The contours of fintech 2.0 are becoming clear in era of AI governance

The industry is shifting from pandemic-era exuberance to AI-driven discipline, prioritising sustainable unit economics and robust governance over vanity metrics for long-term growth

The fintech funding exuberance of the early 2020s was a black swan phase, precipitated by the pandemic. It validated the fintech proof-of-concept, as both investors and consumers began to recognise the long-term potential of technology-led delivery of financial services. Fintechs, particularly in payments and consumer lending, attracted a disproportionate share of capital during this period, driven by rapid adoption and favourable market sentiment. As fintechs scaled, many moved away from their initial role as technology partners to incumbent financial institutions. They instead sought to directly serve customers, by pursuing regulatory licences to operate independently in niche fields. This expansion in scale and scope attracted heightened scrutiny, resulting in a series of regulatory interventions that disrupted many business models. Consequently, the sector witnessed a shift in focus from vanity metrics such as user growth, monthly active users, and gross transaction value toward more fundamental considerations around governance, compliance, conduct, and risk management. 

Fintech funding has moderated over the last couple of years, with total capital raised by fintechs hovering around $2.5 billion by most estimates. While still meaningful in absolute terms, this represents less than one-third of the funding levels peak of 2021. The earlier phase of investor exuberance, characterised by a “spray-and-pray” approach to seed funding, has given way to a more disciplined early- to mid-stage funding cycle, reflecting a preference for backing fintechs closer to product-market fit rather than higher-risk, speculative seed bets. This shift mirrors a broader correction in investment philosophy. 

Early-2020s fintech funding was driven by vanity metrics, with investors assuming that monetisation would inevitably follow scale. In contrast, the current cycle places a premium on predictability, sustainable cash flows, and demonstrable unit economics. Indian fintech funding has shifted to business-to-business and infrastructure-led models from business-to-consumer (B2C) growth-led narratives, driven by investor preference for capital efficiency, lower business-model volatility, and predictable revenues. B2C funding is now largely concentrated in mature, regulated, and multi-product platforms. 

An open question is whether this moderation in fintech funding represents a new structural normal, or whether investor exuberance could return, albeit in a different form? 

With artificial intelligence (AI) in play, it is almost certain that the fintech sector will witness another phase of non-linear growth before the close of this decade. Fintechs, particularly B2C platforms, are positioned to capture this AI-driven upside, given the structured nature of their data, decision-making processes, and strong feedback loops. AI can reshape the economics of B2C fintech models by addressing several structural constraints that limited scalability in the earlier cycle. Automation across onboarding, payments processing, underwriting, servicing, fraud monitoring, and collections can enable consumer fintechs to scale without proportionate increases in operating costs or headcount. AI-led customer segmentation and propensity modelling can improve acquisition efficiency, reduce reliance on incentive-driven growth, and lower customer acquisition costs. AI shall also support stronger retention and monetisation through more superior personalised pricing, credit limits, and product offerings and improving lifetime value of the customer. 

However, there will be caution which will be structural, not incidental. AI-driven models will need to demonstrate governance and control frameworks before being allowed to scale meaningfully. AI-enabled fintechs are likely to see funding initially favour controlled deployments, with larger capital flows following only once governance frameworks are established. While AI will accelerate value creation, it is also likely to temper the pace of unconstrained scaling. 

The early 2020s were about unbridled growth, the current is about discipline, and the next will be about buying into technology that makes growth sustainable. 

The writers are partner and financial services & risk advisory leader, and partner, financial, financial services risk advisory, at Grant Thornton Bharat