Finance & Insurance
Your supervisors want evidence kept current, your payments settle in seconds, and your core banking carries thirty years of history that cannot be replaced in one go. We industrialise compliance evidence, real-time detection and domain-by-domain modernisation, alongside banks, insurers and fintechs.
Prove, detect, modernise without disruption.
Three subjects come up in every conversation with a banking or insurance executive. They drive everything else: what has to be demonstrated, what is settled in milliseconds, and what can no longer be replaced in one go.
Making resilience demonstrable
Third-party ICT register, incident log, continuity testing: DORA expects artefacts kept current, not reconstructed ahead of an inspection. We produce them from your systems rather than alongside them.
Deciding in milliseconds on payments
Your payments settle inside a window measured in seconds, payee verification included. Fraud scoring has to fit inside it, and drive false positives down rather than up.
Modernising core banking piece by piece
A single-shot migration does not clear a risk committee. We extract the business rules from the legacy estate, restate them as testable specifications, and move one domain at a time with no outage window.
Two stakeholders, two expectations
A fraud capability is not bought in the same place as a compliance plan. Here is what each one expects from us, and what they get first.

Payments and financial crime
A decision due inside the payment window, fraud that changes method faster than the rules do, and false positives that cost as much as the fraud they prevent.
Scoring that answers inside your decision window, with the false positive rate measured before and after, and a fallback to business rules when a model degrades.

Retail network and client relationships
Advisers who spend more time looking for information than advising, and answer quality that depends on who picks up the phone.
A copilot grounded in your procedures and product catalogue, citing its source on every answer and leaving the decision with the adviser.
Solutions
DORA operational resilience
(01)Artefacts reconstructed ahead of every inspection, and a subcontracting chain discovered while filling in the register.
Third-party ICT register fed from your systems, incident log and continuity tests actually replayed, so the evidence exists before anyone asks for it.
Real-time fraud detection
(02)A decision due inside the payment window, and false positives that cost as much as the fraud they prevent.
Scoring trained on your transaction history, wired into your message bus, with a fallback to business rules the moment a model degrades.
Faster KYC and KYB
(03)Onboarding that takes days, document checks done by hand, and files lost along the way.
Automated document reading and sanctions screening, with human review reserved for the files the model flags as uncertain.
Explainable credit scoring
(04)Older models that are hard to justify, and a burden of proof shifting towards the institution.
Hybrid models combining learning and business rules, each variable's contribution kept per decision, and drift tracked over time.
Adviser copilot
(05)Advisers searching for information more than advising, and answer quality that varies with who picks up.
An assistant grounded in your procedures and product catalogue, citing its source on every answer and preparing the meeting rather than replacing it.
Sovereignty and third-party risk
(06)Concentration on a handful of providers, and an exit plan nobody has ever tried.
Deployment on qualified cloud or inside your perimeter, third-party dependency monitoring, and an exit strategy rehearsed rather than drafted.
Compliance & standards
DORA
Digital Operational Resilience Act
AI Act
Compliant high-risk models
ACPR
AI notice & governance
LCB-FT
Automated screening
BCBS 239
Risk data aggregation
SecNumCloud
Qualified hosting
GDPR
By design & by default
Stack & partners
Mistral AI
European sovereign LLM
Anthropic Claude
Frontier LLM (via gateway)
Vector DB
Qdrant / Weaviate / pgvector
Sovereign cloud
OVH / Outscale / Scaleway
AWS / Azure
With DORA landing zone
Snowflake / Databricks
Compliant data platform
Our ideas
Securing your APIs: best practices, from OAuth 2.1 to AI agents
OAuth 2.1 and PKCE, DPoP and mTLS tokens, rate limiting, DevSecOps governance and AI agents: the modern best practices to secure your APIs end to end.
Read the article
Let's talk about your finance roadmap
An hour to test your resilience, fraud and modernisation challenges against what we have already put into production elsewhere.
Frequently asked questions
By producing the evidence continuously rather than ahead of the inspection. DORA has applied since 17 January 2025 and expects three things kept current: the register of ICT providers, down to subcontractors and dependency chains, the incident log, and continuity tests genuinely replayed. We feed those artefacts from your systems, so the register reflects the real estate rather than a spreadsheet rebuilt from memory. Threat-led penetration testing, required of entities designated as significant, stays with independent external testers: we prepare the scope and the scenarios, we do not sign off the test.
The timing has moved. Regulation 2026/1744 of 24 July 2026 pushed the obligations for high-risk systems to 2 December 2027, and to 2 August 2028 for AI embedded in an already regulated product. Credit scoring for lending decisions clearly falls in that category ; fraud detection does not automatically, as it depends on what the decision produces for the person concerned. That extra time is for building the technical documentation, the robustness testing and the decision trail while the models run, not for picking the subject back up in 2027. Our founder Anis Zouaoui set out that method at La Matinale IT for Business in April 2026, alongside EY, Salesforce and Informatica.
See Adservio's AI Act expertiseThe right question is not model latency but the decision window of your payment chain, network hops and enrichment included. We start from that window and size the inference to sit inside it with headroom, plugged into the message bus you already run. Two things matter as much as speed: a fallback to business rules when a model becomes unavailable, so an inference outage never stops a payment, and the false positive rate measured before and after, because a fast model that blocks legitimate customers costs more than the fraud it prevents.
By sorting before hosting. We first classify data by what it exposes, then route accordingly: sensitive data stays inside your perimeter or on qualified cloud, the rest can go through an external model under a processing agreement with guaranteed data residency. An open-weights model operated on your own infrastructure already covers a large share of internal use cases. That breakdown matters for DORA too: it is what makes an exit strategy credible, and an exit only becomes real on the day it has been rehearsed.
Since 9 October 2025, every payment service provider in the euro area must check that the payee name matches the IBAN, on both standard and instant transfers, and without charging for it. The check does not block the payment: it returns three outcomes, exact match, close match or no match, and your journey decides what happens next. That is where the real work sits: wording the alert so it gets read, calibrating the close-match threshold, and handling false positives on trading names, which are the first volume to absorb.
Framing takes 2 to 6 weeks depending on scope and the level of compliance required. A first version tested by a group of advisers follows in 4 to 10 weeks, depending on the quality of your document base, which is almost always the deciding factor. Rolling out across the network, with governance and training, runs to 3 to 6 months. These ranges are the ones we apply everywhere, and each comes with what makes it vary: a duration announced without its variable only exists to be exceeded.





