A quiet revolution is underway at the heart of many of our best-known financial institutions. A revolution stirred up by a surprising cross set of people: data specialists, product managers and marketers, united by one thing - the belief that an ethical approach to using data isn’t just compliance by another name but a new source of competitive advantage.
The challenge that professionals at Barclays and other leading firms are addressing is operationalisation - how to make a values-based concept like data ethics integral to how they do business.
When the Open Data Institute released the first Data Ethics Canvas in September 2017, few anticipated that some of the earliest adopters would be financial services businesses. The reasons retail banks like Barclays and Lloyds led the way on data ethics are well understood but worth restating.
Firstly, financial services collect, manage and use a large amount of sensitive personal information. Ensuring both the ethical and legal handling of this data is crucial - from protecting the privacy and security of individuals to ensuring data isn’t misused in ways that are legal but that people feel uncomfortable with.
Secondly, data ethics helps to build trust and maintain the reputation of financial institutions. Regulators, shareholders and employees all want to see financial services businesses behaving in trustworthy ways regarding data.
Thirdly, data ethics plays an important role in preventing discriminatory practices. Financial institutions use data for lending, insurance, and other financial decisions. If data is not handled ethically, it can lead to biased outcomes and unfair treatment of individuals based on things like their demographic characteristics.
Lastly, financial services are subject to data protection and privacy regulations, such as the GDPR (the EU’s General Data Protection Regulation), the GLBA (the Gramm-Leach-Bliley Act, a data privacy regulation for US-based financial institutions) and the CCPA (the California Consumer Privacy Act, often called “California’s GDPR”).
Regulations don’t completely clarify what people can and can’t do. The GDPR, for example, is a principles-based, not a rules-based, regulation, leaving many grey areas undefined.
Grey areas are places businesses rightly fear to tread. However, shining a light on data ethics in unclear situations allows for identifying unintended consequences and potential mitigation tactics. This opens up space for innovation in areas where the GDPR doesn’t offer clear guidance.
The ODI has always suggested that regulations like the GDPR can help liberate businesses from uncertainty about what is acceptable. And to help people move beyond the basic questions the GDPR helps resolve, the ODI Data Ethics Canvas examines more complex questions like “Should we do this, and if so, how do we avoid bad outcomes?”.
Research shows only 60% of consumers trust banks with personal data. The survey, which included 1,200 consumers across Europe, revealed that convenience is a key factor in technology adoption within the financial services sector. However, security concerns and a general dislike of AI-based services are barriers to widespread adoption.
A steady stream of bad data news hasn’t alleviated consumer concerns. From biased algorithms to worries about credit scoring, customers are provided with little evidence to revise their opinions about the trustworthiness of their financial service providers.
This is why Charles Randell, Chair of the UK's Financial Conduct Authority, has cautioned that the consumer finance sector may face a "Cambridge Analytica moment" if it fails to maintain public trust in its data handling practices.
Whilst fears of a consumer backlash have played their part in catalysing a focus on data ethics in the sector, so has the recognition that closing the trust gap can offer businesses a competitive advantage.
“It’s important for customers to trust us with their data at the same level as they do with their money.”
- Russell Barton, Barclays Bank
The potential for using data more effectively to benefit customers and the business itself has driven recent digital and data transformation efforts. Moving beyond simple transformation for the sake of efficiency, initiatives like Open Banking have highlighted the opportunities for trustworthy data use that also delivers innovation.
Whilst many organisations have made great progress in implementing data ethics practices, a lack of skills holds the sector back. Most of the problem is foundational - people misunderstand data ethics and its role.
Mention “ethics,” and many will imagine a common set of virtues and values. People think of ethical brands as those that actively communicate their environmental, supply chain and social efforts. These are, of course, admirable initiatives. However, ethics are not consistent across cultures, companies and communities. This, and a common assumption that an appropriate level of ethics is either unachievable or counterproductive in financial services, might make it feel easier to keep ignoring ethics and carry on.
The presence of data regulation exacerbates any temptation to disregard data ethics and hope everything will be okay. There’s a belief that simply conforming to regulations like the GDPR makes the use of data ethical. This is not the case. The GDPR’s principles-based framework leaves room for interpretation. And in complex areas, for example, crime detection, following principle-based legislation and common sense is not enough.
This is where data ethics skills and frameworks are essential.
Knowledgeable data ethics practitioners understand how to guide organisations through ethical danger zones. They help surface the ethical values an organisation shares with its employees, customers and community. They implement practices that not only help businesses avoid the kind of reputational harm Charles Randell and others want the sector to avoid but also apply data ethics as a form of data design practice - a practice that ensures data projects create value whilst avoiding harm.
The desire to deliver trustworthy innovation and reduce the potential for harm is behind efforts to make data ethics part of data projects. This starts with integrating data ethics into data strategy.
With any strategy, the key to success is execution. For data ethics, execution involves operationalisation - making data ethics integral to how a business collects, manages, uses and shares data.
That journey starts with improving awareness and knowledge and designing ethical practices based on industry benchmarks. For Barclays and other financial institutions, this has involved a range of tactics:
Beyond skills and awareness, there are some common strategies for building brands that are trusted with data:
¹ https://www.theodi.org/article/nearly-9-in-10-people-think-its-important-that-organisations-use-personal-data-ethically/