Speech by Governor Waller on financial innovation
Thank you to the Global Interdependence Center for inviting me to speak today. While my comments will touch on crypto-assets, they are more focused on innovation and the future of finance.1
Innovation has been defined as “the introduction of novelties; the alteration of what is established by the introduction of new elements or forms.”2 This definition does not decide whether innovation is a good or a bad thing. To our modern ears, innovation generally has a positive connotation – it is something desirable that we want to promote. But it is important to remember that there is also a long tradition of looking at innovation with suspicion. This comes to a fundamental point: Innovation is a double-edged sword, with costs and benefits, and different effects on different groups of people. This is a lesson we as financial supervisory authorities should keep in mind. Former Fed Chair Paul Volcker was a noted critic of financial innovation, noting that while credit default swaps and debt obligations may have helped some people hedge investment risk, they also played a key role in the global financial crisis. He famously celebrated the automated teller as a beneficial banking innovation, but was skeptical of most other financial innovations.3 When we think about crypto-assets, or other forms of innovation, we must think carefully about which edge of the sword we are looking at: Will the innovation create new efficiency gains, help reduce risk, increase financial inclusion; or will it create new or exacerbate existing risks?
Recently I commented on crypto assets,4 discuss how individuals can make their own choices about whether to invest in speculative assets, but I also said that banks and other intermediaries who choose to engage in crypto-asset-related activities must do so in a safe and sound manner. At the same time, the world is changing rapidly, and we must be open to the potential benefits of innovation. In that light, I focus my remarks on two areas of innovation that may have the potential to bring significant benefits – tokenization and artificial intelligence, or AI.
Tokenization
Let’s start with tokenization. As I discussed in my previous comments about cryptoassets, I think of the cryptoecosystem as consisting of several parts, including the database management protocol used to record trades, often referred to as the blockchain. A blockchain is ultimately a type of distributed database that can be used to record data, including ownership of assets and transactions in the asset (ie changes in ownership of assets).5 To date, blockchain has primarily served as a ledger for cryptoassets, but it may be suitable to play a similar role for traditional assets, such as securities and derivatives.
Before a blockchain can be used to facilitate transactions in traditional assets, the assets must first be “tokenized” – that is, represented on the blockchain so that the blockchain becomes the asset’s ledger. At that point, parties can engage in transactions with the tokenized asset by updating records on the blockchain.
Why would a financial institution undertake this process to tokenize an asset? What advantages does blockchain offer over traditional approaches to conducting transactions? I do not intend to provide exhaustive answers to these questions here, but I would like to highlight several areas.
First, blockchain can offer fast or even near-real-time transfers on a 24/7/365 basis, which, among other things, gives parties precise control over settlement times and in some cases can increase efficiency and reduce liquidity risk. Of course, I want to note that these benefits are not unique to blockchains. The Federal Reserve’s FedNow service, which is set to begin operations in July, does not rely on blockchain; and it will provide safe and efficient instant payment services in real time, around the clock, every day of the year.
Another potential advantage of tokenized assets is that they are “programmable” and have “smart contract” functionality. A smart contract is a computer program stored on a blockchain, which can be programmed to perform predefined actions when certain conditions are met. Once assets are tokenized, smart contracts can be used to construct and carry out transactions involving the asset. Once the smart contract is activated, the transaction continues automatically as long as the specified conditions are met. This is the sense in which smart contracts are smart: they do not rely on the parties to the transaction to implement them; instead, they implement themselves, based on the terms specified by the parties.
Smart contracts can allow what is called “nuclear settlement”. Instead of relying on each party separately performing its part of the transaction, smart contracts can effectively combine the two, or more, parts of the transaction into a single unified “atomic” action performed by the smart contract. This can be an extra robust way to achieve delivery-for-payment (“DVP”) and payment-for-payment (“PVP”) functionality, so that one part of a transaction is settled if and only if the other part is settled too. Atomic settlement is useful because it can reduce settlement and counterparty credit risk: it ensures that the buyer does not pay if the seller does not deliver; and vice versa that the seller will not deliver if the buyer does not pay.
In fact, private institutions are testing use cases to better understand the benefits and risks of this technology. Businesses have been conducting currency trades using blockchain technology with smart contracts in an effort to improve efficiency. Separately, financial institutions have used blockchain to facilitate intraday repo transactions. The parties to these transactions may have more flexibility as to when the transactions are settled, which in turn has the potential to create additional capital and liquidity efficiencies. And the blockchain’s atomic settlement functionality can serve as another way to achieve an important risk mitigation: using repurchase agreements as an example, the repo “seller” can have confidence that it will receive the specified loan amount in exchange for the collateral it provides; while the repo “buyer” knows it will receive the stated collateral.
This effort is still in the early stages, but I expect that as functionality expands to include more currencies, eligible securities, and new products, there will be more participation and growth.
That’s not to say that there aren’t risks associated with tokenization and the use of smart contracts: smart contracts can have bugs and potential cyber vulnerabilities; and instant settlement adds its own set of risks. But it’s a significant promise, and I look forward to seeing what private sector participants come up with to potentially improve the way traditional transactions are conducted.
Artificial intelligence
The second area I will discuss is artificial intelligence. Can you go anywhere without hearing about AI? AI, as I’m sure you know, is currently seeing a surge in interest thanks to so-called generative language models. These types of models can provide complex answers to user requests in conversational prose that come very close to passing the famous “Turing test” for artificial intelligence. You can ask it to write a 10-page story involving foxes, and a pretty polished short story will be ready for you in seconds. It can also develop presentations, summarize documents, do basic coding, and perform a variety of other functions, all at superhuman speeds.
It is now well documented that these generative language models are still fallible, and that the technology still has a way to go. The answers are often inaccurate, but even in these cases, they often are sounds like it knows what it’s talking about. As with other sources of information, it is important for anyone using these tools to assess the results with an appropriate critical eye and not take them at face value.
But the advances keep coming and we can only speculate what these models will be capable of in the years to come. So, what does all this mean for banking? Banks are already testing or using artificial intelligence in a number of areas. Banks have started using AI models to generate personalized product suggestions for their customers, and AI can even generate and send a customized marketing email to that customer based on the model’s product recommendations. Banks are also looking to AI for a range of customer service applications such as chatbots that can help reset passwords, locate a branch or ATM and check account balances without the need for human intervention. AI has also proven useful for fraud monitoring: for example, it can help banks detect potentially fraudulent credit card transactions, including by identifying new spending patterns that indicate fraud.
Banks have also begun to explore the potential of using artificial intelligence to refine the credit underwriting process and analysis, with the potential to speed up underwriting decisions and lower loan prices.
Like many innovations, AI involves new risks, or at least new variations of old risks. AI models are only as good as the data they are trained on. This can create challenges when AI is dependent on large volumes and different varieties of data, which can complicate the work of discovering problems or biases in data sets. Another important consideration is the “black box” problem, because with some AI models it can be difficult to explain how they arrive at outputs given a set of inputs (this is often called lack of explanation). In some cases, even the AI developers themselves may not know exactly how the AI approach works.
As I mentioned, we already see banks using AI in a number of ways and we have regular discussions with them about understanding and managing the risks associated with it.6 Whether and how they can use generative language models remains to be seen. The technology can bring new efficiency gains to banks’ software development processes; or has applications in customer service; or it may be useful in a way we have not yet anticipated. As with tokenized assets, I’m curious to see how banks can make further use of AI. I also want to make sure they do it in a responsible way.
Conclusion
Tokenization and AI are just a few of the innovations that could eventually come to play a prominent role in banking and, for that matter, the economy more generally. I could just as easily have been talking about Web3 or quantum computing today. All these innovations will have their champions, who will make claims about how their innovation will change the world; and I think it is important to look critically at such claims. But it is equally important to challenge the doubters, who insist that these innovations are a lot about nothing, or that they will end in disaster. The world will change and we should encourage innovations that show promising benefits for society, including the financial sector.
1. The views expressed here are my own and are not necessarily those of my colleagues at the Federal Reserve Board. Return to text
2. “Innovation,” Oxford English Dictionary, accessed 18 April 2023, Return to text
3. Paul Volcker, “Paul Volcker: Think More Boldly,” The Wall Street Journal14 December 2009, Return to text
4. Christopher J. Waller, “Thoughts on the Crypto Ecosystem” (speech at the Global Interdependence Center Conference: Digital Money, Decentralized Finance, and the Puzzle of Crypto, La Jolla, CA, February 10, 2023). Return to text
5. The remainder of this speech refers to tokenized assets represented on a blockchain. But assets can also be tokenized on other forms of distributed ledger technology. Return to text
6. Request for Information and Comment on Financial Institutions’ Use of Artificial Intelligence, Including Machine Learning, 86 Fed. Reg. 16837 (March 31, 2021). Return to text
