Intelligence Center for Instinct Hub

Access best-of-breed technologies and intelligence to enhance fraud defence

Introducing Intelligence Center for Instinct Hub

Intelligence Center enable access to additional capabilities and advanced data intelligence for real-time assessment and validation of applicant's identity, geolocation, contact, device and endpoint security during digital onboarding process. This added layer of intelligence on Instinct Hub helps to pick up anomaly risk indicators for additional insights and enhanced defence against evolving online financial crimes.

Mitigate complex financial crimes attacks like account takeovers, money mules and synthetic identity frauds

Identify fraudulent behaviours and suspicious actors with advanced data and cyber threat intelligence

Increases fraud check accuracy by up to 30%

Identify and correlate different fraud risk indicators to improve fraud detection performance

  • Agile threat responsiveness

    Activate advanced fraud assessment capabilities for enhanced detection of new evolving threats

  • Best-of-breed fraud risk assessment capabilities and intelligence

    Wide and growing range of risk detection capabilities and intelligence from GBG and partners

  • Orchestrate effective defence against complex frauds

    Identify and prevent potential frauds behind innonous application behavaiours leveraging both watchlist and additional intelligence layers

  • Comprehensive identity authentication

    Verify applicant's identity against official ID and using biometric identity verification capability, such as facial recognition and liveness detection, helps to verify the credential against the applicant, mitigating incidents of account takeover fraud.

  • Advanced validation with intelligence correlation

    Address, email, phone and geolocation intelligence help to validate the genuinity of the application and enables further insights to help identify high fraud risk indicators found in application manipulation and synthetic identity fraud.

  • Device validation and endpoint security assessment

    Potential identity theft and money laudering can be identified based on device intelligence such as geolocation, device fingerprint, and cyber threat intelligence. Suspicious user behavours on device can also be analysed during the user session to determine if the access is legitimate.

  • Alternative credit risk scoring

    Besides leveraging traditional credit bureau to assess the solvency of individuals, Machine Learning enabled digital credit scoring capability provides device user intelligence for alternative solvency assessment of individuals with thin files or no credit history.

Financial crimes impact 49% of global organisations, with 31% as cybercrimes

Find out how GBG Intelligence Center can grow your quality customers and keep out threat actors in today’s digital economy.

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