Navigating KYC Regulatory Changes: Leveraging AI and ML for a Scalable, Efficient, and Risk-Mitigated Program
Discover how to streamline your KYC onboarding process, enhance risk assessment, and bolster your organization's financial crime defenses using AI, ML, and Dow Jones Risk and Management Data. Learn about the benefits of creating a Fusion Center for KYC, Cyber, AML, Crypto, and Fraud teams.
Financial Crimes Solutions for Tier 2 Banks
This webinar discusses the challenges faced by mid-sized banks (Tier-2) in complying with Anti-Money Laundering (AML) regulations. It highlights how new, turnkey Machine Learning (ML) and Artificial Intelligence (AI) technology can help these banks fight fraud while reducing unnecessary investigations (false positives).
Home Insurance demo
Watch our demo on how to improve efficiency and accuracy in detecting fraudulent home insurance claims.
Jetpack for Wealth Screener
Connected Jetpack: An AI-assisted analytics module for navigating complex data and generating actionable insights!
Technology Solutions for Trade Surveillance
During this webinar we provide an in-depth look at the challenges of trade surveillance and how financial institutions can use technology and best practices to protect themselves from financial crimes.
Fighting Financial Crimes with Graph Analytics
This session will focus on how new ML and graph analytics work together with simple deep link visualization to reduce false positives by 60%, increase detection accuracy by 70% and improve overall team transparency and productivity by more than 80% to allow real time alerting to avoid sanctions and fines
2023 Trends in Fraud and AML
During this webinar, our speakers from Expero and Microsoft discuss expected trends in 2023 for Financial Crimes.
Expero CoNNected Financial Crimes
Recent events have created increased focus on Financial Crimes attacks as well as Cyber, AML, and fraud attacks that are growing in sophistication creating losses in the billions.
A Fraud Series - Part Six: Insider Threat Security
An insider threat is a vulnerability of a system resulting from people within the organization. This can be intentional or unintentional: accidental breaches due to negligence or phishing are possible. Using the Connected Toolkit, we can use data from within a company’s system to predict where potential insider threats will occur.
A Fraud Series - Part Five: Cybersecurity Detection and Prevention
Data breaches, which can expose emails, passwords, credit card information among other personally identifiable information, are a constant concern for companies who store client data. Our Connected Toolkit alerts users when suspicious behavior occurs, provides the data to learn from prior breaches, and enables you to predict where fraud will happen next.
Cut Costs with Insurance Fraud Solutions
The focus of this webinar is to identify areas in which Machine Learning, Visualization, and Graph technology can increase the accuracy of claims fraud identification by over 21%, and to show how including 'Human-in-the-loop' can get you ahead of your state's legislation.
A Fraud Series - Part Three: Types of Fraud Identified by a Detection System
It is important to note that as time goes on, fraudsters will continue to adapt to rules and regulations that attempt to prevent them from committing fraud. While supervised detection systems can detect certain types of fraud well, oftentimes analysts don’t immediately know whether new patterns are indicative of fraud or not. This is why it is important to use an unsupervised system that can learn not only from existing patterns, but from new patterns as well.
2022 Trends in Fraud + AML
The focus of this webinar is to highlight Machine Learning, Visualizations, and Graph technology trends in 2022 that will increase the accuracy and output of systems, and how including the ‘Human in the Loop’ can get your teams ahead of potential gaps in your anti-fraud solutions and government AML legislation.
Fight Cyber Crime and Fraud with Graph and ML
During this webinar, Expero and Tigergraph will discuss how new ML and Graph analytics can work together with simple deep link visualization to increase detection accuracy, decrease false positives, and increase transparency between silos to allow real time alerting to avoid sanctions and fines.
Fight Fraud With Graph + ML
During this webinar, TigerGraph and Expero will discuss the complexity and state of AML, and how the roles of Humans, Graph, and Machine Learning combine.
Fight Cyber Crime and Fraud With Graph & ML
During this webinar, TigerGraph and Expero will discuss how to visualize cyber threat information using Graph & ML, and how new technology can help Financial Services team fight cyber fraud.
Financial Services: Fighting AML and Trade Fraud
Get a quick look on how to synchronize the trader desktop and the trade sanctions back office functionality to identify real time issues and avoid sanctions in trades, settlements, AML risk profiles and non-compliance.
Financial Services: Fighting AML and Trade Fraud
This session will focus on how to synchronize the trader desktop and the trade sanctions back office functionality to identify real time issues and avoid sanctions in trades, settlements, AML risk profiles and non-compliance.
Insurance & Claims Fraud with Graph & ML Round Table
The focus of this webinar is to identify areas in which Machine Learning, Visualization, and Graph technology can increase the accuracy of claims fraud identification by over 11%, and to show how including the ‘Human in the Loop’ can get you ahead of your state’s fraud prevention legislation.
Fighting Money Laundering with Advanced Graph Analytics and AI/ML
Tune into TigerGraph and Expero's AML 'Easy' Cooking Show, where Michael Shaler and Scott Heath discuss the state of the world concerning AML, along with other topics such as TigerGraph's unique capability in supporting AML investigations and an AML toolkit demo from Expero.
2021 Trends in Fraud (AML)
The focus of this webinar is to identify Machine Learning, Visualization, and Graph technology trends in 2021 that can increase the accuracy and output of systems, and how including the ‘Human in the Loop’ can get you ahead of AML legislation.
Fraud Toolkit in Medical Healthcare Claims
Get a quick look into the Fraud Toolkit from Expero with this demonstration investigating healthcare claims with machine learning, graph technology, and time series structures. Explore crucial features such as interactive dashboards, the ability to view flagged individuals, visualized connections to risky behavior, and more.
Detecting Fraud with Streaming Data with Imply
The focus of this webinar is to identify how the Imply Technology in conjunction with Machine Learning, Visualization and new technology can directly increase the accuracy and output of systems and how including the ‘Human in the Loop’ can get you ahead of fraud.
Insurance Claims Roundtable With TigerGraph
The focus of this webinar is to identify how Machine Learning, Visualization and new technology like Graph can directly increase the accuracy and shorten process time for ‘Human in the Loop’.
Retail Fraud Round Table with TigerGraph
The focus of this webinar is to identify how Machine Learning, Visualization and new technology can directly increase the accuracy and output of systems and how including the ‘Human in the Loop’ can get you ahead of fraud.
TigerGraph UI ToolKits Financial Crimes
Learn more about how Expero partners with TigerGraph in TigerGraph Toolkits for Financial Crimes, increased visibility & optimization with ER/MD demos, C360 applications, use cases involving the Financial Services industry, and more.
Fraud Detection and Prevention in Healthcare Claims
Fraud and loss affect healthcare payers and providers at a staggering amount each year. This also includes all areas of the business from underwriting to the investigations of claims and payments. In addition, fraud and loss is time consuming to investigate and fraudsters become more sophisticated and utilize more complex methods and technology that make it even harder to detect. The sophistication and pressure from world health events has driven the need for real-time analytics and prevent and intervene strategies.
Deploying Data Products
Building data products in your organization to realize data science ROI and never before seen data insights.
Speed Dating with Cassandra
15 Minute Lightning Talks + Q&A. Powerful Data, Storage & Search & Graph Technology in 1 platform - Cassandra.
Fraud Detection Using ML & Graph
Learn how Graph Technology can help to identify risk and fraud patterns in order to quickly respond to threats and anomalies. Many new fraud rings use sophisticated measures for credit card and other methods of fraud. Utilizing Graph and ML will allow you to see beyond individual data points and uncover difficult-to-detect patterns. Join us to learn how to maximize time and resources with Graph vs. traditional relational database platforms. Predict, Identify, and Intervene Fraud with Graph & ML Analytics.
Fraud Prevention in Financial Services Using Google Cloud Bigtable & Janusgraph
Learn how Google Cloud Bigtable, Pub/Sub, and BigQuery with JanusGraph can help to identify risk and fraud patterns in order to quickly respond. Many new fraud rings use sophisticated measures for credit card and other methods of fraud. Utilizing Google Cloud Platform products and services with JanusGraph will allow you to see beyond individual data points and uncover difficult-to-detect patterns. Join us to learn how to maximize time and resources with Graph.
DataStax Edition: Using Graph Technology to Detect & Prevent Fraud
Learn how DataStax Graph Technology can help to identify risk and fraud patterns in order to quickly respond. Many new fraud rings use sophisticated measures for credit card and other methods of fraud. Utilizing DataStax Graph Technology will allow you to see beyond individual data points and uncover difficult-to-detect patterns. Join us to learn how to maximize time and resources with Graph Technology vs. traditional relational database platforms. If there are new ways to commit fraud these days, shouldn't your company have new ways to prevent it? What You'll Learn Detection and anomaly identification - discuss ROI and time: the value of early detection.Progressive Disclosure - The ability to drill in as items are presented as requiring interaction. Create the ability to allow large data viewing without overwhelming users with millions of data points.Scoring and use of algorithms - The ability to score and create usable information from multiple sources. Creation of scorecards and risk calculations for indicating to users what to spend time on and look at more closely.Visual representation of risks, anomalies, hot spots and heat maps and need for human interaction. Creation of easy to identify visual screens and dashboards for key decision makers that allows for real time diagnostics.
Use Real-time Graph Technology to Detect & Prevent Fraud
Utilizing Graph technology will allow you to see beyond individual data points and uncover difficult-to-detect patterns. Join us to learn how to maximize time and resources with Graph technology vs. traditional relational database platforms.
Use Real-time Graph Technology to Detect and Prevent Fraud
Learn how Graph Technology can help to identify risk and fraud patterns in order to quickly respond. Many new fraud rings use sophisticated measures for credit card and other methods of fraud. Utilizing Graph technology will allow you to see beyond individual data points and uncover difficult-to-detect patterns. Join us to learn how to maximize time and resources with Graph technology vs. traditional relational database platforms.