This paper provides a conceptual framework for citizen- centricity, breaking it down into system- level design features. It provides case studies of three SP- DPIs in the Indian context, and surfaces crucial learnings about their design.

As algorithmic systems increasingly shape financial decisions, this blog explores how they can de-humanize individuals by reducing them to data points.

India’s financial inclusion story over the last decade has been remarkable, with dramatic expansion in account ownership and sustained growth in credit. Yet, evidence increasingly points towards a gap between access and impact as witnessed in high rates of dormant accounts and the ongoing NPA crisis in the microfinance industry.

The study was conducted in two contrasting geographic contexts of rural Punjab and urban Tamil Nadu, using qualitative research methods involving 30 WNEs.

Access to suitable credit could enable growth-oriented nano-enterprises to invest in productive assets, adopt new technologies, smooth working capital cycles, and expand their scale of operations.

Our submission in this paper is that impact measurement in financial inclusion, i.e., financial health measurement can, and ought to, play a more diagnostic role in financial inclusion strategy. This is the conceptual departure that the title of the paper describes as the shift ‘from a canary in a coalmine to a thermostat’.

This paper argues that institutional stability and change in social protection policy in India are best explained through the explanatory power of ideas and the interactive processes of discourse. However, traditional institutionalist theories, whether rational choice, sociological, or historical, tend to underplay the role of ideas and discourse as drivers of institutional stability and change.

In this blog, the author has attempted to summarise the vast literature on the determinants of financial inclusion using a framework developed by Moscona et al (2026).

In this blog, we trace the emerging contours of India’s domestic approach to governing AI in finance and identify the priorities that should shape the next phase of policy thinking, in light of alarm bells triggered by Mythos, and OpenAI’s cybersecurity initiative, Daybreak.

The growing prominence of Responsible and Trustworthy AI (RTAI) frameworks reflects increasing recognition of these harms. Contemporary RTAI approaches recommend safeguards across the lifecycle of AI systems to ensure explainability, transparency, contestability, auditability, and human oversight, while reducing the potential for bias and discrimination.