INTRO

Fraud Detection

Device financing fraud rarely announces itself. The documents look right. The application clears a basic check. A straw buyer walks in and presents exactly like a real customer. The problem only surfaces weeks or months later — when a pattern in the data becomes impossible to ignore. By that point the devices are gone and the losses are already on the books.

THE PROBLEM

Why Fraud Is Hard to Catch Early

Document and identity fraud often passes basic checks without deeper data signals

Fraud at origination is usually discovered only after the device has already left

Multi-dealer fraud patterns are invisible at the individual account level

Coordinated fraud can hit thousands of accounts before the pattern is identified

THE SOLUTION

Risk Signals From the Start — Not After the Fact

Risk scoring at the point of application, before approval

Device fingerprinting and identity verification built into the origination flow

Post-disbursement behavioural anomaly detection continues after the loan goes live

Portfolio-level pattern monitoring catches coordinated fraud invisible at account level

HOW IT WORKS

How Fraud Detection Runs

Risk Scoring at Origination

Risk signals evaluate every application before a lending decision is made — identity verification, device fingerprinting, and behavioural patterns generate a score underwriting teams can act on.

Device Fingerprinting & Identity Verification

Identity signals, device fingerprinting, and application behaviour are assessed in the background of the origination flow — no added latency, no disruption to the application process.

Post-Disbursement Monitoring

After disbursement, device behaviour is monitored for anomalies — unusual usage patterns, bypass attempts, signals suggesting the device may have changed hands. Any of these can trigger an alert.

Portfolio-Level Pattern Detection

Cross-account patterns are watched continuously. A fraud ring hitting twenty dealer locations simultaneously doesn't get far before the portfolio-level view flags it — even if each individual location only sees one or two unusual applications.

Automated Alert & Response

When a threshold is crossed, alerts fire. Where configured, the response is automatic — device restriction, account flag, escalation to the risk team. How much is automated vs. human-reviewed depends on how you've set it up.

KEY CAPABILITIES

Core Capabilities Of The Platform

Risk scoring at point of application

Device fingerprinting & identity verification

Post-disbursement behavioural anomaly detection

Portfolio-level pattern monitoring

Configurable alert thresholds & escalation flows

Reset protection & bypass attempt detection

WHY CHOOSE US

What Earlier Detection Actually Means

✔ Fraud caught at origination costs one rejected application — not a device, a loan balance, and collection effort
✔ Portfolio-level pattern detection catches coordinated activity no individual underwriter could see
✔ The shift from after-the-fact discovery to front-end prevention isn't incremental — it's the difference between a near-zero loss and a fully booked one
✔ Device-level signals often tell you more than a document check ever could — especially in markets with less mature identity infrastructure
✔ Automated screening scales with volume — manual review doesn't, and fraud that slips through tends to repeat before anyone catches it

— USE CASES —

Built For Real Business Challenges

👥

High-Volume Lending Portfolios :

The more applications you process, the more critical automated screening becomes — manual review doesn't scale, and the fraud that slips through a manual process tends to repeat before anyone catches it.

📊

Multi-Dealer Networks

Portfolio-level monitoring is the only view where coordinated fraud becomes visible. A fraud ring hitting twenty dealer locations simultaneously doesn't get far before it's flagged — even if each individual location only sees one or two unusual applications.

📱

Emerging Markets

Less mature identity infrastructure means device-level signals often tell you more than a document check ever could — enforcement that doesn't depend on the quality of the document being presented.

⚙️

BNPL & Micro-Lending

Faster origination cycles create more opportunity for fraud. Risk scoring at application is what keeps the economics from falling apart — catching problems before the device leaves, not after.

— INDUSTRIES

Who We Serve

✔

Telecom Operators :

Risk scoring and device fingerprinting embedded across postpaid handset EMI and prepaid bundles — fraud signals active from the first application, not discovered after the device has left.

✔

NBFCs & Lenders :

Portfolio-level monitoring across dealer networks — the only vantage point where coordinated fraud becomes visible before it's already run through thousands of accounts.

✔

Fintech Companies :

Fraud detection built into your BNPL or embedded finance origination flow — configurable alert thresholds and escalation rules that fit your risk profile, not a generic ruleset.

✔

Retailers & Distributors :

Device fingerprinting and behavioural signals at the point of sale — catching straw buyers and coordinated fraud before the application is approved and the device walks out.

Portfolio-level fraud pattern detection across dealers

Frequently Asked Questions

Common questions about fraud detection for device financing.

Before the loan is approved. Risk scores inform the underwriting decision in real time, so the check happens when it can still prevent the loss — not after the device has walked out the door.

Identity signals, device fingerprinting, behavioural patterns, and application data. The specific combination is configurable based on your lending model and risk appetite. What counts as a red flag for a micro-lender is different from what it means for a BNPL fintech.

Yes — alert thresholds, escalation rules, and the signals that trigger a flag are all configurable. Different lending products can have different rules within the same platform.

Yes. Post-disbursement monitoring tracks device behaviour and flags anomalies — unusual usage patterns, bypass attempts, signals suggesting the device may have changed hands. These can trigger alerts and, where configured, automatic device restriction.

In practice, no. Risk scoring runs in the background of the application flow without adding meaningful latency. The check happens, the score generates, and the application continues in roughly the same time it would without it.

Depending on configuration: the application is flagged for manual review, declined automatically, or approved with conditions. Post-disbursement, signals can trigger device restriction and account escalation. How automated the response is depends entirely on how you've configured it.

Stop Fraud Before It Costs You

Risk signals built into origination — not discovered after the device has left.

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