This paper examines the factors associated with valuation patterns in FinTech and RegTech mergers and acquisitions (M&A) using a global sample of 3739 completed transactions sourced from S&P Global Market Intelligence from 2008 to 2025. We develop and empirically validate an integrated theoretical framework combining digital platform theory, open innovation theory, and control-based theories of the firm. We test our five hypotheses using semi-log regression models with heteroskedasticity-robust standard errors. We document five main findings. First, full acquisitions are associated with valuation premiums nearly three times larger than traditional M&A control premiums in baseline specifications, which remain economically large (~188%) after correcting for sample selection. Second, cross-border transactions are associated with significantly higher valuations. Third, infrastructure-oriented FinTech and RegTech segments are valued more highly than consumer-facing segments. Fourth, transaction values increase systematically over time, consistent with declining uncertainty as the sector matures. Fifth, deal structure explains more variation in transaction values than temporal or geographic factors, reversing conventional valuation patterns observed in financial-sector M&A. We further document that tighter financing conditions significantly depress valuations, though the underlying structural drivers of the FinTech premium remain robust to these macroeconomic shifts. Our findings contribute to the banking and finance literature by demonstrating that M&A in FinTech and RegTech exhibit a distinct valuation regime shaped by digital platforms and innovation-driven control mechanisms.
Seitanidis et al. (Thu,) studied this question.