Can you build a DLT trading facility aligned to Switzerland's DLT Act?

Yes, we build ledger-based securities trading and custody infrastructure engineered around the technical expectations of Switzerland's DLT Act.

How much can AI fraud detection reduce our losses?

Results vary by baseline, but clients typically see 40-65% reduction in fraud losses alongside a meaningful drop in false positives.

Do you replace our existing rules engine or work alongside it?

We typically build a hybrid model — machine learning risk scoring layered on top of your existing rules — so you keep proven controls while adding adaptive detection.

Can this integrate with our existing payment platform?

Yes, our risk engines integrate via API or event stream into existing payment, banking, or fintech platforms.

How do you handle model explainability for compliance?

Every flagged decision includes contributing factors and a confidence score, logged for audit and regulator review.

AI & Automation · Switzerland

AI Fraud Detection & Intelligent Automation in Switzerland

Fraud losses and manual review queues both eat margin. Hurain Technologies builds AI-driven fraud detection, transaction monitoring, and workflow automation systems for payments and fintech platforms — real-time risk scoring, anomaly detection, and automated case management that reduce loss without adding friction for good customers. In Switzerland, that means building to the technical expectations of Europe: FINMA applies a principles-based token classification (payment, utility, asset) that shapes the technical and disclosure requirements a crypto project must meet.

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Switzerland Regulatory Landscape

What ai fraud detection & automation buyers in Switzerland need to know

FINMA applies a principles-based token classification (payment, utility, asset) that shapes the technical and disclosure requirements a crypto project must meet.
The Swiss DLT Act creates a dedicated legal category for ledger-based securities and DLT trading facilities, distinct from traditional securities infrastructure.
Crypto exchanges and custodians operating from Switzerland commonly engage FINMA's anti-money laundering supervision, often through a recognized self-regulatory organization (SRO).
We build the technical infrastructure these frameworks expect; token classification and FINMA engagement should be managed with Swiss-qualified legal counsel.

This information is provided for general orientation only and is not legal or licensing advice. Always confirm current requirements with qualified local counsel.

The Challenge

Problems we see teams struggling with

Fraud losses outpacing rule-based systems

Static rule engines can't keep up with evolving fraud patterns, leading to rising chargeback and loss rates.

Manual review bottlenecks

Investigation teams drown in false positives, slowing down legitimate customers and burning analyst hours.

No real-time visibility into risk

Batch-based monitoring catches fraud after the money has already moved.

Repetitive manual operations

Reconciliation, reporting, and case triage consume hours that could be automated.

Model drift going undetected

Fraud patterns evolve, and a model that isn't monitored and retrained regularly quietly loses accuracy until losses spike and someone finally investigates why.

No feedback loop from investigator decisions

When analyst outcomes aren't fed back into the model, the system never learns from the cases your own team has already correctly resolved.

Our Approach

How we deliver ai fraud detection & automation in Switzerland

Real-time transaction monitoring

Stream-processing risk engines that score transactions in milliseconds, not batch cycles.

Machine learning risk scoring

Supervised and unsupervised models trained on your transaction patterns, continuously retrained as fraud tactics evolve.

Anomaly & behavioral detection

Device fingerprinting, velocity checks, and behavioral biometrics layered on top of traditional rules.

Automated case management

Risk-ranked case queues that route only genuine high-risk cases to human analysts.

AML/KYC workflow automation

Automated sanctions screening, PEP checks, and suspicious activity report generation.

Operational workflow automation

RPA and orchestration for reconciliation, reporting, and other repetitive back-office processes.

Continuous model monitoring and retraining

Automated drift detection and a scheduled retraining pipeline that feeds investigator decisions back into the model, so it improves rather than silently decaying.

Technology

Tech stack we work with

ML & Data

PythonTensorFlow / PyTorchFeature storesApache Spark / Flink

Streaming

KafkaApache FlinkRedis Streams

Backend

GoJavaNode.jsPostgreSQL / ClickHouse

Automation

Workflow orchestration enginesRPA toolingCase management systems

FAQ

AI Fraud Detection & Automation in Switzerland — FAQ

Yes, we architect custody, issuance, and disclosure infrastructure suited to how your token is likely to be classified under FINMA's payment, utility, or asset token framework.