Mona Lisa Re Ltd. (Series 2020-1) – Full details:
Bermuda-based reinsurance firm Renaissance Re has returned to the catastrophe bond market to source retrocession for the first time since 2013, bringing a $250 million or larger Mona Lisa Re Ltd. 2020-1 multi-peril cat bond to market.
RenRe’s Bermuda domiciled special purpose insurer (SPI) Mona Lisa Re Ltd. is aiming to issue two tranches of Series 2020-1 cat bond notes, that will be sold to investors and the proceeds used to collateralise underlying retro reinsurance agreements between the issuer and the beneficiaries of coverage, we have learned.
The beneficiaries of the coverage, the ceding reinsurers, will be Renaissance Re itself and also its DaVinci Re Ltd. vehicle, a third-party capital backed equity-based joint-venture reinsurer operated by RenRe.
The retrocessional reinsurance coverage that this Mona Lisa Re 2020-1 cat bond will provide to RenRe and DaVinci Re will be for certain losses from the perils of U.S., Puerto Rico, U.S. Virgin Islands, D.C. named storms and earthquakes, and Canada earthquakes as well.
Coverage will be on an industry loss index trigger basis across a three-year term, with one tranche of notes set to provide annual aggregate reinsurance protection and the other per-occurrence protection to the beneficiaries. We’re told this cat bond will cover losses specifically from personal, commercial and auto lines of business underwritten by RenRe and DaVinci Re, using data reported by PCS for the industry index trigger.
The first, Series 2020-1 Class A tranche of notes, is targeted as a $125 million issuance will provide RenRe with annual aggregate protection and uses a franchise deductible, so qualifying loss events have to be above a certain size.
The $125 million of Mona Lisa Re 2020-1 Class A notes have an initial expected loss of 2.52% at the base case, while they are being offered to investors with price guidance in a range from 7.5% to 8.25%.
The second, Series 2020-1 Class B tranche of notes is also targeting $125 million of protection for RenRe and will provide the company with the per-occurrence protection.
The $125 million of Mona Lisa Re 2020-1 Class B notes have an initial expected loss of 3.46% at the base case and have been marketed to cat bond investors with coupon pricing guidance in a range from 8% to 8.75%.
We’re told that risk modelling analysis shows that a repeat of 2017’s hurricanes Harvey, Irma and Maria, would not trigger either the annual aggregate or the per-occurrence tranches of this cat bond, based on latest estimates, showing that this cat bond covers either much larger single events, or an aggregation of more losses across an annual period than that year presented.
RenaissanceRe has raised the target size for its new Mona Lisa Re Ltd. (Series 2020-1) catastrophe bond transaction by 80%, with the issuance now aiming to secure up to $450 million of retrocession for the company.
We understand that the Mona Lisa Re 2020-1 Class A tranche has a new target size of $200 million to $250 million, while the price guidance has been narrowed towards the lower-end of the range at 7.5% to 7.75%.
We understand that the Class B tranche is targeting an issuance size from $125 million up to $200 million, while the price guidance has also been narrowed slightly towards the lower-end at 8% to 8.5%.
RenaissanceRe has settled for a 60% upsizing of its latest catastrophe bond, with the Mona Lisa Re Ltd. (Series 2020-1) cat bond transaction now priced at $400 million in size.
The Mona Lisa Re 2020-1 Class A tranche of notes has now grown to $250 million, the upper-end of revised size targets, while the coupon price has now been fixed at 7.5%, so the bottom-end of launch guidance.
The Class B tranche eventually settled at $150 million, below the up-to $200 million revised target, while the coupon price guidance has been fixed at 8%, which is again the bottom-end of guidance.
We’re told that for RenRe the pricing has been important and that investors may have supported a larger Class B tranche at a higher coupon, but the sponsor opted to secure the best pricing execution it could.