Fraud & Risk

Our team built the risk infrastructure that scaled Affirm and Airbnb. Now, you can build on the platform of our dreams.
Your fraud detection must be just as unique

Off-the-shelf models only see part of the picture, so good users get blocked, and bad users get through. The best fraud teams leverage their own business insights to spot and block fraud. Chalk enables your fraud fighters and data scientists to incorporate 3rd-party signals alongside product usage, messaging and support history, and even password reset data to make high quality decisions for your unique user base.

Fetch features just-in-time with Chalk

Chalk makes it easy to fetch fraud data only when it’s needed. Each model specifies exactly the data staleness that it can tolerate to give you fresh data cheaply. By employing a layered approach to fraud, you can reject bad candidates without fetching expensive data.

Test new features before going live

The best fraud programs stop bad users and welcome good ones. Striking the right balance requires constant iteration. With Chalk’s Preview Deployments, it’s easy to experiment with new signals before going to production. Preview Deployments show how proposed features would have impacted your previous decisions.

Take new signals live faster than ever before

Great fraud systems rely on dozens of data vendors and constant iteration to stay ahead of fraudsters. Providers like SentiLink, Socure, Emailage, Whitepages, and Early Warning Systems help you to form a complete picture of each user and transaction. However, when you have a new insight, integrating a new vendor or signal often requires significant time and engineering work. With Chalk, ship production-quality integrations on proof-of-concept timelines.

Share features across your organization

Traditionally, teams write one pipeline to fetch data for training and another competing pipeline to fetch that same data for production. To make matters worse, teams often re-write pipelines for each model that relies on that data. You wind up with dozens of implementations to fetch the same data, and they’re never all the same. Needless to say, discrepancies between pipeline code can lead to significant bugs. Chalk solves this with a unified feature catalog — a single pipeline to fetch data which is then accessible for all training and production models.

Alert on feature distribution changes

Chalk integrates with alerting systems like Pagerduty and Slack to keep your team informed about issues. Configure alerting thresholds for when data distributions don't match your expectations.

Get Started with Code Examples
Unlock the power of real-time data pipelines
Fraud & Risk
Withdrawal Model
Decide and enforce withdrawal limits with custom hold times.
Fraud & Risk
Account Takeover
Aggregate failed logins over a Kafka stream.
Fraud & Risk
Changes in Behavior
Detect changes in user behavior over time.
Fraud & Risk
Identity Verification
Make use of vendor APIs to verify identities, control costs with Chalk's platform.
Fraud & Risk
Identify transactions returned for non-sufficient funds.