Grow the book, not the desk.
Personalised advice is expensive, so it reaches only a select few. Most banks already have the models. What they lack is a way to put them in front of every customer and stand behind the result.
Analyzera closes that gap. The conversation is a language model. The decisions are not. Suitability and the audit trail are built into the process rather than added after.
End-to-end financial advice in minutes rather than hours. Work that previously took an adviser, a portfolio team and a compliance review.
Every recommendation comes out of a deterministic process, with suitability and the audit trail at the core rather than arriving afterwards. Jurisdiction-specific rule packs, adaptable to each market's own compliance regime.
Advice on the customer's whole balance sheet, including their held-away accounts, inside one cross-asset risk model. The portfolio is built around the risk they already carry, not the risk of the securities alone.
The advice VIP clients get. For everyone.
From client profile to suitable portfolios.
True personalization, in a fully deterministic and MiFID II compliant process.1
1 Built against the other EU and national rules that apply to investment advice and to the systems delivering it, including the MiFID II Delegated Regulation (EU) 2017/565, ESMA's suitability guidelines (ESMA35-43-3172), the sustainability-preferences amendment (EU) 2021/1253, PRIIPs (EU) No 1286/2014, SFDR (EU) 2019/2088, the EU AI Act (EU) 2024/1689, GDPR and DORA (EU) 2022/2554, together with the national rules of each market the bank operates in.
Illustrative. Elsa is a demo customer.
A standard chatbot
is a poor advisor.
Yet more and more use it. But an LLM alone is not built for regulated finance, and has several shortcomings.
Regulated process.
Built for audit.
Every recommendation follows the same path. What was known, what was checked, and what was decided. All of it reproducible, all of it on the record.
Everything the decision rests on.
The customer's risk, capacity, horizon, knowledge and sustainability preferences.
Same inputs, same verdict.
Versioned per regulatory regime. Any recommendation can be replayed against the exact rules that produced it.
A warning is a gate and a receipt.
Every warning names the rule that fired, holds the confirm button until the customer acknowledges it, and records that acknowledgement on the compliance file.
Written, filed, defensible.
Every recommendation produces a written report. Every check that ran is listed, and each input is labelled.
Never overwritten.
When a recommendation changes, the new one is added. The old one stays intact, enforced by the database itself.
A digital structuring desk that answers in seconds.
Our quantitative backend does the work an investment bank's structuring desk does, and answers in seconds rather than hours. Being able to do complex work that fast is what makes real personalisation possible at all.
A view, a goal or an intention. What the portfolio is meant to do.
The rules that turn the idea into weights.
Backtests, risk decomposition and stress tests against the mandate.
Fully deterministic and replicable.
Orders, rebalancing, and the trail that shows what was done and why.
A view, a goal or an intention. What the portfolio is meant to do.
The rules that turn the idea into weights.
Backtests, risk decomposition and stress tests against the mandate.
Fully deterministic and replicable.
Orders, rebalancing, and the trail that shows what was done and why.
The power to build any long term solution.
Ship any single stock strategy across regions, size segments, fundamentals and themes, or build holistic solutions across asset classes to fit client profiles, with 20+ years of historic evidence in seconds. Drive client trades systematically, or notify before a rebalance.
Illustrative. Both routes run the same documented construction process, so the same inputs rebuild the same portfolio.
Unified risk enables opportunities.
Analyzera's internal cross-asset factor risk models make it possible to create, test and evaluate any idea, taking into account every major asset class, including private assets and properties. A proper risk backbone is what enables flexibility and possibilities.
Illustrative variance contributions. Cross-asset by construction: one covariance structure, not one model per asset class.
Personalisation: primarily an efficiency problem.
Lack of personalisation is not a technology issue — the technology already exists. The issue is that it is not unified, and out of reach for most. Serving five model portfolios is easy; building anything on the fly is a different challenge altogether.
Five model portfolios need none of this. Building anything on the fly, per customer, is what makes it the whole problem.
Your brand, your rules, your shelf.
Integrates with your tech stack, your existing investment solutions and your data. Deployed with any major LLM and cloud provider.
Whitelabel or API
Regional adherence
Fits your processes
Analyzera is a technology provider. We are not a financial advisory firm and we do not provide financial advice.
Our software is licensed to regulated financial institutions. Any advice a customer receives is given by that institution, under its own regulatory permissions and its own responsibility. Nothing on this page, in any demonstration, or in any figure shown is an investment recommendation, an offer, or a solicitation to buy or sell any financial instrument. Portfolios, holdings, returns and customers shown in demonstrations are illustrative. They are not client data and are not a forecast of any result. Past performance is not a reliable indicator of future results. The value of investments can fall as well as rise, and capital is at risk.