Innovation? It’s all about the data, darling

In all my research into financial services innovation one trend stands out above any other: it’s all about the data.

What of data? The second law of thermodynamics describes the ever-increasing march of entropy, a measure of chaos and disorder; like entropy, data is continuously growing. Technological advances in the near future seem likely to focus on how to extract meaningful data from new sources.

It’s all about the data, darling.

But we are already drowning in a sea of data: consider a simple scenario, person to person communication, with data contained within email, SMS, voice, video and social media. Industry analysis indicates we are only exploiting a miniscule amount of the available data, so how will we cope with significantly more? Using our ingenuity and utilisation of current and future tech, we need to innovate.

Financial services products are intangible, thriving on information, and ripe for digitisation, making firms vulnerable to tech-native companies, both great and small. In response, many financial services companies have invested significantly in dedicated digital innovation labs in an attempt to play the “start-up” game, enabling Titans, such as big banks, to behave like Unicorns.

Innovation labs are a safe place for organisations to explore new ideas, particularly for firms operating in highly regulated industries. They provide a distraction free, safe space where employees can focus deeply on an idea. The emphasis is on experimentation, giving people the freedom to be creative, and failure is embraced as part of the process. Typically, the members of the innovation lab are drawn from across the organisation, bringing both technical and business domain expertise; ideally influencing the culture of change in the wider organisation, moving from a reactive to a proactive way of thinking.

So, what does financial services innovation look like? A good place to start is the Financial Conduct Authority (FCA) sandbox – a scheme encouraging innovation both domestically and internationally, testing cutting-edge FS products and ideas.

Although only a small number of organisations are selected for the FCA sandbox scheme, they are representative of the wider innovation effort in the UK and globally. The innovations broadly fall into three technology categories: AI, blockchain and ethical projects.

In this discussion AI, is defined as data plus machine learning. The sandbox projects use AI in a range of different guises, for instance, analysing past behaviour and applying “nudge” techniques to assist the end-user to make good financial decisions. Another uses data analytics combined with Open Banking to automate mundane tasks such as filing a tax return. There’s Robo-advice “with a twist” (warning: this may be too “meta” for everybody’s taste), a comparison service that uses AI to select the best robo-advice site, and once selected it will complete the relevant forms. A robot to find a suitable robot!

We also see an explosion of using AI “under the bonnet”, in the actuarial and underwriting tasks, particularly with the use of unstructured data, such as documents and images, to build a financial “picture”, useful for decision making. And what of untapped data sources? Analysing previous academic performance to predict future earnings; applying machine learning to business reviews, because “a well-run business is a good risk”.

All these can contribute to building a financial digital identity, which when stored in a distributed ledger becomes a financial digital passport. Now we’re straying into blockchain territory, the next innovation category.

Here we define blockchain as both blockchain itself and Distributed Ledger Technology (DLT), the technology blockchain relies on for its integrity and security.

Of the many properties of blockchain, the tamper-proof nature of the technology, and its application to digital identities has always been a no-brainer for financial services. We see projects addressing the challenge of making these identities usable across many services and organisations, plus innovation in adding standard and non-standard financial information to the mix, revolutionising identity and verification (ID&V), know-your-client (KYC) and due diligence. Apply the same theory to equities and you have evidence of change of ownership, creating trust in supply chains. This results in tamper-proof passports for both customers and assets. Imagine the effect on the art-world alone.

But were already drowning in a sea of data.

The final category is ethical projects – a focus on people and inclusion.

These projects approach the ethical from both the investor and consumer perspective. From a major bank understanding the motivations behind the ethical and social preferences of investors, to charities and insurers researching how to help the under-insured when taking out loans, or travel insurance; to the provision of virtual homes to the homeless, so they can have an address and begin to get support.

In FS, a shift in focus towards ethics can be seen, in particular climate change is becoming an important consideration. Mainstream investors are moving towards “clean tech”, a clear recognition of a financial return.

The innovation in this context is all about changing perspectives, not just tech. Insurance has always used the past to predict the future, but what if you can use the present and the future to predict the future? Insurance organisations are partnering with climate scientists to investigate new ways of measuring risk, using new non-standard data sources to feed predictive models.

What of assets? Climate change has a physical manifestation, for example a forest fire, that can be priced, but how do we measure what is happening to our “natural capital”? Things that allow us to function as human beings, for example clean water. A challenge for the FS industry is to attribute the right value to the natural capital, the concept is an innovation in itself.

Unfortunately, many innovation projects are approached from a technology perspective: “I have a great technology, find me a problem to solve”. This can result in cumbersome solutions. Ideally a project should be problem-led. Why? The early stages of the project will be entirely focused on understanding and defining the problem. As Einstein eloquently put it, “If I had an hour to solve a problem and my life depended on it, I would use the first 55 minutes determining the proper question to ask…”. Due to small budgets and other constraints, the ethical projects tend to operate in this problem-focused space. Necessity breeds invention

Let’s look at two examples of innovation.

A recent successful innovation in customer support is centred around augmenting AI with a “human touch”, recognising there are things that humans do well, and incorporating these in an AI framework – augmented intelligence. Using people to make AI better.

Another impressive project is the citizen science app, C-19 COVID Symptom Tracker developed by Kings College London and Zoe Global. Although not an FS project, our financial and physical wellbeing may well depend on it. Produced extremely quickly with clear requirements, the app itself is unremarkable, but the concept is pure innovation, gathering real-time UK population health data, backed-up by significant data science and medical expertise. Vital in the fight against a global pandemic.

And what do all these innovations have in common? Data. It’s all about the data darling.

Addressing the question “do innovation labs work? Or should FS companies just stick to the day job?” the answer is “yes, they can work”, if innovation is approached with a clear understanding of the problem, success is more likely. And remember, people can use products in a totally different way than designed, “induced” innovation – your project may just get lucky!