Featurespace invented Adaptive Behavioral Analytics and created the ARIC™ platform, a real-time machine learning software that risk scores events in more than 180 countries to prevent fraud and anti-money laundering.
ARIC uses advanced, explainable anomaly detection enabling financial institutions to automatically identify risk, catch new fraud attacks and identify suspicious activity in real-time. Over 30 major global financial institutions, including 4 of the 5 largest banks in the UK use ARIC to protect their business and customers. Publicly announced customers include HSBC, TSYS, Worldpay, RBS NatWest Group, Contis, Danske Bank, ClearBank, and Permanent TSB.
Region
Global, APAC, EMEA, NAM, LATAM
Connector
Connector not available
Card Fraud Prevention
Protect your business and your customers from card fraud with ARIC:
Zero model degradation
Automatically detect new types of fraud
Dramatically reduce false positives
Real-time processing and decisioning
ARIC profiles customers holistically, pulling data from touchpoints across the customer journey, providing accurate risk scores for all types of card transactions, including (but not limited to):
In-store card payments (including contactless)
Online shopping
MOTO (Mail & Telephone)
Mobile wallets and e-payments
ATM/Cash machine withdrawals
Application Fraud Prevention
Reduce friction at account opening and across the customer journey while preventing fraud with ARIC Risk Hub:
Profile activity from the start of an application and get an accurate risk score for each individual before on-boarding
Risk scoring behavioral activity through-out the application process minimizes friction and improves security
Review flagged applications via the ARIC dashboard and run deep investigations using our powerful incident management suite
View reports of application fraud incidents within the intuitive UI
Configure rules, models and risk thresholds to accept, reject or review applications within the Application Fraud Prevention dashboard
Payment Fraud Prevention Protect your customers and their accounts from fraudulent activity including debit card and non-card payment channels by profiling monetary and non-monetary data points, with minimal manual intervention.
Combine data from a variety of sources, including device ID, customer behavior, and cross-channel transactions in a single solution, protecting your customers from payments fraud while minimizing friction and reducing the need for manual intervention.
Real-time detection of fraud using machine learning and Adaptive Behavioral Analytics
Use unique Adaptive Behavioral Biometrics to monitor the whole online banking session and stop fraud before a payment is even attempted
Works on all payment types (Faster Payments, BACS, Zelle, ACH, SWIFT, API and more).
Automatic detection of both new and existing types of:
Check Kiting
Account Takeover
Man in the Middle
Man in the Browser
Social Engineering
Authorized Pushed Payments
Money Mules
Elder Abuse
Merchant Monitoring
Monitor merchant onboarding and transactional behavior to proactively identify anomalous chargeback and bust-out activity.
Using the latest machine learning technology alongside cutting- edge behavioral models, the ARIC Risk Hub enables organizations to monitor merchant behavior and risk from the initial account application through to the processing of transactions - preventing chargebacks and bust outs.
ARIC analyzes and risk scores every transaction in real time - stopping more fraud with fewer alerts. The result is minimal negative impact to your genuine merchants and higher payment conversion with reduced risk.
Unified user interface - combine payment event information with Adaptive Behavioral Analytics technology in one UI
Monitor and identify merchant risk for even the most complex types of fraud, including transactional laundering and merchant bust out
Prevent more fraudulent transactions and increase operational efficiencies
Identify fraudulent merchant applications
Automate and streamline the merchant onboarding process
Prevent costly losses throughout the onboarding process
