Less fraud and happier customers: A perfect match

Stop romance scams, account takeover attempts, and more with Sift Science

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Trusted by leaders in the online dating space

Build a trusted community where people will want to meet

The number of people using online dating sites has increased threefold since 2013, creating a large field for fraudsters to exploit. In 2016, $230 million was lost to romance scams in America alone.

The Sift Science Digital Trust Platform looks at user profiles, messages, and behavior to detect threats in real time, so you can automate fraud prevention, reduce operational costs, and increase engagement.

Key benefits

Stop scams and spam

One bad experience can drive a user away forever. Ensure that users only get messages from real people – not catfishers.

Prevent account takeover

Unauthorized access to good users’ accounts leads to a poorer community experience and potential customer churn.

Reduce chargebacks

Fraudsters with stolen credit cards hurt your bottom line with bad purchases.

Streamline operations

Our solution scales with your business, and our tools make fraud management easier, even as fraudsters change tactics.

A single-platform approach to protecting your users and growing your business

Founded in 2011, Sift Science boasts a large network of high quality data and sophisticated machine learning technology, contributing to unparalleled score accuracy.

Live machine learning

We instantly adapt risk assessments to emerging trends as soon as they occur.

Global network

We apply learnings from the fraud we see across 12,000+ websites and digital channels.

Custom modeling

We build you a custom model that adapts to your unique fraud challenges.

Contact a dating community fraud expert

It’s not you. It’s them. And we know when they’re fraudsters.

Our machine learning models adapt to the unique signals of your business and update as we learn new things about each user over time.

One scalable solution for every vector of abuse

Learn more about the Digital Trust Platform