Natural language, real models.
PRISM is not a reporting tool or a pre-built analytics layer. It runs your actual ALM models, driven by a prompt. The rigour stays; the friction disappears.
Introducing PRISM — the AI-native analytics platform for Asset & Liability Management that democratises ALM insight across your organisation.
PRISM
AI-native ALM analytics
I created a dashboard showing the NMD portfolio's duration across the three month-ends (31 Jan, 28 Feb and 31 Mar 2026).
Summary
Download PDFThe NMD portfolio's duration declines modestly over Q1 2026 — from 2.62 to 2.61 years — as the discount curve and client-rate dynamics evolve.
Duration · 31 Jan
2.6196 yrs
Duration · 31 Mar
2.6098 yrs
-0.0098
NPV
€ 98.7 M
A real PRISM session — a natural-language prompt on the left, a fully modelled, interactive dashboard on the right.
The problem
Your Asset & Liability Management models are sophisticated, carefully validated, and perform well in reporting and hedging cycles. Yet using your model landscape to turn ad-hoc questions into actionable insights takes far too long. Vendor ALM systems miss flexibility and modelling and analytics teams are streched beyond capacity building one-off tooling, sourcing data, running analyses, and building dashboards just to answer a single request.
By the time insight reaches the people who need it, the moment has passed.
There is a better way.
What PRISM does
PRISM is an agentic AI solution purpose-built for Banking ALM analytics. It lets anyone in your organisation ask a question in plain language, and get a fully modelled answer — a clear, written interpretation of the results alongside an interactive dashboard — without writing a single line of code or submitting a single request to your modelling or analytics team.
A risk officer asks
A retail business-line head types
PRISM takes it from there.
Why PRISM is different
PRISM is not a reporting tool or a pre-built analytics layer. It runs your actual ALM models, driven by a prompt. The rigour stays; the friction disappears.
PRISM connects directly to your existing data infrastructure — databases, data warehouses, Excel files, or any other source — and figures out autonomously how to shape the data for each model. No bespoke connectors. No integration projects. No maintenance burden.
CFOs, treasurers, risk officers, and business line heads can run their own analyses on demand. PRISM democratises ALM insight across the organisation, enabling faster decisions, better steering, and more effective risk management.
When stakeholders can self-serve through PRISM, your analysts, quants and model developers get their time back — to build better models, validate assumptions, and do the high-value work only they can do.
Built for banking's reality
Model integrity preserved
PRISM always runs analyses through an institution's own validated and controlled model landscape.
Auditability built in
Every PRISM analysis is logged, traceable, and explainable.
Flexible configuration
PRISM works with what you already have, not what a vendor wishes you had.
Scalable across the organisation
From a single modelling team or treasury desk to enterprise-wide deployment.
The result
PRISM is what it looks like when AI is built for Asset & Liability Management — not bolted onto it.
Ready to bring PRISM to your model landscape?
Let's talk.
Our beliefs
PRISM was built on a clear set of beliefs about what good ALM practice looks like — and what stands in its way.
Most ALM analyses boil down to a standardised set of questions that recur over time. Rate environments shift. Competitive dynamics change. Balance sheet structures evolve. But the analyses themselves remain largely the same — it is the context that changes, not the question.
Yet what we consistently see is banks reinventing the wheel. Analyses done in the past are redone from scratch. Tooling that already exists gets rebuilt. Valuable time and resources are consumed not on insight, but on the machinery required to produce it.
PRISM breaks this cycle. Your existing model landscape is the foundation. The AI agents inside PRISM use it to do the work for you — no custom tooling required, no time lost rebuilding what already exists.
The people who benefit most from ALM analyses are often the least equipped to run them. Non-technical stakeholders — treasurers, risk officers, senior management — carry real decision-making weight but depend entirely on modelling and analytics teams to answer their questions. This creates a structural imbalance: stakeholders wait, and modelling teams are stretched beyond capacity fielding ad hoc requests.
PRISM was built to close that gap. Anyone with ALM knowledge can run their own analysis — no technical ability required. Insight reaches the people who need it without passing through a queue.
Modern banks are not short of data. The challenge is no longer finding it — it is getting it to the places where it can add most value. Today, that typically means building and maintaining complex data pipelines, developing dataset-specific knowledge, and possessing the right technical competencies just to make data usable. All before any analysis has even begun.
PRISM removes that burden entirely. Data retrieval and the preparation of model-ready inputs are handled by the agent. Your data becomes an asset you can actually use — without an engineering project standing between you and the answers you need.
PRISM places an AI layer over your institution's own models. It does not make modelling decisions, and it is not designed to. Model development teams retain full ownership of methodologies and model versions. Model validation functions retain their ability to assess and attest to model validity. Senior management retains the ability to trust what they see.
The stakes in ALM are too high for any other approach. PRISM is powerful precisely because it operates within boundaries that your institution sets and controls.