Fraud Management for Shipping and Delivery

Proactively prevent fake and compromised accounts from rerouting or shipping packages to unusual addresses. Ensure platform safety, protect good customers, and reduce fraud losses.

"DataVisor is cool for inverting this philosophy by putting the unsupervised machine learning approach in the forefront. Its clients benefit by being able to rapidly identify previously unseen fraud attacks and by not having to spend time and resources refreshing their fraud detection models regularly."

- Gartner Cool Vendors in Identity and Access Management and Fraud Detection

All-in-one, AI-powered Fraud & Risk Management for the Entire Customer Lifecycle

Never lose a package — or a customer — to fraud. Inspire trust by protecting the entire customer journey, and promote your services with confidence.

Shipping Fraud

Solutions for Every Fraud Type

Fake Accounts

Proactively block the mass registration of fake accounts to prevent downstream financial loss, brand damage, and customer churn.

Account Takeover

Protect good customers by uncovering large-scale ATO attacks in real time, and safeguard existing accounts against new and emerging fraud.

Bot Attacks

Protect your platform against the speed, scale, and complexity of modern, bot-powered fraud attacks.

Advanced Capabilities, Outstanding Performance

Data-Driven Insights

Holistically analyze structured and unstructured data from weblogs, shipment, user profiles and more to identify fast-changing shipping and delivering fraud.

Scalability

Track and detect activities and events initiated by bots and human farms to block fake accounts and large-scale fraudulent shipping requests.

Reduced Overhead

Automate decisioning, reduce manual review efforts, and free up your team from the burdens of intensive reviews.

"With DataVisor and unsupervised machine learning, we were able to identify and stop mass-scale fraud attacks before they had any effect on our users."

Steve Knopf

|Vice President of Trust and Safety

The Datavisor Platform

Data Integration

Ingest structured and unstructured data from omnichannel sources

Feature Engineering

Create advanced fraud features to enhance models and rules

Detection

Defeat fast-evolving fraud patterns with adaptive machine learning

Decision

Take actions in real time to mitigate fraud and delight good customers

Analytics

Review cases with a linkage view and uncover new fraud patterns