About The Project
The Financial Data Revolution:
Seizing the Benefits, Controlling the Risks
A data revolution is underway. We live amid the biggest commercial and social transformation since the Industrial Revolution: driven by the increase in volume of data; and advances in its algorithmic analysis. In 2018, 33 zetabytes (33 trillion gigabytes) of data was created, predicted to rise to 175 zetabytes (175 trillion) by 2025. By July 2021, the new Consolidated Audit Trail initiative of the US Securities and Exchange Commission expects, once operational, to be processing 58 billion financial transaction records every day.
Data can be used: (i) by providers to offer better financial services, (ii) by regulators to promote systemic stability and prevent abuses, and (iii) by consumers to receive better and more competitive services. This Laureate research project will analyse each of these uses of data in the context of finance.
On the upside, data and technology are revolutionising financial services so that they can be extended more broadly: improving lives, lifting economic growth and reducing poverty. In Australia the financial system serves small businesses and consumers poorly — in ways in which those of us with home loans are usually unaware. For instance, between April 2016 and July 2019, Australians borrowed over 4.7 million payday loans of up to $2,000 at 68% p.a. Our financial system today keeps poor people poor. The answer to this real financial hardship is technology — using algorithmically interpreted data to (i) accurately price risk, and thus credit, for these people (an example of FinTech), and (ii) to monitor the behaviour of those selling them the credit (an example of RegTech).
FinTech and RegTech
FinTech is software that deals innovatively with data to solve problems in financial services. US$478.4 billion was invested in it globally from 2017 to 2020. It includes robo-advice, peer-to-peer lending, crowd-funding, payments applications and new risk management methods. RegTech is software that deals innovatively with data to help firms meet their compliance obligations or to help regulators regulate. It is currently enabling cheaper financial services by reducing the regulatory compliance costs of banks, features in bank responses to the abuses identified by the Hayne Royal Commission in Australia, and in time will underpin all financial supervision by regulators.
This data revolution comes with many, as yet uncontrolled, risks. These relate to inaccurate data and its poor algorithmic analysis or other misuse, and are facilitated by poor regulation. These risks are global, none are uniquely Australian, and most are regularly ignored amid the hype. High profile FinTech risks to manifest here have been the long-running robo-debt scandal and Westpac’s 23 million breaches of anti-money laundering laws.
The implementation of the Consumer Data Right (CDR) progressively from 2020 will bring many more such risks as data that has previously been housed safely in one bank will suddenly be able to be moved between providers. Furthermore, FinTech can promote opacity and complexity, thus reinstating some causes of the 2008 GFC. RegTech, poorly applied, could mask an upcoming crisis. Peer-to-peer lending can generate destabilizing sub-prime loans as seen in China, and central bank digital currencies could readily facilitate the collapse of a banking system through the mother of all bank runs.
More generally, we need to learn how to regulate algorithms so they produce transparent and ethical outcomes, otherwise the damage to consumers will be massive. Doing so will also inform global responses to data risks beyond its use in finance and regulation, such as in judicial sentencing and healthcare.
As technological change accelerates, law struggles to respond, everywhere. This project will support the legal recrafting needed to allow realisation of the many benefits and curbing of the many severe risks of this data revolution in finance and regulation. Australia provides a highly suitable laboratory for this research, and the act of solving pressing regulatory problems in one legal system will generate learnings of relevance internationally.
Today’s laws are designed to deal mostly with “things”, tangible things, capable of being possessed and which, if sold, no longer belong to the seller. Data differs from things. You can transfer data about you to another and still possess it; or your bank can share data about you with another bank and all three entities have rights over it. Just as agriculture requires water, this data-driven transformation requires laws to protect and facilitate the use of data, and limit its misuse. Current, poorly adapted, laws often produce lose-lose outcomes – both thwarting innovation and not protecting consumers from the misuse of data about them. Regulation of innovative enterprises retards their growth as it quickly applies the onerous regulatory requirements that only the major banks can readily afford. Laws reduce cybersecurity in myriad ways by not being adapted to a data-driven world. Statutory requirements prevent functions of meetings being discharged by smart contracts and recorded on blockchains, and result in software solutions using work-arounds to accommodate ill-suited laws. Our tick-the-box consent model for data is a contractual approach suited to the sale of things – if you don’t like one apple buy another – but hopelessly adapted to a world with effectively only one social media platform, one major software provider and one search engine, and in which only 6% of people read privacy statements.
The Project's Aim
In short, while FinTech has great potential, current laws everywhere stifle its growth and fail to deal well with the attendant major risks. This knowledge gap is global. The major difference between progressive regulators, and those less adept, is that the former acknowledge they don’t know how to properly regulate the use of data and how it underpins FinTech and RegTech. This project sets out to assist law makers and regulators with the daunting challenges posed by the Data Revolution.
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