01 — Platform

ARi: Credit deterioration is measurable in time, before it is measurable in price.

The institutional credit risk intelligence platform, built around the velocity of credit deterioration rather than just its level.

ARi is built on one single analytical proposition.

Credit deterioration leaves measurable signals in the data before it crystallises in default, ratings actions, or price. The institution able to read those signals on the temporal dimension and on the speed of the deterioration, not just its level holds real advantage in every credit decision the institution makes.

The AI platform that delivers competitive advantage through seven production-grade intelligence pillars, designed to enter a regulated institution's existing model validation and governance processes.

02 — The Seven Pillars

The synthesis layer.

NPL Analysis and Warning

Per-exposure migration probability shifts ahead of conventional NPL classification triggers, surfaced through channel-based stress velocity. The credit officer sees which exposures are most likely to migrate to non-performing in the next 30 to 90 days, with the underlying signals fully traceable to source.

Credit Default Analysis and Warning

Forward default likelihood at issuer level, integrating balance-sheet vulnerability with channel transmission. Per-issuer ranking of default risk shift across 30, 90, and 180 day horizons, with confidence intervals and explicit channel attribution.

GeoPol

The GeoPol Index computes how a geopolitical or macro shock transmits into your credit book loan by loan, through the specific channel, before it surfaces in the mark. Not "how much do we hold in that country," but "which of our exposures does this event actually break, and how." Independent, continuous, and defensible to the exposure.

Significant Risk Transfer (SRT) Intelligence

For banks using significant risk transfer to manage capital, the hardest question isn't whether to do a deal, it's whether the risk you're transferring and the risk you're keeping are what you think they are.

ARi brings independent, loan-level intelligence to the SRT process: surveillance of the underlying reference pool, visibility into how the retained and transferred tranches actually behave under stress, and the traceable, defensible analytics that a risk committee and a regulator both expect. It applies the same core principle that runs through everything we do — seeing what an exposure is genuinely doing, not what it's reported to do — to one of the most capital-critical decisions a bank makes.

Dynamic Interest Rate Warning

Per-exposure refinancing stress projection under shifting rate paths. Identifies which exposures in the book face the largest debt-service capacity shifts as the rate environment moves, and which approach refinancing windows where the shift will crystallise first.

Anomaly Detection

Correlation breaks and behavioural shifts that surface emerging risk before threshold-based systems detect it. Particularly valuable in identifying where existing institutional credit models may be operating outside their validated parameter range.

Conflict Loan Analysis

Direct exposure mapping to geopolitical and conflict events, with quantified impact and recommended action. Built specifically for the institutional credit function whose book carries direct or indirect sensitivity to geopolitical and conflict-driven disruption.

03 — How it fits

Built to be deployed.

ARi is designed to enter the institutional environment as it exists, not to replace it. The platform integrates with existing model governance frameworks. Outputs are explainable down to source data and contributing channel attribution. Audit trails are complete. Per-client data is isolated, with no cross-client model training.

The platform is built for the regulated institution. Model documentation aligned to PRA SS1/23 and ECB TRIM expectations is built from the ground up rather than retrofitted. Security protocols are built; external audit is underway.

The trust posture is the starting point, not the response to objections. The conversation begins where the platform demonstration ends.