Your business should scale.
Fraud shouldn't.

Prevent synthetic fraud with our advanced clustering technology. SentiLink equips your organization with tools needed to pinpoint and stop synthetic identities.

SentiLink stops
synthetic fraud.

SentiLink's technology helps you detect and block synthetic identities, where the name, date of birth, and SSN don't correspond to a single real person. Our real-time API and risk analyst tools identify these fake people and other connected fraudulent applications so they don't harm your bottom line.

Connect the dots.

Today's fraud rings are sophisticated, and will give each identity its own phone number, email address, device, and address. SentiLink's patent-pending soft-clustering technology links together fraudulent applications originating from the same crime ring by searching for statistical anomalies, even if the applications don't share any information explicitly.

Secure and
compliant.

SentiLink's rigorous and audited security program complies with the GLBA and other federal laws and regulations for maintaining the security and privacy of consumer PII.

Use the SentiLink blacklist.

The same fraudsters are targeting every lender in the industry.

Our team

The SentiLink team brings together years of experience building fraud products.

Naftali Harris

Naftali Harris graduated from the University of Chicago with a degree in statistics after dropping out of high school. He subsequently joined the Stanford PhD program in statistics, where he was a Stanford Graduate Fellow. In his professional career, he designed the Titanic dataset for Kaggle and built tweet topic models at Twitter before managing the data science team at Affirm. At Affirm, Naftali was responsible for all production risk systems: his team’s credit and fraud models determined who was approved and who was declined. In his free time, he has a knack for getting his blog posts to the top of Hacker News. Naftali is excited about ending transactional fraud.

Max Blumenfeld

Max Blumenfeld has manually fraud-reviewed over three thousand financial transactions as a risk analyst, verifying the identities of customers online and over the phone, and discovering new fraud vectors. After teaching himself to code in his spare time, he built production risk operations tools and fraud models, and eventually led Affirm’s fraud program. He takes a special interest in synthetic identities, document forgery detection, and account takeover prevention. He has consulted for some of the biggest banks in the world on money laundering and fraud prevention. Max graduated from the University of Chicago with degrees in math and economics.

Investors & backers