Full case study
suss.
AI-powered fraud detection
Enterprise Pilot Brief
Prepared for SDSU / CSU System
Incident Reference
SDSU lost $5.9M to vendor invoice fraud
A fraudster impersonated a legitimate vendor, sent an invoice with new bank details, and SDSU wired $5.9 million to a fraudulent account. FBI assisted with 90%+ recovery.
94%
Risk Score
Source: The Daily Aztec, Feb 25, 2026

6 threat indicators fired

90%
Vendor bank account change request
85%
New vendor with urgent first payment
85%
Sender domain impersonating vendor
80%
Wire transfer instructions via email
75%
Urgency with late payment penalty
70%
Vendor contact person changed

Why universities are targets

Large vendor ecosystems
Hundreds of active vendors — AP teams can't verify every invoice change.
Decentralized purchasing
Department-level procurement = more entry points for fraud.
High transaction volumes
Millions in monthly payments make scrutiny impractical.
Public org charts
Leadership and finance contacts are publicly listed.
CSU System Exposure
23 campuses. 500K+ employees. $13B+ annual budget. If it happened at SDSU, it can happen anywhere in the system.

How the 30-day pilot works

1
Submit suspicious emails
Forward any suspicious invoice or payment request for instant analysis. Zero IT integration.
2
AI scans in seconds
Purpose-built BEC detection analyzes for impersonation, fraud patterns, and social engineering.
3
Verdict via email
Staff gets a risk score, threat type, and recommended actions before any payment is processed.
4
Dashboard for IT
Real-time view of scan volume, threat categories, and ROI metrics.

Purpose-built BEC detection across 4 threat categories

Invoice & Vendor Fraud

Detects fraudulent payment changes, suspicious vendor requests, and invoice manipulation.

Executive Impersonation

Identifies spoofed executive communications and urgency-based payment requests.

Wire & Payroll Diversion

Flags suspicious payment routing, new beneficiary requests, and unauthorized changes.

Email Authenticity

Verifies sender legitimacy, domain reputation, and communication anomalies.

$5.9M
SDSU loss prevented
94% detection
40+
Scam categories covered
BEC + phishing + more
94.5%
Detection precision
Near-zero false positives
94.5%
Threat coverage
Comprehensive detection
<2s
Response time
Before payment sent

Pilot terms

Duration
30 days, free
No credit card. No commitment. Cancel anytime.
Setup
Zero IT integration
Staff BCC emails to a scan address. No firewall changes, no software install.
What you get
Full threat intelligence
Real-time verdicts + end-of-pilot report with threat landscape analysis.
Ready to start?
Email us or visit the full case study for a live detection demo.
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Case study: gotsuss.ai/case-study/sdsu
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Web: gotsuss.ai