Lessons Learned -- Part 1

About a week ago, I was on the phone talking with an old business colleague and friend. We met each other during the 1990s, when the hot new things in financial services were swaps and the over-the-counter derivatives markets.

It occurred to me during the conversation that the FinTech landscape today feels so much like the derivatives landscape did in the early 1990s. A sense of limitless possibility permeates the sector, fueled by impressive new technologies. A strong streak of altruism permeates as well. Hope runs high that new data and new technologies will generate welfare-enhancing ways to minimize risk and expand economic opportunity. All of us caught up in the FinTech fervor (including policymakers) race to use the latest lexicon (e.g., DLT, RegTech, SupTech, InsurTech, RoboAdvice). A general consensus seems to exist that new financial tools necessarily must require new rules or, at the very least, old rules must be updated to reflect the new reality.

It was exhilarating to be part of the bank derivatives regulatory policy community in the early 1990s. It may be hard to believe now, but the bankers were the boring members of the community compared to the swap dealers. It is exciting to be part of the FinTech sector now. But it strikes me that it would be useful to learn a few things from the derivatives experience. So this blog series will reflect on lessons learned from the derivatives policy arena.

Lesson #1: Measurements Matter (or "Don't Over-State Your Importance At The Beginning")

Every new industry at the beginning wants to present a compelling case to regulators for specialized rules and accommodations. It wants to prove that the fledgling industry matters for public policy purposes. The easiest way to do this is to quantify the size of the industry. After all, size matters...right? The bigger the better, right?

In the late 1980s and early1990s, a range of options existed for measuring derivatives market activity. Three options existed: notional amounts, gross market value, and net market value. Each had merits.

  • Notional Amounts: reflect the total amount of value underlying each transaction. These were (and are) large numbers. They tend not be very volatile because the underlying are not traded. They provide a valuable sense of transaction volumes. But they provide very little insight into the risks inherent in the transactions individually or at the aggregate level.

  • Gross Market Values: reflect the amounts actually trading in the marketplace. They are therefore smaller than notional amounts by a significant degree. But they can over-state the risks because they do not consolidate the positive and negative amounts owed between counterpart pairs.

  • Net Market Values: As the name implies, these values reflect the actual amounts of cash exchanged by counterparts after netting agreements have taken effect. Netting agreements are separate contracts between derivatives counterparts. Close-out netting establishes how counterparts will settle amounts owing under a contract in the event that one counterpart experiences a bankruptcy or default event. Bilateral and multilateral netting agreements decrease the amount of funds flowing through the payment system by stipulating that when two-way payment flows exist the only amounts that will be paid are by the counterpart that has the higher obligation.

Example: If Counterparty A owes Counterparty B $10 and, at the same time, Counterparty B owes Counterparty A $20, then the only payment that occurs under a netting agreement is a single $10 payment from Counterparty B to Counterparty A.

Initially, the derivatives industry chose to publish data regarding the derivatives industry using notional amounts. The size illustrated the importance of the market. Net market values were no considered as reliable by regulators because at the time there was no guarantee that netting agreements would be declared valid in courts of law during insolvency proceedings. We will talk about this in Lesson Learned #3.

But then the market started experiencing....growing pains. A bout of volatility and mis-selling hit the markets in the mid-1990s just as the markets had acquired critical mass. Suddenly, the notional amounts created anxiety among both policymakers and market participants. The data chosen to project scale and importance backfired, amplifying fear and instability instead. Suddenly, it was far more important to understand from a policy perspective the shape, scope, and dynamics of derivatives risk rather than just the aggregate notional volume. A decade into the industry hitting critical mass in the financial sector, policymakers and industry leaders had to reconsider which data were the most meaningful indicators of the sector's size and importance.

Why This Lesson Matters to the FinTech Sector

These are heady days in the FinTech sector. Sandboxes that encourage experimentation are sprouting up like palm trees around the world. Central banks are publicly flirting with using Distributed Ledger Technologies someday in the official payment system and maybe even to issue official sector digital currencies. Progressive policymakers are thrilled that FinTech provides opportunities to deliver savings, investments, and safe payment systems to a part of the population that arguably needs it most: the "underserved" and the "un-banked." The potential to bring more transactions out of the shadows and into the formal financial system creates opportunities to enhance law enforcement priorities as well.

At the same time, questions regarding how to measure the size of the industry are bound to start cropping up. FinTechs will seem small compared to industry incumbents if the preferred metric is assets under management, deposits (which few FinTechs accept), assets (which few start ups have), or revenues. Fintechs may even seem small compared to industry incumbents if relative importance is judged in relation to the amount of data processed rather than funds transferred.

Chastened by the recent financial crisis and wisened by the newest thinking regarding financial stability, policymakers will be keen to ensure that size alone is not the determining factor when setting the perimeter of regulation for the FinTech sector. From Northern Rock and Countrywide to Greece and Cyprus, often the smaller players generated the largest amount of trouble.

So advocates in the FinTech sector might want to start thinking strategically as they prepare their public policy positions. Consider the following questions:

  • Will your preferred position or metric stand the test of time?

  • More importantly, will it survive the first real bout of market instability (or hacking event)?

  • Can your preferred position or metric manage to mature with the industry?

Savvy advocates and evangelists will keep a close eye on emerging regulatory policy trends as well. They will want to ensure that their preferred arguments address emerging policy concerns as they emerge. They will want to be sure they have learned Lesson #1 from the derivatives industry.

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