The data ethics of Open Banking

Over the past three years the Open Banking movement has quietly gathered pace in the UK. Without realising it, many people are now benefiting from new products and processes that have been enabled by Open Banking’s free flow of financial data. Each month brings new use cases that range from incremental user experience improvements - such as easing KYC requirements - to more exciting innovative applications in the field of predictive analytics. Although we are yet to see the ‘killer application’, it really is only a matter of time before this happens and Open Banking really takes off. Therefore,  it is the perfect moment for the fintech and data industries to work together to set data ethics standards to guide the future of the sector.  

We all know that financial data is among the most personal and sensitive information you can have on an individual. This is why the rules governing Open Banking were painstakingly crafted to ensure that informed consent was always secured from users and those handling data adhered to stringent data governance procedures. However, as is more often than not the case with any government regulations, Open Banking was not necessarily designed to anticipate and adapt to changing consumer behaviour and technological development. 

Since Open Banking was first conceived, we have seen an incredible amount of innovation in data science. In the past twelve months alone, thanks largely to the pandemic, we’ve seen concepts such as AI and algorithms reach mainstream attention. The marketing sector is among a growing number of industries that have  been completely transformed by the insights data scientists can glean from sources such as social media, browsing, purchasing and demographic behaviour.  It is now possible to provide hyper personalised experiences that determine a customer’s identity and preferences and predict their needs with unprecedented accuracy. All of this has been achieved without financial data. 

You do not have to be a data scientist to understand how applying the same techniques that have been used to gain insights from information such as social media behaviour to financial data could open the door to a mind boggling array of new use cases. The advantages for consumers could be profound. Everything from how they manage their spending, plan their financial futures or make individual purchasing decisions could be impacted. It could revolutionise how credit worthiness is assessed - speeding it up, making it cheaper and fairer, and helping close the financial inclusion gap. Problematic spending behaviour could be identified and addressed before it gets too serious. The list could go on and on. However, this revolution is predicated on consumers retaining trust in the Open Banking movement and the data science behind it driving inclusion not reinforcing any system bias that exists. We only have to look at how the misapplication of personal information by companies such as Facebook has raised serious privacy and security issues and subsequently eroded trust in big tech. 

If the fintech sector was to repeat the mistakes of their social media counterparts, the damage could be even bigger. Misusing someone’s social media data is one thing, being cavalier with their financial data is quite another. 

Now, you may be quick to point out that Open Banking regulations were written with these conditions in mind. Well, the prioritisation of clear consent from users is a very good safeguard. However, it has its limitations. As I’ve already pointed out, data science is moving at a rapid pace. What we can learn from and then do with personal data grows everyday. Although people are generally more aware of the power of data analysis, there is no way that everyone will be fully capable of understanding just what can happen to their data when they approve a company to use it. The consent is not necessarily informed. We also know that bad actors will be attracted to every hot new sector. There will be fintechs that will seek to stretch the limits of what is acceptable in order to make a bit more money. Other fintechs will, in the pure pursuit of innovation, not fully appreciate the consequences of their actions. In short, the scope for things to go horribly wrong in a short period of time is pretty big. 

So how do we mitigate this risk? My view is that serious, self-regulation to act as a prevention rather than draconian Government led intervention to act as a cure, is always the better option. Much of what I’ve outlined above comes down to data ethics. The fintech industry should work closely with other sectors and disciplines to begin to draw some lines in the sand. This means engaging with data scientists, academics, policy makers, financial institutions, lawyers and so forth, to fully explore all the ramifications of Open Banking. By openly debating what could happen, the industry can begin to outline what really should happen. They can shine a light on grey, morally ambiguous areas to provide industry-wide analysis and guidance. Individual fintechs can then design their products with data ethics best practices in mind. Companies that fall short of these standards should be called out. 

What I’ve outlined is not easy. Bringing together scores of competing companies to agree on principles that could impact their freedom to innovate or commercial prospects is, to say the least,  a challenge. However, as they say, ‘be the change you wish to see in the world.’. A movement can start with one company taking a stand and getting the ball rolling on the ethics debate through tangible action. In our own small way, we’ve sought to do this in the data science industry by forming our own multi-disciplined Data Ethics Advisory Board.  It  guides our decision making and will provide advice to the wider industry.  It is unlikely to result in a paradigm shift in the data science industry, but I believe that there is a moral, as well as a commercial imperative to act on these issues - even if you feel a little out on a limb.

Ethics is not about never doing anything wrong, the law moves slower than technology and thus there is no cut and dry and standard rule book here to follow. In a field that’s ever evolving it’s about making sound choices with all the information known at the time. Our Good Data Guide will support businesses from every industry to think through the consequences of those choices to ensure they are not having unintended unethical consequences.

For fintechs operating within Open Banking this same commercial and moral imperative applies. The more thought through the choices and their consequences, the more well-rounded the information from diverse perspectives, the better chance we will have of avoiding our doomsday scenarios above. The true innovators will seize the initiative and lead this data ethics debate.