Trust scoring across millions of card authorizations a year.
Separating real shoppers from fraud at checkout, at scale.
Validating identity in real time, before money moves.
Other tools are built for broad applicability, not your actual fraud environment. When they can't capture the conditions your team manages, decision quality weakens and the gap gets covered by manual effort.
Other tools are easy to stand up but difficult to tune to the fraud patterns and approval goals that define your business.
A phone, email, or device on its own is just an attribute. Elephant evaluates whether those attributes make sense together.
Decisions that can't be explained become harder to defend under compliance review or internal audit. Pipl's intelligence holds up across systems.
When intelligence lacks conviction, work moves downstream to review queues. More precise risk assessment keeps it from getting there.
Large language models reason in prose. Fraud decisions get made in milliseconds, against structured signals like transaction histories, device fingerprints, and identity attributes. Elephant is a large risk model built for that job specifically. Evaluative, not generative. Precise at one high-stakes decision, not broad across many.
The live signal network feeding the stack. Continuously refreshing inflow from the world’s largest payment environments, with more than 2 billion daily signal updates, sourced from the places where payment fraud actually happens.
Trust, Search, and Elements deploy Elephant's intelligence into the workflows enterprise teams already own. Sub-200ms response times, privacy-preserving design, and no rebuild required for the systems already in place.
Trained on more than 1 trillion identity, payment, and behavioral signals, calibrated to the fraud patterns of each environment it operates in. Evaluative, not generative, and built for precision at one high-stakes decision.
The resolved identity foundation Elephant operates against. More than 5 billion digital identities across 28 billion unique identifiers, including 3 billion global mobile numbers and 10 billion global email addresses, built across 20 years of fragmented global markets.
Twenty years of global identity and payment data, collected before AI-generated identities existed and refined across the environments where identity data is hardest to find. The depth that makes the rest of the stack defensible.
The payment moment is where fraud and false declines both cost you. Score each transaction in real time against the identity behind it, whether it's a card at checkout or money moving over RTP, wire, or P2P.
