On the 17th of October, EFIN, BEUC and CEPS-ECRI jointly organized a conference on the theme of Big Data, Fintechs and the role these technological developments play in addressing financial exclusion.
The conference was split between three panels: insurance, payments services and credit.
In the insurance panel, the discussion revolved especially around car insurance, telematics and self-driving cars, which might transform car insurance as we know it. Witold Jaworski, CEO of NIO (a company developing a telematics “pay as you drive” system) stressed that self-driving cars are still far from going mainstream and that car insurance relying on telematics is “fairer” to consumers since it adjusted to the way they drive. Greg Van Elsen, BEUC, nuanced these claims since no studies have yet demonstrated that the use of telematics provides consumers with a better/cheaper insurance. On top of that, the algorithms used to determine how your insurance is calculated differ among companies: acceleration/braking metrics are counted differently in calculating the rebate for driving more “responsibly”. Martin Schmalzried from COFACE Families Europe intervened to underline two points: first, that we would likely not have to wait for self-driving cars to disrupt car insurance given that more and more cars ship with obstacle avoidance and automatic breaking technology, second, that using telematics for the sole purpose of insurance is a waste, since the same data can be used to prevent/avoid accidents (for instance, cars equipped with telematics communicating with each other to alert the drivers when there is an accident).
In the payments services panel, Flora Coleman from Transferwise made it clear that money transfers, and specifically remittances, will be cheaper thanks to technology. The main question is whether consumers will be sufficiently knowledgeable and informed about these services in order to reap the benefits. Incumbents leverage their physical presence and their marketing power in order to keep consumers “locked in”.
In the credit panel, Martin Schmalzried was invited to speak on behalf of COFACE Families Europe. The main points raised were the following:
- Socialization of risk by restricting the data used for creditworthiness assessments: in order to avoid discrimination in creditworthiness checks, the data used for assessing creditworthiness should be restricted to the data that is strictly necessary. In COFACE-Families Europe’s view, this would only amount to current financial commitments (including ongoing loans), and repayment capacity (ability to save, income).
- Innovation in regulation to create a predictable regulatory environment for financial services: regulators need to adopt a mixed strategy in addressing the challenges of Fintechs, combining a technical and principle based approach. From the technical side, regulators can leverage algorithms to monitor and audit other algorithms (like those used for creditworthiness assessments) and test them for discrimination based on sex, religion, race, etc. On the other hand, regulators should draft a set of clear principles and values underlying their regulator approach, including non-discrimination, financial inclusion, proportionality etc. For instance, regulatory sandboxes should examine the business models of Fintechs to see if they are in line with those principles and values, in order to avoid having to deal with them once they are already rolled out and available to the general public (like Pay Day Lending and Dynamic Currency Conversion).
- Use Big Data for prevention, not punishment: instead of “punishing” consumers by making them pay extra premiums for behaviors that have been identified as “risky” by opaque, deep-learning algorithms, Big Data and algorithms should be used to identify root causes of certain behaviors and implement policies to shape the overall environment to prevent those behaviors. One example would be public health policies that incentivize employers to provide “physical activity” breaks for their employees to prevent back problems, instead of making people who sit long hours in front of their computers pay extra for health insurance.
Read also COFACE policy briefing on Big Data