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Pipl Trust Solutions

Sharper authorization decisions

Trust is Pipl's real-time risk assessment suite for online fraud, powered by Elephant, our large risk model built on more than 20 years of payment and identity data. From account opening to payment authorization, Trust delivers calibrated risk scores that improve approval performance without increasing fraud exposure.

Why Pipl
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Improve approval performance

Separate legitimate transactions from risk with scoring calibrated to your actual fraud environment, not a generic baseline.

Reduce manual review burden

Resolve more decisions in the scoring layer so fewer cases reach review queues and exception handling.

Protect against AI-driven fraud

Surface AI-orchestrated and coordinated fraud patterns earlier, before they compound into downstream losses.

5B

5 billion unique identities

1T

1 trillion diverse signals

2B

2 billion daily signal updates

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The model behind every Pipl solution

Elephant is a specialist large risk model, not a general-purpose LLM. Built on more than 20 years of payment and identity data, it evaluates over 1,000 signals in combination and can be calibrated to each environment's fraud patterns.

Every Trust product is powered by Elephant. The result is a precise, explainable risk score in milliseconds, ready for your decision logic.

Learn about Elephant

One engine, every authorization moment

Four Trust products, one engine behind every decision. Each product is the surface of the same system, at every moment of the authorization workflow.

Captures device fingerprint, behavioral biometrics, and session context.

Delivers Elephant's risk score in real time, calibrated to your environment's fraud patterns.

Shows the reasoning behind each score, so review queues move faster.

Tracks behavioral signals across accounts and flags suspicious patterns before they compound.

Click + to expand each product.

i Hover the markers to explore the engine.

iHover the markers to explore the engine.

Device context, captured before scoring begins

Trust Device captures device fingerprint, behavioral signals, and session context the moment a session begins, then answers what device tools alone can't: does this device belong to the person claiming to use it, verified against an identity graph of 5 billion profiles.

That context reaches Elephant alongside the transaction, unmasking emulators, bot farms, and spoofed environments while recognizing trusted customers, even on a first visit. The result is a score that catches fraud, and trust, that transaction data alone would miss.

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Pipl Trust plugs into the fraud platforms you already run

Trust deploys into the fraud platforms that enterprise teams already run. Elephant's risk assessment layers into your existing workflow without rebuilding it. Deploy any or all of the four Trust products through the platform you already use.
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Fraud decisioning platforms

FICO Falcon, Accertify, Feedzai
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Ecommerce fraud platforms

Riskified, Signifyd, Forter
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Trust & safety platforms

Kount (Equifax), Sift
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Payment decisioning platform

Cybersource (Visa)
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Analytics and risk platform

SAS
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Behavioral analytics platform

Featurespace

Measurable results in complex payment environments

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Global Social Media Platform

Higher precision, fewer false flags, zero friction

With millions of new signups every month, this global social platform was over-challenging good users and under-catching risky ones. Calibrated Trust Scores nearly doubled fraud recall at top precision and flagged 40% of risky registrations the native model missed.

Read Case Study
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Global Consumer Electronics Brand

Fraud down, approvals up, trust calibrated

A mature fraud stack still wasn’t enough. Review costs were climbing, approvals had stalled, and new threats kept slipping through. In under four months with Pipl Trust, this consumer brand cut chargebacks by 3 BPS, dropped manual reviews 27%, and lifted model performance 35%.

Read Case Study
case-studies-travel 
 
Travel Booking Platform

Fewer false positives, better signal clarity

For this travel booking platform, fraud was hiding inside third-party processors and high-value international bookings. Pipl held a ROC-AUC of 0.87 even with messy, fragmented data, catching fraud earlier and clearing credible travelers faster.

Read Case Study
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National Retailer

Lower chargebacks, fewer manual reviews

This retailer’s legacy rules engine couldn’t be touched without breaking downstream workflows. Pipl slotted in as a scoring layer and delivered an estimated $2.3M in chargeback reduction and 15.3% fewer manual reviews, without rewriting a single rule.

Read Case Study
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Global Marketplace

More trusted users and fewer losses at scale

This marketplace was stuck choosing between strict rules and lost revenue. Pipl’s Trust Score cut chargebacks from 12% to 4%, dropped manual reviews from 9% to 3.5%, and lifted approvals 19.4 percentage points at the same fraud threshold.

Read Case Study

Frequently asked questions
about Pipl Trust

How does Pipl Trust improve authorization performance without increasing fraud exposure?

Trust delivers risk scores calibrated to your environment's actual fraud patterns, not a generic baseline. Because Elephant is trained on a trillion signals and adapts to portfolio-specific conditions, it separates legitimate transactions from real risk with greater precision.

Fewer good transactions get declined, fewer fraudulent ones get approved, and approval rates and fraud rates move in the right direction together.

 

What makes Elephant different from other payment fraud models?

Elephant is the first domain-specific large risk model purpose-built for payment fraud. It's built on more than 1 trillion signals accumulated over 20 years of making fragmented global identity data usable in enterprise fraud decisions.

Unlike models trained on short data windows or applied generically across different portfolios, Elephant calibrates to the fraud patterns and portfolio conditions of the specific environment it operates in.

It evaluates identity, behavioral, and device signals together as a connected picture rather than treating them as isolated inputs, and it retains its reasoning at every layer, so scores remain explainable across compliance reviews, regulatory inquiries, and internal audit.

How does Pipl Trust pricing work?

Trust uses simple, all-inclusive pricing: pay once per transaction scored, with all four Trust products included. That replaces the typical fraud vendor pattern of charging separately for partial solutions and reduces vendor sprawl in your fraud stack.

How does Pipl Trust support explainability and regulatory compliance requirements?

Elephant retains its reasoning at every layer of the risk assessment, so the factors that contributed to a score remain accessible and defensible across compliance reviews, regulatory inquiries, and internal audit.

Every Trust API score is delivered with the signals and reason codes behind it, suitable for adverse-action requirements, and Trust Insights surfaces that reasoning directly to analysts, reducing the reconstruction burden when decisions are challenged.

For regulated payment environments where explainability is a requirement rather than a preference, decisions built on Trust scores hold up under scrutiny without additional documentation or manual justification.

Which types of payment organizations is Pipl Trust built for?

Pipl Trust is built for enterprise organizations where approval performance and fraud exposure are competing pressures. That includes high-volume merchants in retail, travel, marketplaces, ticketing, gaming, and telecom, as well as financial institutions and payment networks scoring transactions and account openings in real time.

The common thread is a dedicated fraud team that wants transparency and control: your own models, your own thresholds, and a score you can calibrate, rather than a black-box verdict from a vendor.

 

How does Pipl Trust improve authorization performance without increasing fraud exposure?

How does Pipl Trust improve authorization performance without increasing fraud exposure?

Trust delivers risk scores calibrated to your environment's actual fraud patterns, not a generic baseline. Because Elephant is trained on a trillion signals and adapts to portfolio-specific conditions, it separates legitimate transactions from real risk with greater precision.

Fewer good transactions get declined, fewer fraudulent ones get approved, and approval rates and fraud rates move in the right direction together.

 

What makes Elephant different from other payment fraud models?

What makes Elephant different from other payment fraud models?

Elephant is the first domain-specific large risk model purpose-built for payment fraud. It's built on more than 1 trillion signals accumulated over 20 years of making fragmented global identity data usable in enterprise fraud decisions.

Unlike models trained on short data windows or applied generically across different portfolios, Elephant calibrates to the fraud patterns and portfolio conditions of the specific environment it operates in.

It evaluates identity, behavioral, and device signals together as a connected picture rather than treating them as isolated inputs, and it retains its reasoning at every layer, so scores remain explainable across compliance reviews, regulatory inquiries, and internal audit.

How does Pipl Trust pricing work?

How does Pipl Trust pricing work?

Trust uses simple, all-inclusive pricing: pay once per transaction scored, with all four Trust products included. That replaces the typical fraud vendor pattern of charging separately for partial solutions and reduces vendor sprawl in your fraud stack.

How does Pipl Trust support explainability and regulatory compliance requirements?

How does Pipl Trust support explainability and regulatory compliance requirements?

Elephant retains its reasoning at every layer of the risk assessment, so the factors that contributed to a score remain accessible and defensible across compliance reviews, regulatory inquiries, and internal audit.

Every Trust API score is delivered with the signals and reason codes behind it, suitable for adverse-action requirements, and Trust Insights surfaces that reasoning directly to analysts, reducing the reconstruction burden when decisions are challenged.

For regulated payment environments where explainability is a requirement rather than a preference, decisions built on Trust scores hold up under scrutiny without additional documentation or manual justification.

Which types of payment organizations is Pipl Trust built for?

Which types of payment organizations is Pipl Trust built for?

Pipl Trust is built for enterprise organizations where approval performance and fraud exposure are competing pressures. That includes high-volume merchants in retail, travel, marketplaces, ticketing, gaming, and telecom, as well as financial institutions and payment networks scoring transactions and account openings in real time.

The common thread is a dedicated fraud team that wants transparency and control: your own models, your own thresholds, and a score you can calibrate, rather than a black-box verdict from a vendor.

 

Better authorization decisions, calibrated to your environment

Generic fraud tools produce generic results. Pipl Trust calibrates to your environment's actual fraud patterns, so decisions reflect the risk you're actually managing.

Contact us
Why Pipl