be further disrupting the market, accelerating digital transformation and bringing benefits in customers outcomes.

Tech companies have the potential to become key contributors on the ongoing Covid-19 crisis response and post-crisis recovery. However, gaining trust from the public and governments will be key, focussing on risk and compliance, culture and accountability.

Learning and working together can create a win win, not only for banks and technology firms but most importantly, the customers we serve.

Hedwige Nuyens is Managing Director of the The International Banking Federation (IBFed). She has over 30 years of experience in finance at senior international level.