Synthetic Risk Transfers (SRTs) let banks shed credit risk to non-bank financial intermediaries while keeping the underlying loans on their balance sheets. A structural vulnerability arises when the same banks extend credit lines to the funds that buy their SRT protection, creating a circular leverage loop in which the capital relief is partly self-funded. We formalize this loop as a single parameter, λ, the fraction of total SRT protection weight financed by the originating bank or its affiliates. Using a directed network model of bank-NBFI SRT relationships, we simulate contagion cascades across 1, 000 random network realizations for each λ value. The simulation shows a two-stage phase transition: cascade size first departs meaningfully from its baseline at λₒnset ≈ 0. 85–0. 95, then jumps sharply at λ* ≈ 0. 95 where Dragon King events emerge from the loop mechanism itself. The transition location is invariant across network density, investor concentration, shock size, and tranche thickness; what density controls is cascade magnitude at high λ, which scales from 0. 18 to 0. 61 across the tested range. Because λ is not disclosed, we cannot place the real market on this phase diagram. Instead, we propose six publicly observable proxy metrics, computable without proprietary data, ranked by sensitivity-weighted ordinal position relative to λ*. As of Q1 2026, four of six proxy metrics show stress signals; the one metric most practitioners watch, SOFR-OIS, does not. One number, λ, would let supervisors place banks on the phase diagram. It is already known to each originating bank and is not reported. This preprint includes the paper, full simulation code (MIT license), five figures, and a cockpit CSV with current Q1 2026 signal readings.
Daniyel Yaacov Bilar (Fri,) studied this question.