22
Aug

Big Data, Financial Inclusion and Privacy for the Poor

Guest Post by Dr Katharine Kemp, Research Fellow, UNSW Digital Financial Services Regulation Project

Financial inclusion is not good in itself.

We value financial inclusion as a means to an end. We value financial inclusion because we believe it will increase the well-being, dignity and freedom of poor people and people living in remote areas, who have never had access to savings, insurance, credit and payment services.

It is therefore important to ensure that the way in which financial services are delivered to these people does not ultimately diminish their well-being, dignity and freedom. We already do this in a number of ways – for example, by ensuring providers do not make misrepresentations to consumers, or charge exploitative or hidden rates or fees. Consumers should also be protected from harms that result from data practices, which are tied to the provision of financial services.

Benefits of Big Data and Data-Driven Innovations for Financial Inclusion

“Big data” has become a fixture in any future-focused discussion. It refers to data captured in very large quantities, very rapidly, from numerous sources, where that data is of sufficient quality to be useful. The collected data is analysed, using increasingly sophisticated algorithms, in the hope of revealing new correlations and insights.

There is no doubt that big data analytics and other data-driven innovations can be a critical means of improving the health, prosperity and security of our societies. In financial services, new data practices have allowed providers to serve customers who are poor and those living in remote areas in new and better ways, including by permitting providers to:

  • extend credit to consumers who previously had to rely on expensive and sometimes exploitative informal credit, if any, because they had no formal credit history;
  • identify customers who lack formal identification documents;
  • design new products to fit the actual needs and realities of consumers, based on their behaviour and demographic information; and
  • enter new markets, increasing competition on price, quality and innovation.

But the collection, analysis and use of enormous pools of consumer data has also given rise to concerns for the protection of financial consumers’ data and privacy rights.

Potential Harms from Data-Driven Innovations

Providers now not only collect more information directly from customers, but may also track customers physically (using geo-location data from their mobile phones); track customers’ online browsing and purchases; and engage third parties to combine the provider’s detailed information on each customer with aggregated data from other sources about that customer, including their employment history, income, lifestyle, online and offline purchases, and social media activities.

Data-driven innovations create the risk of serious harms both for individuals and for society as a whole. At the individual level, these risks increase as more data is collected, linked, shared, and kept for longer periods, including the risk of:

  • inaccurate and discriminatory conclusions about a person’s creditworthiness based on insufficiently tested or inappropriate algorithms;
  • unanticipated aggregation of a person’s data from various sources to draw conclusions which may be used to manipulate that person’s behaviour, or adversely affect their prospects of obtaining employment or credit;
  • identity theft and other fraudulent use of biometric data and other personal information;
  • disclosure of personal and sensitive information to governments without transparent process and/or to governments which act without regard to the rule of law; and
  • harassment and public humiliation through the publication of loan defaults and other personal information.

Many of these harms are known to have occurred in various jurisdictions. The reality is that data practices can sometimes lead to the erosion of trust in new financial services and the exclusion of vulnerable consumers.

Even relatively well-meaning and law-abiding providers can cause harm. Firms may “segment” customers and “personalise” the prices or interest rates a particular consumer is charged, based on their location, movements, purchase history, friends and online habits. A person could, for example, be charged higher prices or rates based on the behaviour of their friends on social media.

Data practices may also increase the risk of harm to society as a whole. Decisions may be made to the detriment of entire groups or segments of people based on inferences drawn from big data, without the knowledge or consent of these groups. Pervasive surveillance, even the awareness of surveillance, is known to pose threats to freedom of thought, political activity and democracy itself, as individuals are denied the space to create, test and experiment unobserved.

These risks highlight the need for perspective and caution in the adoption of data-driven innovations, and the need for appropriate data protection regulation.

The Prevailing “Informed Consent” Approach to Data Privacy

Internationally, many data privacy standards and regulations are based, at least in part, on the “informed consent” – or “notice” and “choice” – approach to informational privacy. This approach can be seen in the Fair Information Practice Principles that originated in the US in the 1970s; the 1980 OECD Privacy Guidelines; the 1995 EU Data Protection Directive; and the Council of Europe Convention 108.

Each of these instruments recognise consumer consent as a justification for the collection, use, processing and sharing of personal data. The underlying rationale for this approach is based on principles of individual freedom and autonomy. Each individual should be free to decide how much or how little of their information they wish to share in exchange for a given “price” or benefit. The data collector gives notice of how an individual’s data will be treated and the individual chooses whether to consent to that treatment.

This approach has been increasingly criticised as artificial and ineffectual. The central criticisms are that, for consumers, there is no real notice and there is no real choice.

In today’s world of invisible and pervasive data collection and surveillance capabilities, data aggregation, complex data analytics and indefinite storage, consumers no longer know or understand when data is collected, what data is collected, by whom and for what purposes, let alone how it is then linked and shared. Consumers do not read the dense and opaque privacy notices that supposedly explain these matters, and could not read them, given the hundreds of hours this would take. Nor can they understand, compare, or negotiate on, these privacy terms.

These problems are exacerbated for poor consumers who often have more limited literacy, even less experience with modern uses of data, and less ability to negotiate, object or seek redress. Yet we still rely on firms to give notice to consumers of their broad, and often open-ended, plans for the use of consumer data and on the fact that consumers supposedly consented, either by ticking “I agree” or proceeding with a certain product.

The premises of existing regulation are therefore doubtful. At the same time, some commentators question the relevance and priority of data privacy in developing countries and emerging markets.

Is data privacy regulation a “Western” concept that has less relevance in developing countries and emerging markets?

Some have argued that the individualistic philosophy inherent in concepts of privacy has less relevance in countries that favour a “communitarian” philosophy of life. For example, in a number of African countries, “ubuntu” is a guiding philosophy. According to ubuntu, “a person is a person through other persons”. This philosophy values openness, sharing, group identity and solidarity. Is privacy relevant in the context of such a worldview?

Privacy, and data privacy, serve values beyond individual autonomy and control. Data privacy serve values which are at the very heart of “communitarian” philosophies, including compassion, inclusion, face-saving, dignity, and the humane treatment of family and neighbours. The protection of financial consumers’ personal data is entirely consistent with, and frequently critical to, upholding values such as these, particularly in light of the alternative risks and harms.

Should consumer data protection be given a low priority in light of the more pressing need for financial inclusion?

Some have argued that, while consumer data protection is the ideal, this protection should not have priority over more pressing goals, such as financial inclusion. Providers should not be overburdened with data protection compliance costs that might dissuade them from introducing innovative products to under-served and under-served consumers.

Here it is important to remember how we began: financial inclusion is not an end in itself but a means to other ends, including permitting poor and those living in remote areas to support their families, prosper, gain control over their financial destinies, and feel a sense of pride and belonging in their broader communities. The harms caused by unregulated data practices work against each of these goals.

If we are in fact permanently jeopardising these goals by permitting providers to collect personal data at will, financial inclusion is not serving its purpose.

Solutions

There will be no panacea, no simple answer to the question of how to regulate for data protection. A good starting place is recognising that consumers’ “informed consent” is most often fictional. Sensible solutions will need to draw on the full “toolkit” of privacy governance tools (Bennett and Raab, 2006), such as appropriate regulators, advocacy groups, self-regulation and regulation (including substantive rules and privacy by design). The solution in any given jurisdiction will require a combination of tools best suited to the context of that jurisdiction and the values at stake in that society.

Contrary to the approach advocated by some, it will not be sufficient to regulate only the use and sharing of data. Limitations on the collection of data must be a key focus, especially in light of new data storage capabilities, the likelihood that de-identified data will be re-identified, and the growing opportunities for harmful and unauthorised access the more data is collected and the longer it is kept.

Big data offers undoubted and important benefits in serving those who have never had access to financial services. But it is not a harmless curiosity to be mined and manipulated at the will of those who collect and share it. Personal information should be treated with restraint and respect, and protected, in keeping with the fundamental values of the relevant society.

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References:

Colin J Bennett and Charles Raab, The Governance of Privacy (MIT Press, 2006)

Gordon Hull, “Successful Failure: What Foucault Can Teach Us About Privacy Self-Management in a World of Facebook and Big Data” (2015) 17 Ethics and Information Technology Journal 89

Debbie VS Kasper, “Privacy as a Social Good” (2007) 28 Social Thought & Research 165

Katharine Kemp and Ross P Buckley, “Protecting Financial Consumer Data in Developing Countries: An Alternative to the Flawed Consent Model” (2017) Georgetown Journal of International Affairs (forthcoming)

Alex B Makulilo, “The Context of Data Privacy in Africa,” in Alex B Makulilo (ed), African Data Privacy Laws (Springer International Publishing, 2016)

David Medine, “Making the Case for Privacy for the Poor” (CGAP Blog, 15 November 2016)

Lokke Moerel and Corien Prins, “Privacy for the Homo Digitalis: Proposal for a New Regulatory Framework for Data Protection in the Light of Big Data and the Internet of Things” (25 May 2016)

Office of the Privacy Commissioner of Canada, Consent and Privacy: A Discussion Paper Exploring Potential Enhancements to Consent Under the Personal Information Protection and Electronic Documents Act (2016)

Omri Ben-Shahar and Carl E Schneider, More Than You Wanted to Know: The Failure of Mandated Disclosure (Princeton University Press, 2016)

Productivity Commission, Australian Government, “Data Availability and Use” (Productivity Commission Inquiry Report No 82, 31 March 2017)

Bruce Schneier, Data and Goliath: The Hidden Battles to Collect Your Data and Control Your World (WW Norton & Co, 2015)

Daniel J Solove, “Introduction: Privacy Self-Management and the Consent Dilemma” (2013) 126 Harvard Law Review 1880