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Fraud Management

Building a Safe Digital Environment by Mitigating Payment Fraud

Opus believes in a proactive approach towards card and payment fraud management. Based on advanced machine learning algorithms, Opus' technology simplifies payment flow for the end customer while offering enhanced protection against counterfeit cards, lost and stolen cards, card-not-present transactions, account takeovers, and scams.

Key Challenges Faced by Banks, E-Commerce Merchants, and Service Providers in Combating Card Fraud

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Ineffective fraud detection infrastructure in the face of faster adoption of real-time payment methods

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Difficulty in identifying and countering rapidly advancing fraud patterns, such as biometric spoofing and advance takeovers

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Inability to identify fraud issues with remote transactions, such as card-not-present (CNP) or friendly fraud cases, and associated chargeback fees

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Loss of sales and reduced customer dissatisfaction resulting from false declines

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Lack of compatible fraud detection mechanisms that can match the pace of innovation in the digital payment industry

Stay a step ahead with the trusted round-the-clock fraud management solutions

With the world migrating away from cash and towards real-time payments, the frequency and complexity of card fraud are evolving at a rapid pace. Financial institutions and FinTechs have to stay ahead of fraudsters while providing a non-intrusive user journey to their customers. Opus has deep expertise in preventing fraud by using machine-learning algorithms and behavioral analytics to detect financial fraud. We strive to amplify sales for our clients through digital transactions while reducing fraud losses.

Our Fraud Management Solution Includes

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Latest technology products in partnership with Featuresapce, a world-renowned brand in financial fraud management

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Adaptive behavioral analytics and risk score calculations to identify and prevent card fraud for issuing banks

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Machine-learning algorithms to detect bots and suspicious user behavior during an electronic transaction

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Leveraging third-party data, fuzzy matching, and synthetic ID profiling to detect application fraud

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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

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Reduces fraud losses with advanced detection across all digital channels

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Monitors real-time transactions for potentially fraudulent behavior and high-risk events

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Facilitates machine-learning-based analysis of transaction behavior to reduce false positives

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Provides administrators with the necessary access to data and analytical tools to assist them in decision-making

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Ensures compliance with data privacy and security regulations

Recommended Resources To Explore

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.