PRODUCT

Product Descriptions

The information below contains a list of the BioCatch offerings and a description of each. BioCatch may modify these offerings and descriptions at its discretion.

AO fraud detection with basic data support

BioCatch account opening fraud detection product provides protection for web and mobile online customer onboarding processes. The solution tracks user interactions , device and network attributes within web and mobile platforms and uses machine learning and heuristics to model both genuine users and criminal behavior to deliver an accurate risk score. The following components are included:

BioCatch Web and Mobile SDKs: Enable data collection from web and mobile browsers, and Android and iOS apps, respectively. Embedding the SDKs into the website/mobile application allows the behavioral parameters and device and network data to be collected and sent to BioCatch servers for user profiling and risk assessment;
BioCatch API: Generates calls from Subscriber’s server to BioCatch servers. At designated points in the application where a risk score is desired, a call is made to BioCatch via the API, upon which BioCatch responds with the risk score back to the Subscriber’s server; and
Analyst Station: Front-end component for off-line analysis of user sessions and fraud data. Allows analysts to view risky sessions, conduct queries, generate reports and more.

AO fraud detection with advanced data support

Biocatch account opening fraud detection product provides protection for web and mobile online customer onboarding processes. The solution tracks user interactions , device and network attributes within web and mobile platforms and uses machine learning and heuristics to model both genuine users and criminal behavior to deliver an accurate risk score. The following components are included:

BioCatch Web and Mobile SDKs: Enable data collection from web and mobile browsers, and Android and iOS apps, respectively. Embedding the SDKs into the website/mobile application allows the behavioral parameters and device and network data to be collected and sent to BioCatch servers for user profiling and risk assessment;
BioCatch API: Generates calls from Subscriber’s server to BioCatch servers. At designated points in the application where a risk score is desired, a call is made to BioCatch via the API, upon which BioCatch responds with the risk score back to the Subscriber’s server; and
Analyst Station: Front-end component for off-line analysis of user sessions and fraud data. Allows analysts to view risky sessions, conduct queries, generate reports and more.
Data points
Risk and genuine factors
Data sharing via Snowflake

Analysis of behavioral age of user

The BioCatch Age Analysis solution extracts physical, cognitive, and other age-related characteristics as the user naturally interacts with the account opening application. By continuously monitoring an account opening session, the BioCatch age analysis solution predicts the user’s approximate behavioral age and compares it to the declared age on the application. In the event anomalies are surfaced, the BioCatch risk score will be impacted accordingly.

Workflow features with Rule Manager and Case Manager for AO

Using the BioCatch Rule Manager, fraud teams can build rules using BioCatch insights, such as risk score and leading Indicators, in order to trigger a desired outcome with exceptional flexibility and ease. The rule manager allows to configure real-time policy, score, and alert actions. The BioCatch Rule Manager empowers organizations to mitigate risk in real time, improve customer experience, and simplify back-end fraud operations by providing the ability to configure actions based on risk level.

ATO fraud detection with basic data support

BioCatch account takeover fraud detection product provides protection for web and mobile online account applications The solution generates advanced behavioral insights to provide you with the continuous, real-time visibility you need to detect more fraud, increase trust, and improve customer experience in your digital channels. BioCatch risk models leverage innovative research and a decade of data to analyze a user’s physical and cognitive digital behavior and continuously monitor web and mobile sessions to distinguish between genuine users and criminals, whether human or automated attacks such as bots, or Remote Access Tools (RAT).By profiling user behaviors such as mouse movements, typing cadence, swipe patterns or device orientation, the BioCatch platform identifies statistically observed norms for “good” and “bad” behavior. Powered by machine learning, the platform comapres users against their historical profiles and generates a risk score. The following components are included:

BioCatch Web and Mobile SDKs: Enable data collection from web and mobile browsers, and Android and iOS apps, respectively. Embedding the SDKs into the website/mobile application allows the behavioral parameters and device and network data to be collected and sent to BioCatch servers for user profiling and risk assessment;
BioCatch API: Generates calls from Subscriber’s server to BioCatch servers. At designated points in the application where a risk score is desired, a call is made to BioCatch via the API, upon which BioCatch responds with the risk score back to the Subscriber’s server; and
Analyst Station: Front-end component for off-line analysis of user sessions and fraud data. Allows analysts to view risky sessions, conduct queries, generate reports and more.

ATO fraud detection with advanced data support

BioCatch account takeover fraud detection product provides protection for web and mobile online account applications The solution generates advanced behavioral insights to provide you with the continuous, real-time visibility you need to detect more fraud, increase trust, and improve customer experience in your digital channels. BioCatch risk models leverage innovative research and a decade of data to analyze a user’s physical and cognitive digital behavior and continuously monitor web and mobile sessions to distinguish between genuine users and criminals, whether human or automated attacks such as bots, or Remote Access Tools (RAT). By profiling user behaviors such as mouse movements, typing cadence, swipe patterns or device orientation, the BioCatch platform identifies statistically observed norms for “good” and “bad” behavior. Powered by machine learning, the platform compares users against their historical profiles and generates a risk score. The following components are included:

BioCatch Web and Mobile SDKs: Enable data collection from web and mobile browsers, and Android and iOS apps, respectively. Embedding the SDKs into the website/mobile application allows the behavioral parameters and device and network data to be collected and sent to BioCatch servers for user profiling and risk assessment.
BioCatch API: Generates calls from Subscriber’s server to BioCatch servers. At designated points in the application where a risk score is desired, a call is made to BioCatch via the API, upon which BioCatch responds with the risk score back to the Subscriber’s server; and
Analyst Station: Front-end component for off-line analysis of user sessions and fraud data. Allows analysts to view risky sessions, conduct queries, generate reports and more.
Data points
Risk and genuine factors
Data sharing via Snowflake

Workflow features with Rule Manager for ATO

Using the BioCatch Rule Manager, fraud teams can build rules using BioCatch insights such as risk score and leading indicators in order to trigger a desired outcome with exceptional flexibility and ease. The Rule Manager allows to configure real-time policy, score, and alert actions. The BioCatch Rule Manager empowers organizations to mitigate risk in real time, improve customer experience, and simplify back-end fraud operations by providing the ability to configure actions based on risk level.

ATO fraud detection for a second channel (mobile or web)

BioCatch account takeover fraud detection product provides protection for web and mobile online account applications The solution generates advanced behavioral insights to provide you with the continuous, real-time visibility you need to detect more fraud, increase trust, and improve customer experience in your digital channels. BioCatch risk models leverage innovative research and a decade of data to analyze a user’s physical and cognitive digital behavior and continuously monitor web and mobile sessions to distinguish between genuine users and criminals, whether human or automated attacks such as bots, or Remote Access Tools (RAT).By profiling user behaviors such as mouse movements, typing cadence, swipe patterns or device orientation, the BioCatch platform identifies statistically observed norms for “good” and “bad” behavior. Powered by machine learning, the platform compares users against their historical profiles and generates a risk score. The following components are included:

BioCatch Web and Mobile SDKs: Enable data collection from web and mobile browsers, and Android and iOS apps, respectively. Embedding the SDKs into the website/mobile application allows the behavioral parameters and device and network data to be collected and sent to BioCatch servers for user profiling and risk assessment;
BioCatch API: Generates calls from Subscriber’s server to BioCatch servers. At designated points in the application where a risk score is desired, a call is made to BioCatch via the API, upon which BioCatch responds with the risk score back to the Subscriber’s server; and
Analyst Station: Front-end component for off-line analysis of user sessions and fraud data. Allows analysts to view risky sessions, conduct queries, generate reports and more.

Phishing Site Detection Next-Day Report

BioCatch’s Phishing Site Detection informs customers of lookalike sites intended to attack institutions and their customers. Each day the customer will obtain a report listing the phishing sites detected the previous day so that the customer can take actions to have the site taken down. Phishing Site Detection can accommodate different applications and user journeys and collect data from pages such as home pages, login pages and user/account reset pages.

Phishing Site Detection Sale Day Alerting

BioCatch’s Phishing Site Detection informs customers in real-time about the creation of lookalike sites intended to attack institutions and their customers. As these sites are identified, the solution sends a real-time alert of the phishing site so that the customer can take immediate action to have the site taken down. Phishing Site Detection can accommodate different applications and user journeys and collect data from pages such as home pages, login pages and user/account reset pages.

Victims of Phishing Sites List

The BioCatch Site Detection Victims of Phishing Sites List. Through the collection of data that can be linked to a known user, this solution sends victim reports within 24 hours indicating which customers have entered their sensitive details into the lookalike site, so that the organization can take prescriptive actions to protect their customers.

Voice Scams fraud detection with basic data support

BioCatch's voice scam fraud detection product analyzes user and device behavior in real-time to detect when an individual is conducting a transaction under the influence of a cybercriminal, helping banks to protect customers from voice social engineering scams and authorized push payment fraud. Powered by machine learning, the platform generates a voice scam risk score. The following components are included:

BioCatch Web and Mobile SDKs: Enable data collection from web and mobile browsers, and Android and iOS apps, respectively. Embedding the SDKs into the website/mobile application allows the behavioral parameters and device and network data to be collected and sent to BioCatch servers for user profiling and risk assessment;
BioCatch API: Generates calls from Subscriber’s server to BioCatch servers. At designated points in the application where a risk score is desired, a call is made to BioCatch via the API, upon which BioCatch responds with the risk score back to the Subscriber’s server; and
Analyst Station: Front-end component for off-line analysis of user sessions and fraud data. Allows analysts to view risky sessions, conduct queries, generate reports and more.

Voice Scams fraud detection with advanced data support

BioCatch's Voice Scam fraud detection product analyzes user and device behavior in real-time to detect when an individual is conducting a transaction under the influence of a cybercriminal, helping banks to protect customers from voice social engineering scams and authorized push payment fraud. Powered by machine learning, the platform generates a voice scam risk score. The following components are included:

BioCatch Web and Mobile SDKs: Enable data collection from web and mobile browsers, and Android and iOS apps, respectively. Embedding the SDKs into the website/mobile application allows the behavioral parameters and device and network data to be collected and sent to BioCatch servers for user profiling and risk assessment;
BioCatch API: Generates calls from Subscriber’s server to BioCatch servers. At designated points in the application where a risk score is desired, a call is made to BioCatch via the API, upon which BioCatch responds with the risk score back to the Subscriber’s server; and
Analyst Station: Front-end component for off-line analysis of user sessions and fraud data. Allows analysts to view risky sessions, conduct queries, generate reports and more.
Data points
Risk and genuine factors
Data sharing via Snowflake

Workflow features with Rule Manager and Case Manager for Voice Scams

Using the BioCatch Rule Manager, fraud teams can build rules using BioCatch insights such as risk score and leading indicators in order to trigger a desired outcome with exceptional flexibility and ease. The Rule Manager allows to configure real-time policy, score, and alert actions. The BioCatch Rule Manager empowers organizations to mitigate risk in real-time, improve customer experience, and simplify back-end fraud operations by providing the ability to configure actions based on risk level.

Voice Scams fraud detection for a second channel (mobile or web)

BioCatch Web and Mobile SDKs: Enable data collection from web and mobile browsers, and Android and iOS apps, respectively. Embedding the SDKs into the website/mobile application allows the behavioral parameters and device and network data to be collected and sent to BioCatch servers for user profiling and risk assessment;
BioCatch API: Generates calls from Subscriber’s server to BioCatch servers. At designated points in the application where a risk score is desired, a call is made to BioCatch via the API, upon which BioCatch responds with the risk score back to the Subscriber’s server; and
Analyst Station: Front-end component for off-line analysis of user sessions and fraud data. Allows analysts to view risky sessions, conduct queries, generate reports and more.

Mule Account Detection with basic data support

BioCatch Mule Account Detection identifies mule activity within new and existing accounts to help you mitigate financial, reputational, and regulatory risk. The following components are included:

BioCatch Web and Mobile SDKs: Enable data collection from web and mobile browsers, and Android and iOS apps, respectively. Embedding the SDKs into the website/mobile application allows the behavioral parameters and device and network data to be collected and sent to BioCatch servers for user profiling and risk assessment;
BioCatch API: Generates calls from Subscriber’s server to BioCatch servers. At designated points in the application where mule account detection is desired, a call is made to BioCatch via the API, upon which BioCatch responds with whether the account in suspected to be a mule or not back to the Subscriber’s server;

Workflow features with Rule Manager for Mules

Using the BioCatch Rule Manager, fraud teams can build rules using BioCatch insights such as risk score and leading indicators in order to trigger a desired outcome with exceptional flexibility and ease. The Rule Manager allows to configure real-time policy, score, and alert actions. The BioCatch Rule Manager empowers organizations to mitigate risk in real-time, improve customer experience, and simplify back-end fraud operations by providing the ability to configure actions based on risk level.

Secure Customer Authentication with basic data support

BioCatch analyzes behavioral, device, and network attributes to conduct One-Time-Passcode (OTP) profiling and offers a layer of entry of familiar information to protect the Strong Customer Authentication flow under PSD2.

Insights Query Engine

BioCatch Data Sharing provides the ability to import data that was collected or evaluated by BioCatch from your environment for risk assessment modeling. Currently, this offering uses Snowflake’s multi-cluster shared data architecture to access your information. There are two ways to access this service offering:

Insights Query Engine Customer Account: Gaining access of the BioCatch shared data from your own Snowflake account, which is a feature included with Advanced Data Support for your ATO, AO, Mule Account Detection, or Social Engineering Voice Scams, or
Insights Query Engine Reader Account: Accessing the shared data through a BioCatch reader accounts, which requires an annual agreement with BioCatch.

Support and Professional Services

BioCatch offers two levels of support:

Basic Support Services: The basic support service comes with your license and provides integration support and 24x7 technical support which is enough to get you started and realize the value of the solution.
Premium Support Services: Premium support services, the preferred and most comprehensive service program, optimizes your BioCatch experience and takes full advantage of the platform, best practices, and industry expertise.

For additional information on the features and requirements for Basic and Advanced Support and Professional Services, you can find a Data Sheet listing these details on the BioCatch Resources Page at www.biocatch.com.

The information below contains a list of the BioCatch offerings and a description of each. BioCatch may modify these offerings and descriptions at its discretion.

Connect Platform:

BioCatch Connect provides the essential foundation for collecting, validating, and analyzing behavioral, device, network, transactional and application signals from online user sessions which feed the BioCatch modules. The platform includes a comprehensive and expanding suite of research, investigation and analytics tools that deliver actionable insights to fraud, financial crime, and fusion teams. The following components are included within BioCatch Connect:

API and Integration:
- Platform Integration: BioCatch provides a comprehensive, tailored, and seamless implementation of the BioCatch Connect Platform. This assures that the solution is tuned to the uniqueness of each customer and maximizes performance and customer confidence.
- BioCatch API: The API generates calls from the Subscriber’s server to BioCatch servers. At designated points in the application where a risk score is desired, a call is made to BioCatch via the API, upon which BioCatch responds back to the Subscriber’s server with a risk score and additional contextual information for the specific solution.
- BioCatch Web and Mobile SDKs: SDKs Enable data collection from web and mobile browsers, and Android and iOS apps, respectively. Embedding the SDKs into the website/mobile application allows for online user behavior, device and network data to be collected and sent to BioCatch servers for user profiling, as applicable, and risk assessment.
Tools and Applications:
- Analyst Station: The Analyst Station is a tool for off-line analysis of user sessions and fraud data. It allows analysts to view risky sessions, conduct queries, and generate reports.
- BioCatch Rule Manager: Fraud teams can build and simulate rules using contextual data, such as data points, risk score, and leading Indicators, to trigger a desired outcome. The Rule Manager allows for configuration of real-time policy, score, and alert actions.
- Fraud File Uploader: A feedback file from the customer listing fraud/genuine sessions post investigation, can be uploaded via the BioCatch Fraud File Uploader.
- Truth Marking API: The Truth Marking API allows organizations to automate the transfer of fraud investigation results from independent back-office systems to BioCatch, ensuring feedback is seamlessly sent whenever a session is marked as fraudulent or genuine.
- Insights Query Engine: BioCatch provides customers with the ability to view/query their user session data that was evaluated by BioCatch. This offering uses Snowflake’s multi-cluster shared data architecture. You can access this service offering either from your own Snowflake account or through a BioCatch reader account.

Connect Support Services: BioCatch support provides the most comprehensive service program to optimize the experience and take full advantage of the solution, best practices, and industry expertise. Components of Connect support include solution integration, product training, enablement, and business reviews. Additional information on Connect Support Services can be found on the BioCatch Support and Professional Services Data Sheet on the BioCatch Resources Page at www.biocatch.com.

Account Opening Fraud Protection (AO):

BioCatch Account Opening Protection provides risk assessment for new account fraud in online origination. The solution tracks online user interactions, device, network, and behavioral attributes, and uses machine learning and heuristics to model both genuine and criminal behavior to deliver an accurate risk assessment in the form of a risk score and other contextual/supportive data. The following components are included:

AO Model: The AO model aims to detect new account fraud in online originations. The model looks for, among other things, signs of low data familiarity when an applicant is entering information on an online form to apply for a new account. It considers how fluent or not the applicant is with the account opening flow. It looks for expert keyboard usage patterns. In addition, when enabled, it can assess if an applicant’s typing pattern is inconsistent with their declared year of birth.
AO Risk Score: The AO Risk Score is produced by the AO model and predicts the risk of new account fraud. It ranges between 0 and 1,000 with higher scores indicating higher risk.
BioCatch Web and Mobile SDKs: SDKs enable data collection from web and mobile browsers, and Android and iOS apps, respectively. Embedding the SDKs into the website/mobile application allows for online user behavior, device, and network data to be collected and sent to BioCatch servers for risk assessment.
BioCatch API: The API generates calls from the Subscriber’s server to BioCatch servers. At designated points in the application where a risk score is desired, a call is made to BioCatch via the API, upon which BioCatch responds with the risk score and other contextual/supportive data back to the Subscriber’s server.
Risk and Genuine Factors output: In addition to the risk score, BioCatch provides an extra layer of detail, including Risk Factors (attributes that indicate risk) and Genuine Factors (attributes that indicate genuine behavior).
Data Points: Customers can also access additional behavioral device information in their API response, beyond scores or Boolean indicators like risk and genuine factors, including data collected or analyzed during the session.

Push API: The push API allows customers to receive notifications from the BioCatch server. These notifications are triggered by pre-configured conditions, via a score or policy, that are defined in the BioCatch Rule Manager. The customer can create an automated decisioning strategy for the push API calls on their side.

Threat Indicators: Another layer of detail that can accompany the BioCatch risk score are Threat Indicators. These are separate values in the API response to identify threats such as bots, emulators, etc.
Age Analysis: BioCatch Age Analysis considers physical, cognitive, and other age-related characteristics as the user interacts with the account opening experience online and predicts the user’s approximate behavioral age and compares it to the declared age on the application. A significant discrepancy between the two bolsters the fraud risk assessment at account opening.
Analyst Station: The Analyst Station is a tool for off-line analysis of user sessions and fraud data. It allows analysts to view risky sessions, conduct queries, and generate reports.
BioCatch Rule Manager: Fraud teams can build and simulate rules using contextual data, such as data points, risk score, and leading Indicators, to trigger a desired outcome. The Rule Manager allows for configuration of real-time policy, score, and alert actions.
Truth Marking API: The Truth Marking API allows organizations to automate the transfer of fraud investigation results from independent back-office systems to BioCatch, ensuring feedback is seamlessly sent whenever a session is marked as fraudulent or genuine.
Fraud File Uploader: A feedback file from the customer listing fraud/genuine sessions post investigation, can be uploaded via the BioCatch Fraud File Uploader.
Insights Query Engine: BioCatch provides customers with the ability to view/query their account opening session that was evaluated by BioCatch. This offering uses Snowflake’s multi-cluster shared data architecture. You can access this service either from your own Snowflake account or through a BioCatch reader account.

Support Services: BioCatch support provides the most comprehensive service program to optimize the experience and take full advantage of the solution, best practices, and industry expertise. Components of Connect support include solution integration, product training, enablement, and business reviews. Additionally, BioCatch provides solution support comprising of a team of dedicated professionals. Some of these additional support capabilities are model training and calibration, urgent fraud request support, assistance in model governance, and ad hoc reporting. Additional information on Threat Analytics services can be found on the BioCatch Support and Professional Services Data Sheet on the BioCatch Resources Page at www.biocatch.com.

Account Takeover Protection (ATO):

BioCatch Account Takeover Protection delivers risk assessments for online account takeovers and the resulting unauthorized transactions across web and mobile channels. The solution generates a risk score along with factors that provide advanced behavioral intelligence while monitoring user behavior in real-time. The solution output can be used to detect ATO fraud, increase trust, and improve customer experience in your digital channels. The following components are included:

ATO Model: The ATO model aims to detect Account Takeover fraud, while analyzing device, network, and behavioral data alongside detailed user profiles built from online banking interactions. The model identifies behavioral anomalies comparing current session behaviors with those expected from the user profile. Additionally, customers can pass on contextual information via an API request to BioCatch. This multilayered approach, powered by machine learning, minimizes false positives while maximizing accurate fraud detection, ensuring reliable and effective security against the risk of account takeover.
ATO Risk Score: BioCatch’s risk engine dynamically compares data obtained from an active session against the user’s profile, genuine population, and fraud population to calculate an accurate risk score (between 0 – 1,000) which can be used to determine the likelihood of ATO fraud.
Profiles: A comprehensive behavioral profile for every user is developed over time to compare against current session data to distinguish between genuine and fraudulent activity. These profiles form the baseline for ATO detection but do change over time as the genuine user attributes change. BioCatch analyzes more than 2,000 behavioral, cognitive, and device attributes to recognize the typicality of every user.
Risk and Genuine Factors Output: BioCatch provides additional information about user behaviors and factors observed during the session providing an extra layer of detail along with the risk score. These factors are categorized as Risk (potentially risky) and Genuine (aligned with genuine activity) Factors.

Data Points: Customers can also access additional behavioral device information in their API response, beyond scores or Boolean indicators like risk and genuine factors, including data collected or analyzed during the session.
Threat Indicators: Another layer of detail that can accompany the BioCatch risk score are Threat Indicators. These are separate values in the API response to identify threats such as bots, emulators, etc.
Model Support Services: As part of your contract, BioCatch provides solution model support comprising of a team of dedicated professionals. Some of the support capabilities are, but not limited to, model calibration, urgent fraud request support, assistance in model governance, and ad hoc reporting. Additional information on threat analytics services for Account Takeover Protection can be found on the Services Data Sheet on the BioCatch Resources Page at www.biocatch.com.

Social Engineering Scams Detection (Scams)

BioCatch's Social Engineering Scam Detection product analyzes online (web or mobile) user behavior and device information in real-time to provide an assessment of whether the user is being scammed to make a payment, often called an Authorized Push Payment (APP). The solution analyzes user behaviors like hesitation, distraction, frustration, confusion, duress and such in conjunction with contextual information passed on via an API request to BioCatch. This multi-layered approach, powered by machine learning, minimizes false positives while maximizing accurate scam detection. The solution generates a scam risk score along with other factors described below. The following components are included:

Scam Model: The Scam model aims to accurately detect scenarios where the genuine user is being coerced by a cybercriminal to send out a payment. By analyzing unique device, network, and user behavioral data, and comparing those with detailed user profiles built from online banking interactions, the model identifies behavioral anomalies and the risk of a scam. This unique approach maximizes accurate scam detection protecting both the customer from losing money and the bank from investigations and potential reimbursements.
Scam Risk Score: BioCatch’s machine learning model dynamically compares data obtained from an active session against the user profile, genuine population, and fraud population to calculate a highly accurate scams risk score (between 0 – 1,000) which can be used in determining the likelihood of a genuine user being under the influence of a scam.
Profiles: A comprehensive behavioral profile for every user is developed over time to compare against current session data to distinguish between genuine and fraudulent activity. These profiles help distinguish from changes in behavior and actions when a user is under the influence of a cybercriminal. BioCatch analyzes more than 2,000 behavioral, cognitive, and device attributes to recognize the typicality of every user and compare those to session activity to protect the user from being scammed.
Risk and Genuine Factors Output: BioCatch provides additional information about user behaviors and factors observed during the session providing an extra layer of detail along with the risk score. These factors are categorized as Risk (potentially risky) and Genuine (aligned with genuine activity) Factors.
Data Points: Customers can also access additional behavioral device information in their API response, beyond scores or Boolean indicators like risk and genuine factors, including data collected or analyzed during the session.
Threat Indicators: Another layer of detail that can accompany the BioCatch risk score are Threat Indicators. These are separate values in the API response to identify threats such as bots, etc.
Model Support Services: As part of your contract, BioCatch provides solution model support comprising of a team of dedicated professionals. Some of the support capabilities are, but not limited to, model calibration, urgent fraud request support, assistance in model governance, and ad hoc reporting. Additional information on threat analytics services for Social Engineering Scams Detection can be found on the Services Data Sheeton the BioCatch Resources Page at biocatch.com.

Mule Account Detection (Mules)

BioCatch's Mule Account Detection (Mules) solution identifies accounts at high risk of being a mule or that have been taken over to be used for the purpose of money laundering. This solution analyzes activity in recently opened and existing accounts to help stop the use of bank accounts for money laundering and mitigate financial, reputational, and regulatory risk. Powered by proprietary technologies, the following components are included:

Mules Model: The mules model aims to accurately detect accounts that are at risk of being used as a mule to launder money. By analyzing unique device, network, session activity, and behavioral data, and comparing this against money mule behaviors, the model can identify the severity or risk of an account being used for laundering funds. This uniquely helps to identify risky accounts before funds are received or sent through said account, saving fraud losses, operational expenses and bolstering defenses against money laundering activity.
Mules Risk Score: BioCatch’s risk engine dynamically compares data obtained from an active session against the user profile, genuine population, and mule population to calculate a highly accurate mules risk score (between 0 – 1,000). The risk score can be used in determining the likelihood of an account being used as a mule to launder money.
Profiles: A comprehensive behavioral profile for every user is developed over time to compare against current session data against money mule behaviors to distinguish between genuine and mule activity. These profiles help distinguish changes in behavior and actions when user activity strays from their user profile. BioCatch analyzes more than 2,000 behavioral, cognitive, and device attributes to recognize the typicality of every user and compare it to session activity to help prevent use of the account to launder money.
Risk and Genuine Factors Output: BioCatch provides additional information about user behaviors and factors observed during the session providing an extra layer of detail along with the risk score. These factors are categorized as Risk (potentially risky) and Genuine (aligned with genuine activity) F
Data Points: Customers can also access additional behavioral device information in their API response, beyond scores or Boolean indicators like risk and genuine factors, including data collected or analyzed during the session.
Threat Indicators: Another layer of detail that can accompany the BioCatch risk score are Threat Indicators. These are separate values in the API response to identify threats such as bots, etc.

Model Support Services: As part of your contract, BioCatch provides solution model support comprising of a team of dedicated professionals. Some of the support capabilities are, but not limited to, model calibration, urgent fraud request support, assistance in model governance, and ad hoc reporting. Additional information on threat analytics services for Social Engineering Scams Detection can be found on the Services Data Sheet on the BioCatch Resources Page at www.biocatch.com.

Inherence Analysis for the 3D-Secure Channel (SCA Solution)

BioCatch’s SCA solution helps FIs enhance their existing compliant, multi-factor payment flows by analyzing how OTPs and personal data are entered to detect more payment fraud and stop the transaction going through. Depending on risk appetite, up to nine layers of security can be applied to the inherence check. The solution can also support a possession factor through BioCatch’s advanced device persistency. The solution generates a scam risk score along with other factors that are described below. The following components are included:

SCA Model:This model strengthens two factor authentication by verifying that it’s the genuine user entering the sensitive data. In addition to analysis of the OTP entry, users are prompted to enter a piece of personal information stored in their long-term memory - making it harder for fraudsters to replicate. By analyzing how both inputs are entered, the model detects behavioral anomalies and assesses payment risk. This approach enhances existing multi-factor, SCA-compliant flows, giving fraud teams greater confidence in user authentication.
SCA Risk Score: BioCatch’s risk engine dynamically compares data obtained from an active session against several factors such as a user profiles and typical criminal behavior patterns to calculate an accurate risk score (between 0 – 1,000) which can be used to determine the likelihood of payment fraud.
Profiles: A comprehensive behavioral profile for every user is developed over time to compare against current session data to distinguish between genuine and fraudulent activity. These profiles help distinguish the changes in behavior and actions when it’s not the typical user trying to go through the steps to make a payment. A comprehensive behavioral profile for every user can also be leveraged from existing ATO profiles to expedite profile creation.
Risk and Genuine Factors Output: Available through Analyst Station, BioCatch provides deeper insight into session activity by highlighting behavioral patterns observed during the user journey. These are categorized as either Risk Factors (indicative of suspicious activity) or Genuine Factors (aligned with legitimate behavior), offering valuable further context.
Data Points: Depending on the institution’s risk appetite, multiple layers can be configured into the inherence check, such as OTP entry patterns, memory field behavior, device and network intelligence, behavioral profiling, and transaction data (e.g. merchant, amount, currency). These data points are accessible within Analyst Station.
Threat Indicators: To support deeper investigation, Threat Indicators can be explored via Analyst These highlight specific threat types observed during a session - such as bots, remote access tools, or emulator usage, and provide an additional dimension to the risk score output. These are visible in Analyst Station.

Model Support Services: As part of your contract, BioCatch provides solution model support comprising a team of dedicated professionals. Some of the support capabilities are, but not limited to, model calibration and enhancement, urgent fraud request support, assistance in model governance, and ad hoc reporting. Additional information on threat analytics services for can be found on the Services Data Sheet on the BioCatch Resources Page at www.biocatch.com.

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