2018 Whitepapers

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Machine Learning: The Secret Ingredient for Detecting and Preventing Fraud

Simility's Chief Technology Officer shares insights on how machine learning can be beneficial to eCommerce companies and why this technology is playing an increasingly important role in fraud detection and mitigation.

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Future of Device Fingerprinting

Simility discusses recent innovations to enhance the efficacy of device fingerprinting and several use cases where this technology can help uncover fraud and abuse.

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Online Marketplace Fraud

Simility explores common fraud patterns targeting online marketplaces and details three ways in which companies can better identify suspect users and transactions.

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2018 Voice Intelligence Report

Pindrop discusses the growing problem of fraud originating from the voice channel and which industries are particularly impacted by this threat.

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The 7 Habits of Successful "New" Payments Leaders

SafeCharge and Edgar, Dunn & Company share key findings and best practices from their survey of a dozen payments leaders across disparate industries and geographies.

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Visa Chargeback Rules

DIMOCO highlights key changes in Visa's revamped rules on chargebacks, known as Visa Claims Resolution, or VCR, and shares several insights on how merchants can help reduce the volume of chargebacks they receive.

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Making the Move to Dynamic Multifactor Authentication

iovation takes a detailed look at multi-factor authentication and explains that it can, when used in a dynamic context, offer enhanced security and a better user experience.

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Fighting Fraud Without Wounding Customer Experience

Simility explores the intersection of fraud prevention and customer experience, and examines the impact risk mitigation can have on customer trust.

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Why Machine Learning for Fraud Detection?

Ravelin examines the process of moving to a machine learning platform, including the methodology behind scoring and risk thresholds, and discusses the impact machine learning is having on fraud analysts.

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Mission Critical Artificial Intelligence & Machine Learning

Discover the advantages and drawbacks of key machine learning and artificial intelligence techniques, and the implications these characteristics have for fraud and risk mitigation.

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