(While solution providers have multiple functionalities, these categories group providers by their core function. All providers have ONLY ONE Primary Functionality.)
A solution that provides a comprehensive platform of risking capabilities and services. These solutions vary greatly in methodology and technology, however the range and/or scale of coverage qualify them under this category.
Identity & Authentication
Some fraud platforms authenticate users, but these solutions have a distinct focus on authentication and digital identities. They span a variety of technology and fraud types.
Data Provider & Verification
These solutions leverage identity data at scale. The data is then used by clients to help with verification and data enrichment. They have a diverse customer base, including other fraud solution providers.
While many solutions help manage chargebacks, these solutions are pure breed players. They have dedicated processes, procedures and domain expertise that provide more bandwidth to manage chargeback disputes.
Fraud & Abuse Types
Fraudulent transactions that use compromised payment information, including credit cards and other alternative payment methods.
Unauthorized access to an existing account using compromised information, using that access to make fraudulent purchases, compromise additional information or engage in account abuse.
New Account Fraud
Unauthorized creation of a new account using compromised information, using that account to make fraudulent purchases or engage in account abuse.
Synthetic Identity Fraud
Unauthorized use of real identity data, often different pieces from different individuals, in combination with fake data to create a fabricated identity.
Abuse of promotional offers by circumventing rules and/ore conditions in order to obtain significant discounts.
Abuse of loyalty points to obtain significant discounts or sell stolen loyalty points. This abuse may include account takeover as a means of gaining access and stealing loyalty points.
Abusive or malicious user-generated content. This abuse may include account takeover and/or new account fraud. Spam falls under this type of abuse.
Call Center Fraud
Exploiting call centers as a channel in which to launch fraud attacks, spanning varying forms of fraud and abuse.
KYC & AML
Failure to adhere with established compliance and regulations for specific businesses and industries. Money-laundering leverages legitimate businesses or banks to conceal the origins of illegally obtained finances.
The use of distinctive, measurable human and physiological characteristics to verify an individual’s identity. This type of biometrics includes things like fingerprinting, facial recognition and iris scans.
The analysis of how users behave when interacting with devices and performing a variety of actions. This enables the generation of unique user profiles and provides risking capabilities through out the user session.
The use of two or more layers of authentication to verify a user’s identity. The technology and implementation vary greatly, with some solutions relying heavily on KBA (Knowledge-Based Authentication), while others including advanced layers and applications.
A subset of Artificial Intelligence, Machine Learning has the ability to ingest a large amount of data to detect patterns and anomalies at scale. The models self-learn as data and decisions are continually introduced, often through structured feedback. Machine learning is classified as Supervised or Unsupervised, with the primary differentiator resting in whether the models are trained to make data-driven decisions (Supervised).
Rules leverage algorithms with defined parameters to detect patterns and anomalies. A Rules engine allows for the creation and management of rules. While not self-learning in nature, rules engines have flexibility that enables analysts to test and modify rules.