One Fed’s view of how AI will impact finance

I was interested in this speech given the other day by Patrick T. Harker, President and Chief Executive Officer of the Philadelphia Federal Reserve Bank, because its title was: Fintech, AI, and the Changing Financial Landscape

The speech is broad, and focuses upon the risks of artificial intelligence (AI) and machine learning (ML) to the financial system. It is an interesting view from a regulator who is an economist but, more importantly, engineer by background.

Patrick begins by asking: “Why does the president of a Federal Reserve Bank care about artificial intelligence (AI), machine learning (ML), and these other emerging technologies? Doesn’t the Fed only care about interest rates?”

He answers the question by stating that “there is nothing about technology noted in the Federal Reserve’s dual mandate — the focus for our work which Congress handed down to us in the 1970s to clarify our goal as a central bank. The dual mandate says that the Fed must be concerned, first and foremost, with securing stable prices and maximum employment for the American people.”

Stable pricing needs, therefore, a close inspection of how money is being transacted and traded, whether it is physical or digital. More than this, as Patrick points out, there is a strong relationship between money and engineering. He quotes a piece written by the eminent engineer John Hayford, then director of the College of Engineering at Northwestern University:

“Economics and engineering are closely related. Economics has been defined as the social science of earning a living. With the same appropriateness, engineering may be defined to be physical science applied to helping groups [. . .] to make a better living.”

This is interesting as I am reading another economists book at the moment – David McWilliams’s Money: A Story of Humanity – and he also talks a lot about how money is our social technology alongside law, language and religion. Likening money to the invention of fire, the wheel, the plough and other physical technologies, it is our social technologies that complement these, and money is core of those social technologies. Without money, society would have disorder. You add law, language and religion, and you have social order structured under governance, whether that governance be a King, an Emperor, a government or a community.

This is an interesting point for me as I keep saying that you cannot have money without governance, but who is the government? It could be the internet community. Had that chat already.

This makes that whole discussion about the physical – engineering – combined with the digital – the economist – pretty interesting.

Anyway, back to Patrick’s presentation, and he posits the question that fintech is great but the evergreen question is: What is the end goal of the fintech revolution?

My view?

The end goal does not exist. There is just a constant change, and the winners are those who are most adaptable to change. This is why, when people ask about digital projects, objectives, deliverables, I always say that digital is not a destination but a journey into a continuum of change.

In the interim however, I think there is a transfer of power from the traditional 20th century institutions to the ready for the 21st century institutions. That means the move from a Wells Fargo or Barclays to a Chime or Monzo for retail customers or moving from a Citibank or HSBC to a Revolut or Starling for commercial customers … and that is happening, albeit in low-scale today (ed: what about tomorrow?).

Patrick answers this in his view with the comment that when game-changing technologies emerge, like AI and ML, we must think of the regulatory environments in which they work. There is no freedom without responsibility or, in my MCU words, with great power comes great responsibility. So, he recommends that regulators have to work in partnership with technology companies and financial institutions to make these things happen.

Nothing new there.

An interesting point he does make is picking on the works of New York University economist and professor Thomas Philippon and, specifically, his 2019 book, The Great Reversal.

Philippon takes a critical eye to the workings of the American economy over time, including the financial sector and, in doing so, found an interesting result. This is that the cost of monetary intermediation has grown massively in the last forty years.

Philippon looked at the cost of financial intermediation as a proportion of U.S. Gross Domestic Product over a 130-year span, from 1880 to 2010. What he saw was an upward trend line. In 1880, this share was 2 percent. For nearly a century, while there was both growth and some outlier boom years, this share of GDP never breached 6 percent until the 1980s. By the time his dataset reached its end point, in 2010, this figure was 8 percent.

For me that’s an interesting point as Andy Haldane, former Chief Economist with the Bank of England, said the same thing a few years ago at the Financial Services Club, also citing Philippon’s works and noting that most efficiency gains from technology have been taken as bonus payments for bankers in his view.

Banks take IT efficiency gains in bonus payments

Patrick therefore notes that there is a puzzle here.

“If we have so much more invested in the intermediary systems in the name of enhancing the efficiency and speed of our financial system, why has the cost remained steady? The financial system of 2024 is significantly more efficient than the financial system of 1924, let alone 1880 … so, why hasn’t this cost decreased by more?”

Being honest, Patrick says he doesn’t have the answer but, as mentioned, Andy Haldane blamed it on the bankers.

Equally, he moves on to discuss the old computer programmers' fear, “garbage in, garbage out” and that, when it comes to the nation’s financial system, keeping the garbage out takes on a new dimension of immediacy if you are trying to ensuring both fairness and resilience against risk. The question there is: how do you do that? How do you know what is garbage?

That comes back to the question I continually ask banks, which is that you cannot be smart with dumb data. Sort out your data. That’s not simple – you need to rationalise and consolidate years of historical systems that are fragmented and product-centric – but it can be done. Where there’s a will, there’s a way!

His speech finished with a final tech area: Quantum Computing.

“The imagined potential for QC to dramatically change how economic models are built and run is seemingly endless. From analysis of financial market data in detail we have not yet seen to conducting complex risk assessments with an accuracy we have yet to achieve with classical computing, and doing so with both real-time and historical data, QC will likely change the entire game.”

Truth.

Patrick concludes by saying: “The choice of whether AI has a huge positive or not-so-positive effect is not a matter of technology — it is a matter of how we, as humans, choose to use technology.”

Truth.

What surprised me is that his speech focused mainly on AI and ML, but with no mention of digital currencies. We live in a fascinating moment where central bank, stablecoin and cryptocurrencies are changing the world and challenging governments and regulators everywhere. I guess he didn’t want to go down that rabbit hole.