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Guardian Analytics

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  • Real-time CDD/EDD Risk Scoring & Identity Verification
    Real-time CDD/EDD Risk Scoring & Identity Verification
    Guardian Analytics and Alloy Recorded: Mar 28 2019 40 mins
    De-Risking Customer Onboarding is a challenge, current legacy tools are inflexible leading to very long onboarding time and a lot of tedious manual processes. Guardian Analytics modern AML CDD/EDD and Alloy real-time identity verification bring leading-edge technologies to:

    - Automatically check a customer’s background against various databases and sanction lists
    - Simplify the onboarding process
    - Helps banks respond faster to any changes in regulatory laws
  • Seamless Upgrade to a Modern AML Platform: Star One Credit Union Testimonial
    Seamless Upgrade to a Modern AML Platform: Star One Credit Union Testimonial
    Lynn Brubaker VP Star One Credit Union, Eric Tran-Le Vice President of Product Management Guardian Analytics Recorded: Jan 31 2019 31 mins
    Banking regulators encourage financial institutions to explore modern technologies to reduce significantly false alerts, investigation time and operating costs.

    Star One Credit Union VP Lynn Brubaker, BSA Officer, will walk through the key considerations to modernize their current AML system with Guardian Analytics Modern AML EvidenceLake™ Platform.

    Join our webinar, and you will learn how to:

    • Significantly reduce the number of alerts false positives
    • Speed up your investigation time by 200%
    • Substantially reduce your AML Operating Costs
  • Fighting Faster Payments Fraud With Machine Learning
    Fighting Faster Payments Fraud With Machine Learning
    Eric Tran-Le, VP of Product Management, Wendy Xue, Director of Product Management, at Guardian Analytics Recorded: Jan 23 2019 43 mins
    Fraud follows speed. Faster payments leave no time for manual review of transactions and no room for high false positives. Learn how machine learning based fraud detection can mitigate fraud in real-time with low false positives, ensure positive customer experiences, and transform fraud operations from loss-recovery to loss-prevention.
  • Real-time Digital Banking Fraud Detection
    Real-time Digital Banking Fraud Detection
    Eric Tran-Le, VP, Product Management, Guardian Analytics Recorded: Nov 27 2018 31 mins
    "A stolen account credential cost less than $25 on the darknet, you can even have a bundle for $35 with the associated social security number" Source: Darknet

    Guardian Analytics Fraud Intelligence research on our customer’s Digital Banking accounts activities shows:

    • Over 20% of Online & Mobile events are IP geolocation changes related
    • Over 30% of Online & Mobile events are associated with money transfers via Wire or ACH

    Here are some key challenges:
    • A user can have multiple IP address depending on their home router, office proxy, traveling hotspot location…
    • Should you detect suspicious Online and Mobile events?
    • Should you detect the subsequent suspicious money transfer activities resulting from suspicious Online and Mobile events?
    • Do both?
    • Should you block an IP address coming from an infected device?

    Guardian Analytics machine learning and fraud behavioral analytics risk engine monitors in real-time hundreds of digital banking fraud risk indicators from anomalous login behavior including time of day, day of week, IP address change velocity, to device fingerprinting and configuration changes, wire recipient unusual changes, ACH recipient unusual changes, malware detected on devices…
    and calculate a real time risk score for every digital banking user enabling Financial Institutions to detect digital banking suspicious activities.

    Benefits:

    • Detect suspicious digital banking activities in real-time
    • Detection unusual digital banking related ACH and Wire money transfers
    • Enables real-time intervention on payment channel to avoid illicit funds transfers
    • Increase operational efficiency by focusing on the highest risk transactions and reducing callbacks
    • Enhance compliance by meeting FFIEC guidelines for anomaly detection
  • Increase Your Operational Efficiency & Fraud Intelligence with Fraud Analytics
    Increase Your Operational Efficiency & Fraud Intelligence with Fraud Analytics
    Eric Tran Le, VP of Product Management Recorded: Oct 11 2018 41 mins
    Guardian Analytics Fraud Analytics provides a single place where Fraud Managers and Business Intelligence users can collaborate on Alert, Case Risk Analytics combined with User Activity and Location Analytics cross Payment Channels.
    This webinar will showcase how easy it is to interact with powerful dashboards built with your favorite office productivity tools. We will do a walk-thru of the following features:
    -Alert & Case Analytics Operational KPIs
    -Activity Analytics Dashboard
    -Location Analytics Dashboard
    -User Account Fraud Intelligence Dashboard
  • Seamless Upgrade to a Modern AML Platform: Star One Credit Union Testimonial
    Seamless Upgrade to a Modern AML Platform: Star One Credit Union Testimonial
    Lynn Brubaker VP Star One Credit Union, Eric Tran-Le Vice President of Product Management Guardian Analytics Recorded: Sep 27 2018 32 mins
    Star One Credit Union VP Lynn Brubaker will describe the key considerations to modernize their current AML system to Guardian Analytics Modern Evidence Lake Platform. Guardian Analytics will present the seamless upgrade path and the key benefits gained on 4 core AML transaction monitoring flows:
    - AML Rule Initialization
    - Detection to Alert
    - Alert to Investigation
    - Investigation to SAR Filing
  • How to Comply with the New FinCEN Beneficial Ownership Rule
    How to Comply with the New FinCEN Beneficial Ownership Rule
    Ranay Allred, Former Asst. BSA/AML Compliance Officer & Matthew Lau, CAMS, AML Product Mngr, Guardian Analytics Recorded: Jul 25 2018 24 mins
    With the new FinCEN CDD rule in effect as of May 11th, 2018, financial institutions must now to identify and verify the identity of the beneficial owners of legal entity customers who own, control, and profit from companies, when those companies open accounts. This webinar will describe the impact of new rule and explain the different ways to comply with FinCEN's ruling, including how to define, collect, and monitor beneficial ownership accounts.
  • How to Prevent Peer-to-Peer (P2P) Payment Fraud in Real-Time
    How to Prevent Peer-to-Peer (P2P) Payment Fraud in Real-Time
    Eric Tran-Le, Vice President of Product Management, Shirley Inscoe, Senior Analyst at Aite Group Recorded: Jun 28 2018 50 mins
    Guardian Analytics and Aite Research Group will describe the different types of real-time payments in digital banking from online bill pay to emerging P2P payments and explain why machine learning and behavioral analytics are needed to prevent fraud in real-time
  • Detect ACH Payroll Fraud in Real-time
    Detect ACH Payroll Fraud in Real-time
    Eric Tran-Le, VP, Product Management, Guardian Analytics Recorded: May 8 2018 23 mins
    Payroll hacks are common and they are difficult for banks to detect and prevent. From Business Email Compromise (BEC) to Payee Edit Fraud, fraudsters do not create new batch or transaction but rather modify the recipient number of an existing ACH batch. According to ACFE survey it takes almost 2 years to detect a payroll fraud. With Guardian Analytics machine learning and behavioral analytics fraud detection you can detect ACH fraud on payroll systems as they come and trigger real-time intervention to hold or reject suspicious ACH payroll transactions.
  • How to Detect Wire Fraud with Machine Learning and Behavioral Analytics
    How to Detect Wire Fraud with Machine Learning and Behavioral Analytics
    Eric Tran-Le, VP, Product Management, Guardian Analytics Recorded: Apr 23 2018 34 mins
    This webinar is part one of the Wire Webinar Series. We will be discussing how you can leverage Guardian Analytics behavior-based, real-time wire fraud detection solution to monitor all activities and transactions for each account holder allowing you to build a profile of each user’s typical behavior. Tracked activities include hundreds of elements from payment amounts, wire originators and recipients, plus online login, session duration, sequence of activities during each session.

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