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Lightening the RWA load in securitisations

Credit Agricole quants propose new method for achieving capital neutrality

The financial system is a complex machine that must be kept well-oiled to function properly. Occasionally, regulations designed to enhance stability inadvertently throw sand in the gears.

Securitisations are a prime example. Intended to facilitate efficient risk transfer, the financial instruments see banks shift bundles of assets from their balance sheets into new securities, which can be sold to investors in tranches.

Yet securitisation can make assets appear riskier. That’s because risk weights assigned to these tranches often diverge from those assigned to the actual assets. Consequently, the capital banks must hold against the tranches of a securitisation may exceed capital requirements on the underlying pool.

This imbalance, known as capital non-neutrality, disincentivises securitisations and can slow the transfer of risk. The issue is well known among regulators. The European Banking Authority (EBA) acknowledged in a 2022 paper that “capital non-neutrality […] has been too high”.

Two quants from the securitisation unit at Credit Agricole CIB in Paris have devised a new approach to the issue, which they hope will spark industry debate and encourage regulators to take action.

We are not asking to apply precisely this proposed formula, but it provides a direction, and it shows that the main risk factor is the type and quality of the underlying portfolio
Frédéric Zana

Frédéric Zana, a senior quant, and Eric Rossignol, who heads the securitisation quant team, developed a closed-form formula for determining more efficient risk weights and allocating capital to the tranches of a securitisation in a way that ensures neutrality and eliminates the arbitrage.

The research was inspired by the EBA’s 2022 paper ‘Joint Committee Advice on the Review of the Securitisation Prudential Framework’. While the regulator made a series of recommendations, the RWA conundrum remained a blind spot.

“With regards to the risk-weighted assets on securitisation, it was a bit stuck,” Zana says.

In part, this reflects the regulator’s conflicting objectives of maintaining a cautious approach to RWAs while also encouraging risk transfer activities. 

The new approach was borne out of previous research Zana conducted on asset and default correlation.

Default correlations can be estimated either from equity correlations or historical default data.  The pair opted to simulate a default dataset, which they use to estimate the correlation and the default probability associated with each tranche of the securitisation, and then the relevant RWA, using Basel formulas.

In contrast with most quant projects, the approach is not derived from first principles, and the process did not begin with a formula. Rather, it is reverse engineered from the data, with the final version being the result of an iterative process to meet the best fitting specification.

“The solution we discussed […] was to identify the economic curve, which we call inverted S shape curve, which describes this relationship,” explains Zana, referring to the risk weights and the capital derived from them.

“We looked at different types of portfolios, and we saw that formulas are different depending on levels of risk and on correlation within them. It’s much more pool dependent than what stands in the regulation.”

This dependency is best illustrated by the real estate market. In some countries, risk weights on real estate assets are low because the risk itself is deemed low. This, according to Zana, reduces the effectiveness of a securitisation, meaning many real estate loans remain on banks’ balance sheets. The authors claim this pattern is particularly pronounced in the French market.

He argues more efficient risk weight formulas that ensure capital neutrality would enhance efficiency and liquidity in capital markets, by enabling any type of asset to be securitised and transferred from banks’ balance sheets.

“This approach is part of a discussion we are having with regulators. It’s to quantify the cautiousness implied by the current risk weights and to show how we can reduce this cautiousness,” says Zana.

“We are not asking to apply precisely this proposed formula, but it provides a direction, and it shows that the main risk factor is the type and quality of the underlying portfolio. That factor seems to be underweighted in the current approach.”

He says the proposal is already drawing regulatory interest.

“We found that regulators are very receptive of the proposal, although the discussion at this stage was held only with the European Commission. We’d like to broaden it to central banks and to the Basel Committee.”

The adoption of this method might not be imminent, but Zana and Rossignol hope they have stirred the debate towards an improved outcome.

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