Cut the whole network at once.

Fraud runs on accounts, lines and devices that look unrelated. Datasight links them across the systems a bank or an operator already runs, so the team stops a ring as a whole instead of chasing it alert by alert. Every case then reaches the supervisor complete.

A mule ring, end to end

One mule ring at a bank, from six separate alerts to a single report.

01 Ocean Hub Joins the customer files

One customer, however each system writes the name.

Onboarding writes HOFER LUKAS, the card system L HOFER, the device log only a hardware code. Ocean Hub brings them together under one customer, so six alerts that looked unrelated now point to the same person.

Ocean HubCustomer gateBatch 0388

From Ocean HubLukas HoferDevice ••9B4EInès Moreau

02 Stella Draws the ring

Stella lays out what Lukas Hofer is tied to: device 9B4E, the phone line that leads to Inès Moreau, and Consulting Co., whose account the money passes through. Analysts stop reading alerts one by one and see the ring they belong to.

StellaLukas Hofer

From StellaConsulting Co.Acct ••8014

03 Anna AI Answers the analyst

Who really owns the company?

Which accounts came from this device, and who stands behind Consulting Co.? Anna AI answers from the bank's records and the company registry, naming the documents behind each reply. The beneficial owner goes straight into the file.

Anna AIWorkspaceLocal model

From Anna AIBeneficial ownerAcct ••2261

04 Nora Builds the report

One report instead of six alerts.

Nora keeps the ring as a single case: the six alerts, the ownership answer and the statements, each sealed as it arrives. The compliance officer signs off, and the suspicious transaction report goes to Tracfin with its evidence.

NoraCase 0027Open

On film

One customer under three names, and the network around him.

Banking · 50 s · English subtitles Know your customer. A bank customer known under three names, the fraud network around him, and a file ready for the regulator.

Banking

Fewer false positives. More rings found.

Know your customer

The owners behind a company account

EU anti-money laundering rules, now gathered in a single regulation, the AMLR, require banks to know who owns the companies they serve. Company registries are fused with your customer files to establish beneficial owners and their ties.

Anti-money laundering

Money followed, step by step

Funds are traced from account to account, with the people and companies behind each one, and each step is kept on the record.

Telecommunications

Every scam needs a line. Find every line behind it.

Scams

Every line of a scam, suspended together

Numbers calling many strangers and lines opened with the same document are linked. The team suspends the operation behind them in one action, before the next wave of calls.

Revenue

Bypass fraud

SIM boxes route international calls through local lines and take the interconnect revenue. Their call patterns, set against what each line was sold for, give them away.

Subscription

Identity checks at the counter

Each new subscription is checked against your existing customer records. The same document or payment card behind a series of lines is flagged before activation.

Requests

Answers for the authorities

Lawful requests are answered faster, because subscriber, call and device records are already linked.

Signals

Signals a fraud team can act on

A signal names the pattern that raised it and the lines involved, so the team can act while a line is still in use.

Deployment

Customer records stay with you. So does every case built on them.

Datasight is installed on your own servers, next to the systems it connects, from core banking to call records and billing. Anna AI runs on your hardware. The platform needs no outside cloud to run, which keeps it simple to account for under DORA and NIS2. Each access is written into an audit chain, and every exported case is sealed.

Show us the ring you cannot see yet.

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