SE Fraud prevention · SEON Technologies

Seon

Fraud-first platform using digital footprint and device intelligence, run inside your Zenoo onboarding flows.

At a glance

Overview

Seon overview

Seon is a fraud-first platform that combines identity signals with real-time fraud detection. It analyses digital footprints from email, phone, and IP data alongside device intelligence, and suits teams that prioritise fraud detection within their onboarding.

Company
SEON Technologies
Category
Fraud prevention
Strongest in
Digital footprint and device intelligence
Best fit
Fraud-focused onboarding teams

Where it is strongest

Key strengths

What Seon does well.

01

Digital footprint analysis

Enriches email, phone, and IP data to build a picture of a customer's digital footprint.

02

Device intelligence

Adds device fingerprinting and real-time fraud signals to onboarding decisions.

03

Fraud-first approach

Positions itself as a fraud-first platform with API features for fuzzy search and AML source profiles.

Who it suits

Best for

Where Seon fits, and what to plan for.

Honest notes on the trade-offs, each with a way to cover the gap inside a Zenoo flow.

Best for
  • Teams prioritising fraud detection and device intelligence within their onboarding flow
Considerations
  • Integration complexity. Some reports suggest integrating Seon's rules and scoring benefits from experienced developers. Zenoo builds and maintains the connector for you, which removes most of that lift.
  • On-demand individual AML. Some competitor comparisons note it is not primarily built for on-demand AML checks on individuals. Pairing Seon with a dedicated screening provider in the same Zenoo flow covers that need.
You

Open the customer's case

What your team sees

The Seon result, beside everything else.

The result sits with screening and review on one case, so nobody checks a second tool to see the whole customer.

LA
Lorraine AshcombeSample case · Personal
In review
SeonRecorded
Name and date of birthAgrees
PEP screeningSuggested
Name matches a list entry, but the date of birth differs. Suggest you clear as a false positive.Zenoo suggests, your team decides
You

Tomorrow, your case

Bring us a case that went wrong.

We will run it through Zenoo while you watch: the evidence, the decision, and the record your MLRO would want to defend.

30 minutes. Your data. No slides.