The Collateral Channel: From Unsecured Cash to a Pledgeable Asset

The key mechanism behind FinTech lending and later bank credit is not the word “technology.” It is the sequence linking a junior unsecured loan, a new asset, and a later bank claim. This chapter traces that sequence and tests its predictions against two alternatives: a FinTech loan may reveal useful information about a firm, or it may simply be refinanced quickly. The evidence helps decide whether the bank-credit increase is best understood as an asset-and-priority effect.

What the collateral channel predicts

The argument begins with a difference in what the first lender controls. A junior unsecured FinTech lender does not take a specified machine, vehicle, or building as collateral. The firm can therefore use the loan to acquire an asset without attaching that asset to the FinTech claim. If the asset is productive and a bank accepts it as security, the firm can later borrow against it. The bank receives a senior claim; the FinTech lender remains junior; and the firm has added bank credit without having financed the same asset with a senior bank claim in the first place.

The important word is later. The mechanism is not that the FinTech loan itself becomes safer or cheaper after the firm signs it. The mechanism is that the loan may change the firm’s future collateral position. A bank deciding on a second loan sees a firm with a new asset that can potentially support a senior claim. The firm has more debt than before, but it may also have more pledgeable capacity. The first loan has altered the order in which claims were placed on the asset.

That sequence generates a useful empirical fingerprint. If the collateral channel is operating, bank-credit growth should not be spread evenly across every type of credit. It should be strongest in products for which collateral matters, especially longer-term loans. It should also be stronger when the FinTech loan pays for a new asset rather than when it covers a purpose that leaves no newly pledgeable property. Finally, the firm should become more likely to pledge specific assets after receiving the FinTech loan.

The French study finds this pattern. Relative to matched bank borrowers, FinTech borrowers experience a 25% increase in long-term bank credit; relative to rejected FinTech applicants, the increase is 16%. The effects on used credit lines are weak, and the study finds no effect on other credit types such as leasing. That concentration matters. A general improvement in borrower sentiment or a broad signal of firm quality might increase several forms of credit. A mechanism based on assets that banks can secure should show up most clearly in collateral-intensive lending.

The timing of the long-term loans fits the sequence as well. The increase appears soon after the FinTech loan, develops over roughly three to six months, and then remains at a higher level. There are no differential trends between FinTech borrowers and benchmark firms before the outside loan. That does not prove that a specific machine was pledged in every case, but it is consistent with firms acquiring assets first and obtaining longer-term bank credit after those assets became available to a senior lender.

The direct collateral test goes one step closer to the mechanism.