Regulators often lack the expertise and resources needed to assess the value of FinTech innovation, with instruments at their disposal being crude and underdeveloped. We advance a theory where FinTech innovators, incumbents, and regulators strategically respond to opportunities to innovate under uncertainty. In it, regulators acquire costly and imprecise information about the societal value of innovation while FinTech firms can not be certain about the regulatory response to this information. We show that the rate of innovation in FinTech depends on the budget and skills of the regulator in assessing the gains and risks to innovation, the private rents that accrue to innovators, and the number of FinTech firms with access to new technology. Multiple equilibria arise from the complementarity between regulatory preparedness/competence and investments into innovation, adding extrinsic risks to the regulation--innovation game. Among several policy implications, our theory shows that skilled regulators with ample budgets prompt FinTechs to innovate more.

We develop a credit market competition model that distinguishes between the information span (breadth) and signal precision (quality), capturing the emerging trend in fintech/non-bank lending where traditionally subjective (``soft'') information becomes more objective and concrete (``hard''). In a model with multidimensional fundamentals, two banks equipped with similar data processing systems possess hard signals about the borrower's hard fundamentals, and the specialized bank, who further interacts with the borrower, can also assess the borrower's soft fundamentals. Increasing the span of the hard information hardens soft information, enabling the data processing systems of both lenders to evaluate some of the borrower's soft fundamentals. We show that hardening soft information levels the playing field for the non-specialized bank by reducing its winner's curse. In contrast, increasing the precision or correlation of hard signals often strengthens the informational advantage of the specialized bank.

We develop and estimate a model of endogenous growth in productivity and bank efficiency, where banks adopt technology embedded in capital goods produced by entrepreneurs, and agents choose whether to become workers or capital-good-producing entrepreneurs. In this framework, bank efficiency influences productivity by affecting agents' occupational choices, while productivity, in turn, affects bank efficiency through the relative price of capital goods. We find that increasing technology adoption in the banking system to the level in the top half of the distribution in the data accelerates the economy's long-term growth from 2\% to 2.19 \%. We also find that empirical evidence based on U.S. bank, MSA, and state level data is consistent with the critical mechanisms of our model.