Publications
The AI suply chain
Joint with L Gambacorta
Review of Network Economics, vol. 24 (2026), pp. 205-223.
BIS papers no. 154. , CEPR discussion paper 20143.
Intelligent financial system: How AI is transforming finance
Joint with I Aldasoro, L Gambacorta, A Korinek and M Stein
Journal of financial stability, Vol. 81 (2025), article 101472.
BIS working paper no. 1194, CEPR working paper no. 19181.
Big Techs in Finance
Joint with S Doerr, J Frost and L Gambacorta
Book chapter, Oxford Handbook of Banking, 4th edition, 2025.
BIS working paper no. 1194.
The design and adoption of fast payments
Joint with J Aurazo, C Franco, J Frost, P K Wilkens, A Kosse and C Velasquez
Journal of Payments Strategy & Systems, Vol. 18 (2024), no. 4, pp. 366-380(15).
Mobile payments and interoperability: Insights from the academic literature
Joint with M Bianchi, M Bouvard, R Gomes and A Rhodes
Information Economics and Policy, Vol. 65 (2023), article 101068.
BIS working paper no. 1092.
Working Papers
Joint with Debi Prasad Mohapatra. BIS working paper no. 1344, April 2026.
Why would a market leader choose not to patent an innovation? We study Samsung's decision to forgo patent protection for dual SIM technology in the Indian mobile handset market. Using a structural model of demand and supply estimated on quarterly product-level data from the Indian mobile handset industry, we document that rival firms' dual SIM products generated a \textit{preference discovery externality}. Rival firms' widespread adoption of the dual SIM technology allowed consumers to discover the value of the technology, also benefiting Samsung itself. Counterfactual simulations show that a patent would have suppressed this externality, reducing Samsung's equilibrium profits despite holding monopoly rights. Voluntary non-patenting was therefore privately optimal. Our findings shed light on wider debates about open-sourcing in software and other markets.
Joint with K Rishabh. BIS working paper no. 1343, April 2026
Media coverage: Fdi intelligence, FT
In this paper, we trace the geography and economic characteristics of firms that produce artificial intelligence (AI) products and services. Many economies around the world are evaluating their strategic priorities in AI, yet relatively little is documented about the global distribution of AI production. We construct a new database that identifies 1,246 AI-producing firms across 32 economies. We map these firms in each economy into the five layers of the AI supply chain: compute, cloud and related infrastructure, data tools, AI models and AI applications. The biggest markets for AI production are China and the US. Most economies specialise only in a few supply chain layers and many focus largely on compute. AI firms in all economies exhibit strong home bias in investment activity, with a focus on downstream applications. Finally, we find that venture capital inflows are strongly correlated with the presence and density of AI firms in a given economy.
Joint with J Aurazo, H Banka, G Galicia, N Ramteke and K Tanaka. BIS working paper no. 1295, October 2025
Fast payments are at the forefront of payments digitalisation globally. By enabling immediate availability of funds on a 24/7 basis, they offer the potential to enhance efficiency, promote financial inclusion, drive innovation and foster competition. Despite their growing adoption, key questions remain regarding the design of fast payments systems (FPS), particularly concerning pricing. Open issues around pricing of fast payments exist at three levels: between the FPS owner and participants (system level), among participants themselves (participant level) and finally between the participants and their customers (end user level). This paper provides a comprehensive overview of global practices in FPS pricing at these three levels. To relate these practices with the academic literature, particularly for the person-to-merchant (P2M) payments, we use a classical two-sided market model and analyse how different pricing schemes at the end user level might influence the volume of fast payments and overall social welfare. Our expository model shows that fast payment usage may be lower than socially optimal in many cases. Moreover, when all fees are zero, fast payments are unsustainable without external subsidies or alternative revenue streams for participants.
Tracing the adoption of digital technologies* (submitted)
BIS working paper no. 1166, February 2024
Internet-based digitalisation has ushered in a wave of economic and financial development in emerging markets, but digital divides remain. Narrowing these divides requires an understanding the drivers of technology adoption. The paper develops a structural model of consumer demand and supply to understand the main drivers of adoption of an essential digital technology: smartphones. Through counterfactual simulations, the paper quantifies the role of growth in income and in income inequality, expansion of 4G network coverage, foreign entry, and improvements in device quality in expanding adoption. The paper also provides a counterfactual comparison of three pro-adoption policies: an ad-valorem tax reduction, a uniform subsidy and a targeted subsidy.
*Previously circulated as "Explaining Smartphone Adoption in India" and "Adoption of digital technologies: The case of smartphones in India"
Work in Progress
Market structure and firm outcomes in AI
Joint with K Rishabh
How does a demand driven floor really work?
Joint with P Asberg-Sommar, M Drehmann and D Hansson
The impact of digital finance channels on saving and investment decisions in South Africa
Joint with Judith Bohnenkamp, Arif Ismail and Jon Frost