Tokenization: Preventing the Next Subprime Crisis

As we stand at the next frontier in finance with the AI revolution, a more silent, yet no less important, change is taking place: tokenization.

Tokenization is nothing more than converting all sorts of financial assets into tradable tokens that can include different categories, asset classes, risk classes and returns. These tokens can be traded seamlessly at much faster trading and settlement speeds.

While tokenization has been discussed for a couple of years, the trade mechanism and, more importantly, the underlying risk have not been fully grasped. With the immense opportunity to provide a more liquid market, there must be sufficient assurances to protect investors and thus the asset itself.

Thinking as an investor and a current “slow-moving asset trader,” there are many areas that should be covered. Let me begin with the explanation for the slow-moving trading comment. I’m currently involved in Capital Markets funding for an asset-backed financial corporation. In this line of work, one of my primary functions is to look at the market and seek asset-backed transactions that could be traded for many different reasons, such as price sensitivity, concentration risk or incremental exposure. I am, of course, referring primarily to non-delinquent portfolios, which are the type of assets I am considering in the context of this discussion.

Participants in the financial system should remain cautious of opportunities that package different risk classifications within the same token, potentially creating risks similar to those seen in the 2008 subprime crisis. At that time, mortgages with different credit characteristics, including subprime and near-prime loans, were packaged into Mortgage-Backed Securities (MBS), divided into different tranches with different levels of seniority and credit ratings. Some of these MBS were subsequently pooled into Collateralized Debt Obligations (CDOs), which were also divided into tranches and rated by rating agencies.

The problem was not simply the presence of subprime mortgages, but that models and ratings underestimated the probability and severity of a broad decline in house prices and, more importantly, the extent to which mortgage defaults could become highly correlated. As house prices declined, borrowers increasingly became unable to refinance or sell their homes, leading to higher delinquencies and foreclosures. Losses then spread through the MBS and CDO structures, including highly rated tranches that had been considered relatively safe.

This created significant losses and uncertainty around the value of the underlying assets. As liquidity disappeared, determining their true value became increasingly difficult, while the final investor remained far removed from the original transaction and underlying asset.

After briefly reviewing the scenario that created the subprime crisis, there are many opportunities to learn from it and develop this new era of tokenization.

Significant Differences

There are quite a few significant differences between both instruments, and a very important one is technological. The main difference is the use of blockchain, where the traceability of an asset, its ownership and the asset that gave birth to the transaction can potentially be viewed and accounted for clearly, no matter how many changes in ownership have taken place. This, of course, must be tightly guarded in an age of technological advance where new technologies always create operational opportunities as well as potential threats.

When the tech and operational hurdle is cleared, we go into what I would describe as the most important challenge to the token. I briefly described my current business as slow-moving trading, where first choosing a transaction is not as hard as underwriting that transaction, which is where the slow part comes into play. The slow part is very important because to underwrite a financial asset, particularly an asset-based lender’s financial asset, many things come into play. Let me share the overall idea:

First, we have to look at counterparty risk. In this case, that would be the party who originated the transaction and who analyzed the final client’s creditworthiness. Within this analysis, the considerations must include how the original party performs its underwriting, what financial information was required and available, and the actual asset quality and expected current and final value. There should be additional consideration for legal documentation quality, ease of enforcing the guarantees, and finally, transaction settlement.

Another important consideration is correlation and concentration risk. A portfolio may contain hundreds or thousands of transactions, but if they share the same industry, geography, economic factor or originator, they may still be exposed to the same underlying risk. As the 2008 crisis demonstrated, diversification of individual assets does not necessarily mean diversification of risk.

Providing Transparency

In just looking at this previous section, there are several different risk assessments that could require an independent risk or credit rating for each section. With so many areas to be rated, there could be an opportunity for rating agencies to pool these different ratings and build a composite rating system, with a layer for each rating, that can give clarity to the investor who will invest in each token.

The objective would not simply be to give the token a single rating, but to provide transparency into where the risk actually comes from: the counterparty, the underwriting, the underlying asset, its valuation, the legal enforceability, the expected recovery or the concentration of the portfolio. In this way, the investor could understand not only the overall risk of the token, but also the individual components that create that risk.

As we have seen, tokenization is a great opportunity to improve market liquidity, speed and traceability. The challenge now lies in understanding, rating and communicating the underlying asset risk. Within these challenges lies the next opportunity. Let’s take the next step and make trading both safer and swifter.