Banking’s data revolution needs ethics as well as innovation
With 2.5 quintillion bytes of data created every day, the exchange of information has become integral to the way we live.
The opportunities data analytics can create for consumers are vast – as is the commercial potential.
There are now more than 4,000 data brokers worldwide. Governments across the world are grappling with questions over who owns data and the liabilities surrounding this ownership.
But just as it is difficult for customers to keep up with the pace of change, the same is true of regulation. Regulatory-based compliance will never be enough in the fast-paced area of new technology.
Instead, responsible firms will need an underlying ethical approach that maintains trust and matches customer expectations.
Like many other sectors, banking is already beginning to use data analytics and automation to transform customer experience, from developing “predictive banking” that analyses a customer’s account in order to offer personalised insights, to looking at how artificial intelligence (AI) could be used to assist loan approval and management to speed up decisions.
If the industry gets this right, the opportunities are enormous. Companies that invest in data analytics have grown three times more quickly than those which are less analytically driven. And for consumers, automation could bring about better money management and advances in financial inclusion.
But to achieve that, we have to acknowledge the risks, not only in terms of operational and regulatory liabilities, but also potential reputational damage if firms get this wrong. Ethics and innovation have to come together to make this revolution work.
And so UK Finance and KPMG have identified five key principles to ensure data analytics are developed ethically by financial institution.
First, financial institutions must respect freedom of choice, in particular by not unduly limiting customers’ access to information or manipulating them to act against their interests.
Second, to safeguard equality and fairness, financial institutions should weigh up the pros and cons of any new innovation from a customer’s perspective, including harms like impacts on privacy or accidental discrimination.
Third, firms should understand how their AI and analytics reach conclusions and should, as far as possible, be transparent in explaining this to customers.
Fourth, they should adopt an organisation-wide approach, led by senior leaders who are evangelical yet practical in their support for ethical data use. This needs to be embedded as business as usual.
And finally, firms need to establish accountability and be clear who is responsible for what, including testing and monitoring.
Earlier industrial revolutions brought great advantages for society, but also led to societal challenges, like impacts on labour markets, which were difficult to identify immediately. It took time before sustainable frameworks were embedded.
This time carries the same risks. We have to find a balance to ensure that the fourth industrial revolution and advanced analytics are a force for good for everyone.