Working Paper: NBER ID: w26330
Authors: Thomas Philippon
Abstract: The cost of financial intermediation has declined in recent years thanks to technological progress and increased competition. I document this fact and I analyze two features of new financial technologies that have stirred controversy: returns to scale, and the use of big data and machine learning. I argue that the nature of fixed versus variable costs in robo-advising is likely to democratize access to financial services. Big data is likely to reduce the impact of negative prejudice in the credit market but it could reduce the effectiveness of existing policies aimed at protecting minorities.
Keywords: Fintech; Financial Inclusion; Robo-advising; Big Data; Machine Learning
JEL Codes: G11; G2; G5; L1; N2
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| technological progress (O33) | decline in intermediation costs (G21) |
| roboadvising (G24) | democratization of access to financial services (G20) |
| big data and machine learning (C55) | reduction of biases against minorities (J15) |