Online lending through fintech firms is a rapidly expanding segment of the financial market that is receiving much attention from investors and increasing scrutiny from regulators. Research is only beginning to assess how fintech firms' entry is altering the choices and outcomes of small businesses that borrow from them. The Federal Reserve Small Business Credit Survey is a unique data source on the experiences of business owners with new and more traditional sources of credit. We find that the businesses using online lenders are not representative of small and medium-size enterprise in the US. Businesses borrowing online are younger, smaller, and less profitable. Through reaching borrowers less likely to be served by traditional lenders fintech lenders have substantially expanded the small business finance market. We apply treatment effects estimators to flexibly control for composition differences in the borrowers. After controlling for compositional differences between online and bank borrower, we find that loan application amounts are generally smaller with fintech lenders; businesses that receive fintech loans expect more revenue and employment growth than those receiving a bank loan; and businesses that borrow from banks are more satisfied than businesses that borrow online, which are still more satisfied than businesses who were denied credit. These results highlight issues that the financial industry and regulators should examine as fintech lending to small businesses continues to expand.

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This paper is concerned with the 513 isomorphism classes of degree 12 2-adic fields whose automorphism groups have order 4. For each extension, we identify a defining polynomial, the extension's ramification index, residue degree, and discriminant, and the Galois group of the extension's normal closure. These results extend previous work of Jones-Roberts, Awtrey, and Awtrey-Shill.