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This paper aims to examine the impact of traditional banks’ financial technology (FinTech) adoption on corporate loan spreads and lending practices.

This study examines the impact of FinTech adoption by banks on corporate loan spreads and lending practices. By analyzing data from bank 10-K filings, we develop a novel metric to assess FinTech adoption at the individual bank level. Our analysis reveals a significant positive correlation between increased FinTech adoption and higher corporate loan spreads, particularly for loans that are relatively informationally opaque. This causality is further validated through a quasi-natural experiment. Additionally, we identify trends toward loans with smaller sizes and longer maturities in banks with advanced FinTech integration.

Using a sample of corporate loans issued from 1993 to 2020, this paper documents a significant positive relationship between a bank’s increased FinTech adoption and higher loan spreads. This correlation is especially noticeable for loans that are informationally opaque. Moreover, the paper reveals trends toward smaller loan sizes and longer maturities with advanced FinTech integration in banks. Overall, these findings indicate FinTech enhances efficiency in processing hard information and holds the potential to enhance financial inclusion.

This paper contributes to two significant strands of finance literature. First, it highlights how banks with advanced FinTech integration gain advantages through enhanced processing of hard information. Furthermore, it underscores the role of FinTech in promoting financial inclusion, particularly for those borrowers facing informational opacity.

This paper aims to propose an alternative method to measure idiosyncratic volatility and test whether the idiosyncratic volatility puzzle holds in commodity futures markets.

This paper proposes a partially new measure of idiosyncratic volatility in commodity futures markets based on the Schwartz and Smith (2000) short-term/long-term model. This model enables us to capture systematic risks of commodity futures markets in a parsimonious way.

Using a sample of futures contracts for 20 commodities from 1973 to 2022, this paper demonstrates that idiosyncratic volatility is more significant than systematic volatility in commodity futures markets, and that the idiosyncratic volatility puzzle does not hold in these markets. This paper also performs robustness tests to investigate whether the puzzle holds during subsample periods when commodity markets are more volatile and find consistent results. This study highlights the differences between commodity futures markets and equity markets and emphasizes the importance of investigating idiosyncratic volatility in commodity futures markets.

The contributions of this paper are threefold. First, this paper contributes to the literature by focusing on the idiosyncratic volatility of commodity futures returns. Second, this paper constructs a partially new measure of idiosyncratic volatility in commodity futures markets. Finally, this paper also contributes to the literature on the idiosyncratic volatility puzzle and demonstrates that the puzzle may not exist in commodity futures markets.