Use Case: Food Delivery Fraud
Your Platform is Paying for Deliveries that Never Happened
Ghost orders, GPS manipulation, and coordinated account fraud silently drain food delivery revenues each year. Bespot Gatekeeper detects every attack at the device level, before a single fraudulent payout clears.
01
Challenge
Fraud is Scaling Faster Than Your Operations
Food delivery platforms are uniquely exposed. You operate across thousands of driver and customer accounts, process real-time transactions at a massive scale, and depend on location data that bad actors can manipulate with a free app download.
Traditional fraud controls, static rule engines, manual review queues, and post-hoc chargebacks were built for a slower world. Fraudsters have moved on. The result? Inflated driver payouts, drained promo budgets, and compromised customer accounts. Every incident decreases your margins, restaurant relationships, and brand trust.
Persistent Device ID
Real-Time Risk Signals
Every order we process has a 1-in-8 chance of being fraudulent. We didn't build a delivery platform, we built a fraud machine.
02
Solution & Results
Bespot Gatekeeper: Device-First Fraud Prevention for Food Delivery
Traditional fraud tools analyze transactions. Bespot targets the source: the device. Every fraudster, regardless of fake accounts, SIM cards, or VPNs, operates from a physical device. That device is their fingerprint. And we never lose it.
What if they use emulators instead of devices? We have got you covered on this front too.
Our platform combines persistent device intelligence with real-time behavioural analysis to detect fraud in real time, not after the damage is done. No rule engines to game. No review delays. No blind spots.
Platform Capabilities
- Persistent Device ID: Survives factory resets, VPNs, and SIM changes. Links all accounts ever created from a device, exposing multi-accounting rings invisible to session-based tools.
- Behavioral Risk Intelligence: ML models trained on food delivery fraud patterns identify GPS spoofers, auto-clickers, and app cloners the instant they activate.
- Real-Time Risk Signals: Risk scores delivered in under 200ms per session. Fraud stopped before checkout, not after fulfilment.
- Seamless API Integration: Drop-in SDK for iOS, Android, and web. Connects to your existing systems without a rearchitecture project.
- Fraud Operations Dashboard: Real-time visibility into fraud trends, blocked accounts, and estimated savings for your ops and fraud teams.
What Platforms Achieve with Bespot
- Fraud Rate Reduction: Across ghost orders, promo abuse, and multi-accounting within the first 30 days of deployment.
- Monthly Savings Recovered: In recaptured incentive payouts, chargeback reversals, and eliminated fraudulent promo claims.
- Decision Latency: Risk scores delivered per session in real time. Fraud stopped before checkout, not after fulfillment.
- False Positive Rate: Legitimate drivers and customers virtually never incorrectly flagged. Revenue protected, not blocked.
- Average Integration Time: From contract to live fraud detection, no rearchitecture, no months-long implementation sprints.
- Bot Detection Accuracy: Auto-clickers are identified at the device level before a single order is manipulated.
Fraud Scenarios - Customer Side
Account Takeover (ATO)
Fraudsters use credential-stuffing attacks — testing leaked username/password combinations against your platform at scale — to access legitimate accounts. Once inside, they order food using saved payment methods or harvest stored card data.
Impact:
- Customers charged for orders they never placed, destroying trust
- Stored credit card data at risk of downstream theft and exploitation
- Chargeback rates spike, threatening your payment processor relationship
Promo & Referral Abuse
Fraudsters create hundreds of fake customer accounts using disposable emails and virtual numbers – each claiming ‘first order’ discounts and referral credits before cycling to the next platform systematically.
Impact:
- Marketing acquisition budgets depleted by synthetic user registrations
- Referral programs become loss-generating rather than growth-driving
Friendly Fraud & Refund Exploitation
A customer places a real order, receives their food, then disputes the charge — either with their bank or through your support system. Serial offenders exploit easy refund policies to consistently dine for free. These users are invisible to basic rule-based systems because each individual claim looks plausible in isolation.
Impact:
- Chargeback fees per order affect economics directly
- Support team time consumed by fraudulent claim investigation
- Legitimate restaurants penalized through false low-rating patterns
- Elevated dispute rates risk your relationship with payment processors
Fraud Scenarios - Driver Side
Ghost Orders & Simulated Deliveries
Fraudsters clone the delivery app, generate thousands of fake accounts on a single device, then use autoclickers to accept orders. GPS spoofers simulate the route and mark it complete, without leaving home.
Impact:
- The platform pays incentives for deliveries that were never made
- Completion metrics are artificially inflated, masking true performance
- Legitimate orders are starved of available drivers in real time
GPS & Location Spoofing
Drivers use freely available GPS spoofer apps to appear near restaurants or in high-demand zones, grabbing premium deliveries they can’t actually fulfil. Others spoof arrival to claim payment without reaching the customer.
Impact:
- Fraudulent drivers monopolize peak-hour bonuses unfairly
- Customers pay for orders they never receive, destroying trust
- The platform’s location data becomes fundamentally unreliable
Promo & Incentive Abuse
Bad actors generate thousands of fake driver identities from a single device, claiming every bonus tier repeatedly: sign-up bonuses, peak-hour multipliers, and completion milestones.
Impact:
- Sign-up bonus pools drained by synthetic driver identities
- Completion bonuses claimed through ghost order rings
- Incentive program ROI entirely destroyed at scale
Account Sharing & Identity Fraud
Drivers sell or lend verified credentials to uncertified and unselected individuals, bypassing background checks entirely. Others create multiple accounts under different names, all from the same device and household.
Impact:
- Unselected, potentially dangerous individuals make customer deliveries
- Platform responsibility exposure increases significantly
- Customer safety and brand trust are undermined over time
Why Traditional Systems Fail
Rule Engines Can't Keep Up
Legacy fraud tools were built for simpler attacks. Modern food delivery fraud is coordinated, device-aware, and faster than any manual review cycle.
Manual Review Queues
At scale, manual review always lags. By the time a fraudulent driver is identified, thousands in incentives have already been paid out.
Post-Transaction Blocking
Catching fraud after fulfilment means the damage is done. Chargebacks, refunds, and payout clawbacks are expensive and operationally painful.
Data Models
Systems that analyze driver and customer fraud independently miss coordinated rings controlling accounts on both sides simultaneously.
How our Platform Strengthens Food Delivery
Protect Your Driver Incentive Budget
Every incentive of sign-up bonuses and peak-hour multipliers reaches a real, active driver, not a synthetic account running autoclickers in a warehouse.
Secure Your Promotion Economics
First-order discounts and referral programs convert new customers at the cost your marketing team determines, not 10x that cost due to multi-account exploitation.
Build Customer Trust at Scale
Account takeover fraud destroys customer relationships. Bespot ensures that when a customer opens your app, their account and payment data are theirs alone.
Maintain Restaurant Partner Trust
Ghost orders damage restaurant partners who lose preparation costs on orders that were never real. Fraud prevention protects the entire ecosystem.
Meet Compliance Obligations
Data protection and fraud prevention requirements are increasingly encrypted. Bespot's audit-ready reporting helps you stay ahead of regulatory scrutiny.
Free Your Operations Team
Manual fraud investigation is expensive and slow. Bespot automates detection, so your team focuses on strategy, not ticket queues.
Why Choose Bespot Gatekeeper
Privacy-Compliant by Design
GDPR & CCPA compliant out of the box. No legal review required before deployment.
Global Coverage
Fraud rings operate across borders. Bespot's global device graph connects accounts that look local but are coordinated internationally.
Deploy in max 4 Days
SDK integrates with your existing stack in under four days. No infrastructure restructuring, no lengthy planning rounds. Real protection starts fast.
ROI from Day One
Every fraudulent incentive claim blocked and every promo abuser stopped at registration is recovered revenue.
FAQ: Food Delivery Fraud
Can Bespot detect rings that control driver and customer accounts?
Yes. This is a core strength. Bespot's device graph links accounts across both sides of your marketplace. Ghost order rings control both driver and customer accounts - often from the same device. Our graph detection exposes these coordinated structures that siloed systems miss entirely.
How long does integration take for a platform at scale?
Most platforms complete integration within 2-4 days. Our SDK supports iOS, Android, and web with full documentation. For enterprise platforms with custom systems, our solutions engineers work directly with your team for a smooth, non-disruptive rollout.
Is Bespot compliant with GDPR and data protection regulations?
Bespot is GDPR & CCPA compliant. Device intelligence is created without collecting personally identifiable information. Our data retention and processing practices are fully auditable, making regulatory review straightforward for your legal and compliance teams.
Get in touch with Bespot
Our offices in Athens, Greece:
Voutadon 28, Athina 118 54