Search

This paper reviews how central banks are integrating non traditional data and artificial intelligence (AI) into policy analysis and operations. Using the Bank of Canada’s experience, it examines emerging applications, governance challenges, and strategic choices for responsibly scaling AI to enhance insight, efficiency, and institutional resilience.

This paper develops a general equilibrium model to assess central bank digital currency (CBDC) design in a monetary system where traditional banks and “crypto banks” (i.e., banks that issue stablecoins) coexist. We compare tokenized and non-tokenized CBDC, showing that their desirability depends on the reliability of private money provision, the availability of collateral assets and the features of the crypto sector.

DeFi lending with proper governance is operationally viable, but it also faces constraints related to capital efficiency, liquidation risk, and systemic fragility within the crypto ecosystem.

We study the competition between a welfare-maximizing public payment platform (e.g., CBDC or fast payment system) and a profit-maximizing private platform in a two-sided market, deriving optimal public pricing and showing how network effects, fragmentation, and policy mandates like zero fees or cost recovery shape welfare, usage, and fee incidence.

Project Samara was a real‑world experiment testing distributed ledger technology and wholesale central bank digital money for bond issuance and settlement in Canada. It demonstrated technical feasibility and potential efficiency and risk‑reduction benefits, while highlighting important trade‑offs related to complexity, governance, and regulatory alignment.

We use a randomization of question placement in surveys to estimate the causal effect on financial literacy results. We find that financial literacy questions placed at the end of a survey lead to a drop in financial literacy of 5%–15%. This research suggests a measure of financial literacy adapted for survey length.

Can artificial intelligence (AI) think and act like a cash manager? In this paper we explore how generative AI agents can help manage liquidity, prioritize payments and optimize efficiency in real-time gross settlement systems.

We study how participants in the Lynx payment system use the net send limit (NSL) tool to control their intraday payment outflow levels. Our results show that participants typically adopt a “set it and forget it” approach to scheduling NSLs and sometimes have distinct intraday NSL adjustment behaviours.

Central bankers argue that programmable digital currencies may compromise the uniformity of money. We develop a stylized model to examine this argument and the trade-offs involved in circulating programmable money.

We outline possible system architectures for an online retail central bank digital currency (CBDC) and identify one well-suited for basic payments. We analyze OpenCBDC 2PC, a representative system, finding such designs to be feasible, although some areas require further investigation. Our framing highlights other promising architectures for a retail CBDC.