AI can streamline financial regulation, but systemic reform and power imbalances must be addressed
Original framing: “Why AI could be a financial ‘sludge’ buster” — Financial Times
Robust scientific evaluation demands transparent datasets, reproducible validation, and bias diagnostics. Current pilot projects often rely on proprietary data, limiting peer review and obscuring error propagation that could affect vulnerable borrowers.
AI offers a promising lever to streamline financial compliance, but its impact is mediated by entrenched power structures, historical patterns of technocratic reform, and cultural norms of governance.
By integrating Indigenous accountability, rigorous scientific validation, and cross‑cultural lessons from mobile‑money ecosystems, we can redesign AI tools to serve public interest rather than reinforce elite capture. Institutionalising transparent impact assessments, fostering open‑source co‑design, and reshaping regulator incentives together create a feedback loop that aligns efficiency with equity. Ultimately, embedding marginalized voices and employing trickster insights uncovers the paradoxes that simple techno‑optimism hides, guiding a systemic transformation of financial regulation.