Instinct Hub
Application Fraud Management
Instinct Hub is an application fraud and compliance risk management platform that helps you prevent financial crimes when onboarding customers for new services across channels.
Awards & Recognition
Chartis RiskTech Quadrant 2021 - Enterprise Fraud Solutions
Recognised as Category Leader for Enterprise Fraud Solutions.
Forrester Now Tech Report - Large-size APAC EFM Provider 2020
Listed as Enterprise Fraud Management player in Forrester Now Tech APAC, Q4 2020 Report
Regulation Asia Awards for Excellence - Fraud Monitoring & Detection 2020
Awarded Best Solution in Fraud Monitoring & Detection in the Regulation Asia Awards for Excellence 2020
Trusted by over 20,000 companies
Stay agile in your financial crime defence
With the evolving nature of cyber and financial crimes, your approach to fraud prevention needs to be agile and proactive. Instinct Hub helps you stay updated and detect onboarding fraud effectively by using adaptive machine learning and additional risk assessment capabilities.
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Benefits
Detect new and complex frauds
Identify potential fraudulent attempts by uncovering imperceptible risk indicators and anomalies, leveraging adaptive analytics, alternative intelligence, and ongoing account monitoring across the customer journey.
Improve fraud operation efficiency
Automate fraud detection with efficient rule matching and real-time decisioning. Detect up to 30% more fraud while reducing false positives with machine learning.
Orchestrate multi-layer fraud defence
Strengthen fraud detection and decisioning by layering additional intelligence derived from phone, email, IP, device, or behavioural risk assessment capabilities via the Intelligence Center.
Scalable deployment with flexible design
Our platform is designed for fast and scalable solution deployment to support your financial crime strategies and business needs.
Use cases for every challenge
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Get in touch
Contact us to find out more about GBG’s unique fraud and compliance services and how it could help your business.