Digital platforms operate in high-velocity, multi-sided environments where fraud is no longer isolated. Traditional controls like static device fingerprinting, OTPs, and one-time identity checks are under pressure from tactics such as: - Emulator and virtual-device networks - Location spoofing and environment manipulation - Multi-account coordination - Incentive abuse at scale - Fraud-as-a-service ecosystems As AI makes it easier to simulate purely digital signals, platforms face a critical question: which signals still hold up in real-world investigations? This panel explores how teams are combining investigative expertise with signals grounded in real-world behavior to identify coordinated abuse, connect accounts to real actors, and surface risk earlier in the user journey.

Digital platforms operate in high-velocity, multi-sided environments where fraud is no longer isolated. Traditional controls like static device fingerprinting, OTPs, and one-time identity checks are under pressure from tactics such as: - Emulator and virtual-device networks - Location spoofing and environment manipulation - Multi-account coordination - Incentive abuse at scale - Fraud-as-a-service ecosystems As AI makes it easier to simulate purely digital signals, platforms face a critical question: which signals still hold up in real-world investigations? This panel explores how teams are combining investigative expertise with signals grounded in real-world behavior to identify coordinated abuse, connect accounts to real actors, and surface risk earlier in the user journey.

Digital platforms operate in high-velocity, multi-sided environments where fraud is no longer isolated. Traditional controls like static device fingerprinting, OTPs, and one-time identity checks are under pressure from tactics such as: - Emulator and virtual-device networks - Location spoofing and environment manipulation - Multi-account coordination - Incentive abuse at scale - Fraud-as-a-service ecosystems As AI makes it easier to simulate purely digital signals, platforms face a critical question: which signals still hold up in real-world investigations? This panel explores how teams are combining investigative expertise with signals grounded in real-world behavior to identify coordinated abuse, connect accounts to real actors, and surface risk earlier in the user journey.

Digital platforms operate in high-velocity, multi-sided environments where fraud is no longer isolated. Traditional controls like static device fingerprinting, OTPs, and one-time identity checks are under pressure from tactics such as: - Emulator and virtual-device networks - Location spoofing and environment manipulation - Multi-account coordination - Incentive abuse at scale - Fraud-as-a-service ecosystems As AI makes it easier to simulate purely digital signals, platforms face a critical question: which signals still hold up in real-world investigations? This panel explores how teams are combining investigative expertise with signals grounded in real-world behavior to identify coordinated abuse, connect accounts to real actors, and surface risk earlier in the user journey.

Digital platforms operate in high-velocity, multi-sided environments where fraud is no longer isolated. Traditional controls like static device fingerprinting, OTPs, and one-time identity checks are under pressure from tactics such as: - Emulator and virtual-device networks - Location spoofing and environment manipulation - Multi-account coordination - Incentive abuse at scale - Fraud-as-a-service ecosystems As AI makes it easier to simulate purely digital signals, platforms face a critical question: which signals still hold up in real-world investigations? This panel explores how teams are combining investigative expertise with signals grounded in real-world behavior to identify coordinated abuse, connect accounts to real actors, and surface risk earlier in the user journey.