Ineffective fraud detection infrastructure in the face of faster adoption of real-time payment methods
Difficulty in identifying and countering rapidly advancing fraud patterns, such as biometric spoofing and advance takeovers
Inability to identify fraud issues with remote transactions, such as card-not-present (CNP) or friendly fraud cases, and associated chargeback fees
Loss of sales and reduced customer dissatisfaction resulting from false declines
Lack of compatible fraud detection mechanisms that can match the pace of innovation in the digital payment industry
Our Fraud Management Solution Includes
Latest technology products in partnership with Featuresapce, a world-renowned brand in financial fraud management
Adaptive behavioral analytics and risk score calculations to identify and prevent card fraud for issuing banks
Machine-learning algorithms to detect bots and suspicious user behavior during an electronic transaction
Leveraging third-party data, fuzzy matching, and synthetic ID profiling to detect application fraud
Advanced analytics to map the customer journey and events across host and third-party systems that help identify money laundering behaviour or scams
Opus Unlocks the Potential of Digital Channels by Managing Fraud Losses
Reduces fraud losses with advanced detection across all digital channels
Monitors real-time transactions for potentially fraudulent behavior and high-risk events
Facilitates machine-learning-based analysis of transaction behavior to reduce false positives
Provides administrators with the necessary access to data and analytical tools to assist them in decision-making
Ensures compliance with data privacy and security regulations
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Frequently asked questions
The fraud management process involves reviewing transaction activities with the aim of identifying unauthorized use of a financial product, such as a credit card.
A fraud management solution employs multiple layers of protection to identify and report fraudulent transactions. Banks and FinTechs deploy advanced fraud management software to manage fraud. These software use machine learning algorithms to analyze user behavior and detect fraud or scams. These solutions are updated on a regular basis to be able to combat newer forms of fraud and scams.
Financial organizations use a few common fraud detection methods. Transaction behavior monitoring is one such method. It uses complex algorithms to identify and report unusual transactional activity, such as a large purchase at a location far removed from the user’s registered address.