IDENTITY VERIFICATION AND INVESTIGATION FOR FINTECH

VERIFY IDENTITIES. INVESTIGATE FRAUD.

EMAIL, MOBILE, AND SOCIAL IDENTITY INFORMATION THAT SPANS THE GLOBE

Today's customers expect to be able to open accounts and apply for credit online with minimal information — leaving you to figure out the rest.

Pipl goes well beyond simple credit header data and makes it easy to know the real person behind an account. With over 3 billion online identities containing current and historical information, you can accept more new accounts in more places with greater confidence and simplify the detection of identity data abuse.

6m 20s

Global

150 countries

Email

1.7 billion email addresses

Mobile

1.9 billion mobile phone numbers

Social

4 billion social media usernames

THE CHALLENGE

IMPROVE YOUR KYC AND FRAUD-PREVENTION CAPABILITIES

Fintech companies that interact with their customers online face unique challenges in the form of KYC requirements and fraud prevention. Synthetic identity fraud and account takeover are on the rise – and traditional tools that depend on authoritative data like credit headers and state-issued identification have proven ineffective at combating them.

Pipl’s identity trust gives Fintech companies a new way to verify that account holders are who they say they are and that the information they submit is indeed associated with them.

APPLICATION EXAMPLES

NEW ACCOUNT OPENING

Verify identity information instantly with automated systems and rapid manual review processes
Reduce the risk of fraud by knowing more about your customers – no matter where they live
Automate new account screening processes
Comply with local and international KYC regulations

FRAUD INVESTIGATION

Prevent and remediate account takeover by spotting emails, phone numbers, and other identity information not associated with the true account holder
Simplify the detection of stolen and synthetic identities
Build and resolve cases faster with more complete data

eBook: DEFENSE AGAINST SYNTHETIC IDENTITY

Synthetic Identity Fraud (SIF) happens when criminals combine real and fake information to create and nurture identities to use for fraud. The real information, such as a Social Security Number, is usually stolen. The fake information is publicly seeded to create the illusion the identity is real. It’s hard to detect with traditional fraud filters—and it’s a growing focus for manual review teams.

Ebook