One live network model of your supervised population — firm-level, market and contagion risk in one place — so the financial-stability read draws on a current model rather than a periodic cross-directorate data-call programme.
Firm-level analytics arrive on the return, stress tests run as periodic programmes, network tools give static snapshots — and the thing that matters most, how a shock transmits across the population, falls between them. Abgalis carries the supervised population as one continuously updated network, so concentrations, common exposures and contagion paths are visible live from firm-level signals rather than reconstructed each data call.
It is analytics, not authority: supervisory judgement, decisions and the use of any output remain entirely with the authority. Abgalis is the intelligence layer beneath the supervisory process.
Concentrations, common exposures and contagion paths regenerated live from firm-level signals — a current systemic view rather than one rebuilt each data call.
System-wide stress and scenario analysis assembled from the same live model — consistent, versioned and reproducible across the population, not a fresh programme each cycle.
Live mapping of how a shock transmits across firms and domains — the same cross-domain transmission the Cascading Risk Index measures, at population scale.
Because the population is modelled as one live network, you can play a shock through it — a market move, a large-firm distress, a common-exposure event — and watch it transmit across firms and domains to a system-wide read, with emerging threats (climate, cyber, geopolitical, liquidity) surfaced live.
See the war-gaming approach on the war-gaming view, how the integrated proposition compares with SupTech and systemic tools on the comparison for regulators, and the transmission axis in the Cascading Risk Index.
Abgalis carries your supervised population as one continuously updated network model — firm-level, market and contagion risk in one place — so concentrations, common exposures and contagion paths are visible live and the financial-stability read stays current between returns. It is a data and analytics layer; supervisory judgement and decisions remain entirely with the authority.
Firm-level signals are carried in one network model of the population, so the systemic picture — concentrations, common exposures, contagion paths — is regenerated live rather than reconstructed each periodic data call, with stress and scenario runs consistent and reproducible.
The population is represented as a live network and a shock is transmitted across firms and domains — mapping how distress in one part propagates to others. This is the same cross-domain transmission the Cascading Risk Index measures, applied at population scale.
No. Abgalis is an intelligence and integration layer above the systems you already run — SupTech analytics, stress-testing platforms, network tools, data-collection systems. It turns firm-level signals into a live systemic view; it does not replace them or supervisory judgement.
Abgalis is designed to deploy inside your own infrastructure so the most sensitive supervisory data stays under your control, with data-handling and resilience treated as first-order — the very third-party concentration you require firms to manage. Deployment and data arrangements are agreed and confirmed contractually.
No. Abgalis is a data and analytics provider. It supports analysis and situational awareness; it does not make supervisory decisions, exercise regulatory judgement or carry any statutory function. All of that remains with the authority.
Yes. Emerging threats — climate, cyber, geopolitical, liquidity — are surfaced live across the population, so horizon-scanning is a continuous read rather than a periodic data-collection exercise.
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Abgalis Limited is a risk data and analytics provider. It supports supervisory analysis and situational awareness; it does not exercise any supervisory, regulatory or statutory function, and all supervisory judgement and decisions remain with the authority. References to systemic-risk and financial-stability frameworks describe the supervisory context.
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