Automatically Check Every Application
Process every application through Instinct and achieve accurate and consistent fraud checking. Instinct will mitigate fraud, reduce operational costs, and increase reputation through a combination of historical data, fraud scoring, behavioural rules, and known criminal activity.
Instinct’s sophisticated algorithms use your organisation’s historical data, rules-based logic, data validation, and fraud scoring to detect suspicious applications and identify repeat offenders. Fraud models can be changed instantly to catch fraud as it evolves.
Applicants are assessed and graded according to their fraud risk. Suspicious cases trigger alerts for further analysis, and are automatically assigned to your fraud review team.
New applications can be linked to existing cases, enabling investigators to see the whole picture and review cases quickly. Customised reports can be generated instantly when more data is required.
Algorithms can be customised to your organisation's database. Instinct can be heavily customised to cater for your specific data requirements, ensuring that data is shown and processed accurately.
Automatically process all applications through a fraud check prior to approval. Applications are processed with high speed to ensure a fast response time.
Reduced fraud loss
Blacklist & watchlist management
Reduce operational costs
Automated risk decisions
Automated review alerts
Automated audit logging
Customised field requirements
Customised user access
Instant fraud definition updates
Group case management
When an application is made, Instinct will quickly perform a fraud check. If a possibility of fraud is detected, an alert will be raised, and the application will be sent to your fraud review team for further analysis. Instinct gives your fraud review team fast and easy-to-use tools to mitigate fraud, and reduce false-positive cases.
Prevent losses from application fraud, and discourage fraudsters from targeting your organisation.
Decisions can be automated and applications prioritised according to your organisation’s goals.
New fraud prevention models can be evaluated against existing strategies by conducting simulations with real data.