Dynamics 365 Fraud Protection


Helps e-commerce, brick-and-mortar, and omni-channel merchants protect their revenue and reputation by providing tools to decrease fraud and abuse, reduce operational expenses, and increase acceptance rates.

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What is Dynamics 365 Fraud Protection and how is it connected to Digital User Identity?

Dynamics 365 Fraud Protection (DFP) is a platform that helps e-commerce, government to resident agencies, and other major brands protect their revenue and reputation by providing tools to decrease fraud and abuse, reduce operational expenses, and increase acceptance rates across account registration and sign-in, as well as during purchase transactions.

Adaptive AI technology

  • Adaptive AI learns and adapts to patterns of legitimate and fraudulent account activities
  • Equips security managers with assessments and tools to optimize multi-factor authentication challenges

Fraud Protection Network

  • Connected knowledge about the behavior of entities across all customers provides a broad awareness of account fraud activity worldwide
  • Security of confidential information and shoppers’ privacy is kept top of mind

Device Fingerprinting

  • Collects device and location attributes that are telltale markers that AI models can use to detect fraud patterns
  • Advanced deep learning models identify returning devices with high fidelity

Bot Protection

  • Helps protect against bot networks attempting to create synthetic accounts or gain access to accounts using stolen credentials
  • Helps defend against scripted spoofing, password spraying, and credential stuffing attacks

What kinds of fraud does DFP Mitigate?

Digital Identity Related Fraud

In combination with a Consumer Identity and Access Management System like Azure AD or Microsoft Entra, DFP helps combat account and discount fraud with adaptive AI technology that continuously learns evolving fraud patterns both from Microsoft’s own web stores as well as your own apps and websites. During an authentication, DFP provides signals to the identity provider of how likely the authentication originates from a risky user (someone who has been compromised) or from a bot (scripted traffic indicative of attack) using machine learning data as well as other inputs from your own existing fraud protection infrastructure.

Purchase-Related Fraud

DFP helps protect revenue by improvingthe acceptance rate of e-commerce transactions with insights and toolsthat help balance revenue opportunity with fraud loss and checkout friction.

Helps protect your revenue​

  • Helps decrease wrongful rejects​
  • Helps increase bank authorizations on card payments​
  • KPIs impacted: Revenue, Authorization Rate

Helps streamline automation and operational efficiency

  • Helps reduce COGS losses to payment fraud​
  • Helps reduce manual review expenses​
  • KPIs impacted: Fraud losses (chargeback rate), manual review rate

Helps deliver a seamless shopping experience​

  • Helps increase the number of successful orders​
  • Helps reduce challenges and delays for customers​
  • KPIs impacted: Order conversion rate, challenge rate, time to fulfillment​

Why work with WhoIAM on your DFP discovery or implementation?

As one of the launch integration partners of DFP, WhoIAM has specialized in the intersection of DFP with major authentication systems to make sure the end-to-end experience from when a user signs up for your service, to when they complete a transaction remains secure. We have a wealth of experience in architecting and deploying DFP to major Fortune 500 accounts as well as to federal, state, and local government agencies across the world.

Some of our credentials in this space:

  • Member of the Dynamics Fraud Protection Customer Advisory Board
  • Top DFP deployment vendor in government for citizen/resident account protection
  • Member of Microsoft Intelligent Security Association (MISA) for our contributions to external/consumer identity deployments
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We’d love to hear from you. Drop us a line if you’d like to discuss our work or would like to schedule a product demo.