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FINANCIAL SERVICES INTELLIGENCE

Sovereign AI for
Financial Services

Fraud, risk, and compliance teams sit on more data than ever and still decide too slowly: the signals are scattered across core systems, and the black-box cloud AI that promises to help is exactly what DORA and your regulator will not accept. That is the problem we solve: frontier predictive analytics and autonomous agents for fraud detection, risk management, and personalised banking, on one ontology of customers, counterparties, and exposure that keeps every AI decision explainable — with DORA compliance and data sovereignty on our European-native platform.

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Built for DORA

Meet Digital Operational Resilience Act requirements with resilient, on-premise AI infrastructure.

Fraud Prevention

Real-time transaction monitoring and anomaly detection with zero data leakage.

Legacy Modernization

Wrap legacy core banking systems with intelligent API layers and AI agents.

Financial Applications

Secure Financial Innovation

Sovereign AI solutions for regulated financial services.

Real-Time Fraud Detection

Security

Challenge

Traditional rule-based systems generate too many false positives and fail to catch sophisticated new fraud patterns.

Solution

Deploy autonomous agents that learn transaction patterns in real-time, flagging anomalies with high precision without moving data off-premise.

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Reduction in fraud losses by 40% and false positives by 60%, improving customer trust.

Algorithmic Risk Management

Investment

Challenge

Market volatility requires instant analysis of massive datasets, but latency and data privacy concerns limit cloud usage.

Solution

Sovereign AI models analyse market data, news sentiment, and internal positions locally to adjust risk exposure in milliseconds.

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Faster reaction to market events and improved risk-adjusted returns while keeping strategies proprietary.

Automated KYC/AML

Compliance

Challenge

Manual review of Know Your Customer (KYC) and Anti-Money Laundering (AML) alerts is slow, expensive, and error-prone.

Solution

AI agents automatically gather and verify customer data from multiple sources, summarising findings for compliance officers.

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Onboarding time reduced from days to minutes, with a fully auditable decision trail.

Regulatory Reporting

Operations

Challenge

Compiling reports for regulators involves gathering data from siloed legacy systems, a tedious and manual process.

Solution

Data space connectors unify disparate data sources, and AI agents generate compliant reports automatically.

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100% on-time reporting accuracy and significant reduction in operational overhead.

Market Intelligence

Real-time Transaction Analysis

In high-frequency trading and payment processing, every millisecond counts. Our platform enables in-memory data processing at the edge, combining market feeds, historical data, and user behaviour into a single, live operational picture of positions and flows, grounded in your financial ontology. Decision intelligence then turns a flagged signal directly into a routed, approved action instead of another dashboard alert.

  • Data Fusion: Correlate internal ledgers with external market data in real-time.
  • Privacy Preserving: Analyse sensitive customer data without exposing PII.
  • Decision Intelligence: Route a flagged signal straight into an approved action, with the full reasoning trail preserved.

SUGGESTED IMAGE: Trading Floor or Data Visualisation Dashboard

Banking Operations

Modernise the core of your institution. From back-office automation to customer-facing applications, the AI OS streamlines operations — onboarding, reconciliation, reporting — without compromising security.

Secure Back-Office

Automate reconciliation and reporting workflows in secure environments.

Legacy Modernization

Wrap legacy mainframes with intelligent API layers and AI agents.

Open Banking

Securely share data with third parties while maintaining control and consent.
Regulatory Compliance

Sovereignty & Compliance

We support the mission of financial stability. Our platform is architected to align with GDPR, DORA, and MiFID II, ensuring that your data remains under your control and compliant with the strictest regulations. Persistent, entity-grounded agent memory keeps multi-week AML and fraud investigations fully traceable for regulators, even across changes in analyst or agent.

Built for GDPR

Built-in privacy controls and data residency.

Audit Trails

Complete immutability for all AI decisions.
100% European Sovereignty

Your Data, Your AI, Your Control

Deploy the Scrydon platform where it makes sense for you — from air-gapped environments to public cloud — with sovereignty, compliance, and auditability built in.

Air Gapped

  • No external network paths
  • Offline signed updates
  • Strict audit trails

On Premise

  • Runs in your datacenter
  • Identity-integrated & compliant
  • Full operational control

European Cloud

  • EU data residency
  • GDPR-first architecture
  • Managed sovereign services

Confidential Compute

  • TEE-protected workloads
  • Encrypted memory & attestations
  • Secure ML inference

Public Cloud

  • Multi-cloud compatible
  • Policy-driven data controls
  • Hybrid & burst-ready

No data leaves your jurisdiction. No black-box AI. No compromises on control.

This is sovereignty by design.

The platform behind this

What these outcomes actually run on

Everything above is delivered by one platform, with the model governance and audit trail your regulator will ask for. For the architects and engineers evaluating it, these are the pieces that matter.

See the full architectureRead the documentation
FAQ

Frequently asked questions

What is sovereign AI for financial services and why does it matter?+
Sovereign AI means your models, data and the platform that runs them stay under your control and within your chosen jurisdiction, rather than depending on an external operator's cloud. For banks and insurers this matters because customer data, transaction records and proprietary risk models are among your most sensitive and regulated assets. A sovereign, European-native platform gives you full control over data residency, processing location and the model supply chain, so you can innovate with AI without surrendering custody of regulated data.
How does the platform support DORA and operational resilience?+
The platform is designed to align with the Digital Operational Resilience Act and broader operational-resilience expectations, with capabilities such as detailed audit trails, access logging, policy enforcement and resilient, self-hosted deployment that reduces concentration risk on a single external provider. It supports the documentation, traceability and ICT risk-management practices DORA emphasises. We speak to alignment and the controls that help you meet your obligations, not to a formal certification on your behalf.
Can we run real-time fraud, transaction and risk analytics on the platform?+
Yes. The platform is built for high-throughput, low-latency analytics over streaming and historical financial data, so you can score transactions for fraud, monitor exposures and run risk analytics in real time. Agentic AI can orchestrate detection, triage and operational responses across these processes. Because it runs on your sovereign data platform, sensitive transaction data never has to leave your control to be analysed.
How do you handle model governance, explainability and audit for regulated AI?+
Every model, dataset and agent action can be versioned, attributed and logged, giving you end-to-end audit trails as part of our AI governance. An ontology provides a consistent semantic layer so decisions can be traced back to the data and business concepts behind them, supporting explainability and model risk management. This lets risk, compliance and internal audit teams review how AI reached a given outcome and demonstrate governance to supervisors.
We piloted chatbots and copilots — how do we move to organisation-wide, governed AI across the bank?+
Moving from isolated pilots to organisational AI is about putting governed infrastructure underneath the experiments: shared model serving, a common data and ontology layer, federated identity and consistent policy controls. The platform lets you take the copilots and assistants you have proven and run them at sovereign scale across business lines, with the governance, audit and resilience a regulated bank requires. That bridges the gap from promising proof-of-concept to production AI used safely across the organisation.
Can sensitive financial data stay protected from the cloud operator, or run fully on-premise?+
Yes. The platform supports deployment anywhere from fully air-gapped on-premise environments to your own cloud, so data never has to leave infrastructure you control. Where you do use cloud, confidential computing keeps data encrypted in use so that even the cloud operator cannot access it. This means you can adopt AI on the most sensitive financial data while keeping it shielded from third-party operators.
How do you manage identity, attribution and policy for AI agents acting on financial systems?+
AI agents are treated as first-class identities under a zero-trust, federated identity model, so every agent authenticates, carries scoped permissions and acts only within policy. Each action an agent takes on a financial system is attributed and logged, giving you a clear record of who or what did what. This lets you grant autonomy to agents for fraud, operations and risk workflows while retaining strict, auditable control.
How do you avoid vendor lock-in and stay model-agnostic?+
The platform is model-agnostic and supports open-weight models served on your own infrastructure with engines such as vLLM, alongside commercial models where appropriate. You are free to choose, swap and combine models without re-architecting, and to keep open-weight models entirely on-premise. This avoids lock-in to any single provider and ensures your AI strategy, data and models remain portable and under your control.
Can the platform turn an insight directly into an approved action, not just a dashboard?+
Yes. Decision intelligence connects the ontology to the next operational step, so a flagged risk or credit signal can trigger a recommended action — a limit change, a hedge, an alert — routed through your existing approval workflow. The full reasoning trail behind the recommendation is preserved, so risk and compliance teams can see exactly why an action was proposed.
Do investigative agents retain memory across a multi-week AML or fraud case?+
Yes. An entity-grounded memory layer keeps the evidence, ruled-out hypotheses and related cases tied to an investigation, so any analyst or agent resuming the case starts with full context instead of re-reading the file from scratch. That reasoning history stays available and auditable for regulators throughout the case lifecycle.

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