Coming together to discuss the next generation of payments and securities settlement data and information
Every year, I look forward to connecting with fellow researchers, academics and policymakers to discuss the future of payments.
This year, from July 27-28, Payments Canada, in partnership with the Bank of Canada and Deutsche Bundesbank, hosted a workshop on payments and securities settlement data and information. The objective of this annual workshop is to bring together national and international industry experts with an interest in payment systems to discuss recent payment research, spur discussions around the next generation of payment systems and share and learn from each other.
This one-and-a-half-day workshop covered various areas related to payments and securities settlement data and information including:
- The use of payment transactions data to predict key macroeconomic indicators;
- The economics underpinning the evolution of fintechs and the role they play within the payments and securities settlement ecosystem; and
- Ongoing developments in the digital currency space
The sessions that stood out the most to me were related to open banking. The discussions suggested that while there are many advantages to open banking, there remain a number of key research and policy-relevant challenges. Two key questions were brought to the forefront of the discussion.
The first question was: What are the drivers behind the adoption of open banking?
Data- and model-driven analyses presented during the session noted that contrary to conventional wisdom, competition﹘or lack thereof﹘in the banking sector is not important for the uptake of open banking. The most important driver for open banking adoption is trust in fintechs. In other jurisdictions, open banking laws have led to increased trust and venture capital investment in fintechs and open banking has resulted in more small-to-medium-enterprise lending. Both highlight the potential importance of peer-to-peer lending providers.
With regard to consumers, the discussions identified some potentially unfavourable effects of open banking depending on the type of open banking service under consideration (i.e., advice-based open banking vs. credit-based open banking). Advice-based open banking refers to the use of client financial or banking data by third-parties expressly to provide financial planning services; companies in this space include First Wealth and Open Advice. By contrast, credit-based open banking refers to the use of financial data by third parties for the primary purpose of extending loans and credit to clients; these include buy now, pay later (BNPL) schemes, personal or peer-to-peer loan services such as those provided by Finio Loans and Koyo.
The economic research presented specifically showed that advice-based open banking is the dominant application of open banking, and credit-based open banking results in an increase in data sharing and exposes those who choose not to share their data to higher costs. That is, individuals who choose not to share their personal information do not benefit from receiving better borrowing rates and conditions. This contrasts with individuals who do choose to share their personal information. Individuals who reveal background information about themselves – that lenders may find appealing – may offer those individuals better borrowing rates.
The second question was: Are there benefits to data sharing under credit-based open banking arrangements?
Open banking results in a trade-off between client privacy and potential gains from data sharing. While lower credit quality borrowers are more likely to be willing to share their data, there are benefits to all classes of borrowers – whether they have high or low credit quality – because the data allows fintechs to better tailor their lending conditions based on a client’s transactions history.
Particularly, payment data provides an indication of a borrowers’ sensitivity to price changes. That is, borrowers are more likely to opt in to data sharing if it gives them a favourable outcome – better borrowing rates. Nevertheless, experience from insurance markets suggests sharing data can be detrimental for people on the basis of race and other sociodemographic factors. Data sharing may also help foster financial inclusion for new immigrants who have a low default probability but do not have the credit history required by traditional lenders.
Another interesting presentation by Tarush Gupta, Associate Quantitative Analyst at Payments Canada, focused on the impact of macroeconomic shocks on payment value and volume. Our Business Economics team continues to develop data products and quantitative models to deliver valuable information to our members and internal business partners. This work helps us to identify potential risks stemming from extreme economic events such as COVID-19 and broader economic stagnation.
Many learnings were also shared from the Swiss and Mexican central banks on how Payments Canada can continue to improve our advanced forecasting of Canadian economic activity. Payment data is a record of every transaction that happens in the economy. We are actively looking at ways to leverage payment data to forecast indicators like Canada's GDP and inflation rates three-months earlier than traditional sources of economic measurement. You can read more about this research in our discussion papers.
I can’t overstate the importance of getting together to discuss and debate the future of payments with industry peers. It’s through this insightful, challenging and collaborative exchange of ideas that we shape the next generation of payments. I’m already counting down the days for next year’s workshop in Frankfurt, Germany. Until then, I look forward to continuing these important discussions at The 2024 Payments Canada SUMMIT, taking place from May 29-31, 2024, in Toronto.
Lead Economic Advisor