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Payment Fraud Prevention

Reduce chargebacks and payment fraud

LRDefender scores the device and browser context before your PSP sees the card—so you decline stolen instruments, flag mule patterns, and protect good customers from unnecessary friction.

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67%

Fewer chargebacks

<40ms

Decision latency

90+

Risk signals

$2.1M

Avg. annual savings

The Problem

Fraud moves faster than rule updates

Stolen cards and synthetic identities clear AVS and 3DS just often enough to hurt. Static BIN lists and velocity rules catch yesterday’s attack; today’s fraud uses fresh devices and split sessions across merchants.

First-time fraudsters appear as “new good” customers because there is no chargeback history on file.
Friendly fraud and BNPL abuse hide behind real devices until disputes arrive weeks later.
High false declines push buyers to competitors while fraud still slips through on weaker checks.
PSP-level scores miss your catalog-specific patterns—gift cards, digital goods, high-margin SKUs.
Investigations lack a shared device story between checkout, account creation, and post-purchase changes.

The Solution

Authorize with a device story, not a single score

LRDefender enriches every payment attempt with device stability, tampering signals, and cross-session links—fed into your risk engine or ours—so you stop fraud at authorization without punishing loyal buyers.

Pre-auth device risk bundle

Send a compact signal pack to your fraud platform: emulator hints, canvas stability, keyboard timing anomalies, and VPN/datacenter likelihood.

Instrument-specific policies

Tighten automatically for one-click wallet checkouts and high-risk MCCs; relax where your data shows clean conversion.

Linking across guest and logged-in flows

Connect guest carts to account history when the same device shows up again—closing the gap fraudsters exploit between signup and pay.

Chargeback forensics export

Bundle device timelines and signal snapshots for representment and internal loss reviews.

Real-time model refresh hooks

Stream outcomes back to LRDefender so segment-specific models adapt as fraud rings rotate tactics.

Latency-safe integration

Designed for payment paths where every millisecond counts—parallelize with 3DS and network token steps without blocking UX.

How It Works

Three steps to protection

1

Collect on checkout surfaces

Lightweight SDK on web and in-app checkout; optional server-side session binding for headless and API orders.

2

Score before capture

LRDefender returns a fraud-oriented device assessment in line with your PSP authorization call.

3

Tune with labeled outcomes

Feed approvals, declines, and chargebacks so precision improves on your exact product mix—not a generic benchmark.

Products Used

Stop funding fraud at the card tap

See how teams cut chargebacks without blanket declines—start a trial, plug into your existing risk stack, and benchmark latency on your checkout.

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