Fraud detection processes monitor and analyze customer data, transaction activity and other user behavior to identify suspicious or potentially unauthorized activity. By leveraging AI, machine learning, and advanced analytics, modern fraud detection systems proactively detect and prevent fraud and mitigate institutional losses. Mitek’s AI-powered fraud prevention solutions give organizations the ability to spot and stop threats in real time.
Use case / examples for fraud detection:
Transaction fraud detection: Identifying suspicious transactions or patterns of transactions based on purchase velocity, amount, and frequency.
Account flagging: Flagging accounts after multiple failed logins from multiple geolocations.
Real-time risk scoring: Scoring transactions in real time, with the use of AI and behavioral biometrics to assess the risk from any specific transaction or login.
Loan origination: Detecting fraudulent loan applications by analyzing document authenticity, liveness, and biometric data.
