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How can the financial services sector generate greater trust when it comes to data? Nicola Eschenburg says it can be done, and the sooner the better
Thursday 22 July
Read time: 3 mins
The 3 layers of data trust for financial services
Trust. Rarely does one word resonate so strongly across society. It affects all of us in different ways. It’s something that we, as individuals, yearn for. It’s something we want to generate – with each other, with our family, with our friends and with our colleagues. And it’s something we want to enjoy with all the groups and organisations we interact with.
But the thing about trust is that it doesn’t happen overnight. There’s that oft-repeated phrase about it taking “years to build, seconds to break and forever to repair”. Now, I’m not sure if I agree with that entirely – I wouldn’t instantly stop trusting my best friend if she forgot to meet me for a coffee – but it’s certainly true that it’s easier to lose trust than it is to create it.
And the financial services sector is no exception.

Confusion between trust and compliance

Data trust within the banking sector is currently driven by regulation, causing compliance to become a box checking exercise for many. Some banks are starting to try and do what’s right when it comes to data because that is what the customer wants, and not just because of compliance. For those that genuinely care and are trying to improve things, it’s like trying to turn a moving ship against the tide… And even if customers aren’t interested in the data itself, they are interested in the output. If they see banks using data for good, such as supporting vulnerable customers and demonstrating positive outputs, that will go a long way in increasing trust.
In order to do just that, data needs to move from compliance and defence to a source of value, and this needs to be informed by consumer nuances. For example, Generation Z is far more aware of data abuse, and many don’t have Facebook because they don’t trust it, which needs to inform how banks target this customer segment. Ultimately, it comes down to how data is used to inform the lifeblood of banks’ business, which needs to evolve.

The three layers of trust

What we need, then, is a way of understanding how trust can take root – particularly when it comes to data and its cascading uses across society. With algorithms holding increasing sway over how decisions are made and what we all do, we have identified three layers to help better understand trust – how to build, nurture and understand it.
The first is dispositional. By this we mean an individual’s enduring tendency to trust automation based on factors such as culture, age and personality. The second is situational, meaning the specific context and this is based on aspects such as an individual’s ability to freely evaluate an algorithm’s performance. And the third is learned which is based on past experiences relevant to specific system and its ongoing performance. Here, factors include pre-existing knowledge, design features, performance and situational factors not related to trust.

Data opportunities – more than just compliance

Data is where the opportunities lie for banks over FinTechs – they have more data and more clout, so in theory should find it easier to take the moral high ground and protect their customers, if they nail the question of data trust.
However, data identifying vulnerable victims is also like finding a needle in the hay stack, and banks don’t have as much confidence in what they are trying to identify as many may believe. At the end of the day, how do you trust what you don’t know? And throwing millions at the problem without knowing if it’s achieving the goal isn’t the solution. When looking for unknown unknowns… how do you know you’ve got them all? Or indeed that there was anything to catch in the first place? So the industry needs to take a step back and think about what would give them genuine confidence and not just the confidence they’d probably escape a fine if something went wrong!

Confidence boosters

The three layers of trust are applicable across both the private and public sectors, but there’s little doubt that the financial services sector has much to do. According to a recent report by Arizent, less than half of consumers have faith in financial services providers to protect their data privacy. That figure is worse against the backdrop of the pandemic, with only a quarter trusting financial services providers more than they did one year ago, with the rest saying their trust levels have stayed the same or declined. A similar study by Accenture also found that the rapid shift to digital banking during the pandemic has accelerated the erosion of consumer trust.
Financial institutions, though, can take solace in the knowledge that there are plenty of ways that they can improve their handling of data, demonstrate output and in turn, generate greater customer confidence.
For example, they can invest in learning and development to establish a culture of data confidence within their workforce. Data leaders need to think about how their people can be champions for data confidence, inspiring change and making data accessible.
Decision makers also need to remember that data doesn’t have to be scary. Data can be a highly complex data-set used to create an algorithm, but could be as simple as a customer’s date of birth. In other words, it’s important to humanise data – a process which can fall to the increasing cadre of data professionals across government departments.
In summary, data need not fuel mistrust of the financial services sector. On the contrary, handled well it can build confidence and, in doing so, help bridge the divide between consumers and their chosen bank.
We don’t need an algorithm to tell us that would be a good outcome.

About the author
Nicola Eschenburg is the FTS Venture Lead in the Futures team at BAE System Applied Intelligence


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