Explore our Financial Crimes Insights

Fight Fraud with GenAI & Graph Tech: Webinar for Insurance Claims

Connected Jetpack: An AI-assisted analytics module for navigating complex data and generating actionable insights!

Explore the impact of regulations, tech like Generative AI & ML on AML, cyber, trade surveillance & fraud prevention. Discover solutions for increased accuracy in Financial Crimes..

Watch this webinar highlighting why Financial Crimes investigators (AML, Credit Card, Trade Surveillance, and KYC teams) must use new technology to decrease false positives and increase alert-to-case accuracy and effectiveness.

This blog post discusses the importance of fraud detection and prevention in organizations and introduces Expero's Connected Toolkit as a comprehensive solution.

In this demo we will share our financial crimes field work examples and illustrate how complex data and analytics work together to reduce company’s financial crimes false positive detection.

During this webinar, we delve into the world of financial crimes, shedding light on emerging trends, evolving regulatory frameworks, and cutting-edge technology that combat financial crimes activity.

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.

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

During this webinar, our speakers from Expero and Microsoft discuss expected trends in 2023 for 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.

Easy to use fraud detection software solutions, such as the Expero Connected Toolkit, reduce the overhead required to track and predict fraud and provide a variety of tools for many user personas.

Alerts are a powerful tool for real time fraud detection systems. Alerts can be used to surface things one normally wouldn’t see in real time.

A discussion on how Graph and Machine Learning work together to detect, prevent, and investigate cyber fraud using capabilities that Expero has put together.

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.

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. 

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.

Building a useful fraud detection system requires bringing many tools together and making them work together to bring undetected anomalies to light.

This demo explores cyber and graph analytics

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. 

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.

This post looks at the different technology approaches and adaptations to finding and detecting fraud, and the technology behind Expero's Fraud Product.

This post explores the history of fraud and how Expero's Fraud and AML toolkit is designed to help learn and combat fraud in many types of organizations.

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.

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.

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.

This discussion will go over how Graph and ML combine, as well as cover a demo of Anti-Fraud with Graph in action.

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.

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.

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.

During this webinar, we will show AML and Fraud practitioners how to use Graph and Machine Learning to ensure organizational compliance with AMLA in 2021.

During this webinar, we’ll dive into these collaborative and organizational challenges in the context of Data Science teams working in retail fraud.

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.

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.

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.

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.

The focus of this webinar is to identify how technological advances can directly increase the accuracy and shorten process time for ‘Human in the Loop.'

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’.

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.

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 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.

Fraud Detection and Prevention in Finance

Demonstration of Expero workbench for detecting and investigating fraudulent activity such as AML, credit card transactions and internal threats.

Learn about fighting fraud with Graph and Machine Learning Experts

Build a single view of your corporate security model using new capabilities in graph and streaming technology through which you can funnel all your access attempts to critical data.

Building data products in your organization to realize data science ROI and never before seen data insights.

15 Minute Lightning Talks + Q&A. Powerful Data, Storage & Search & Graph Technology in 1 platform - Cassandra.

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. ‍

Cut Costs & Manage Entitlements with Graph Technology & ML Analytics.

Watch our online seminar to learn how to unlock patient 360 & prevent opioid fraud with graph & ML technology. We discuss how graph-based Patient 360 breaks silos and enables analytics to discover more efficient operations, better healthcare outcomes, and fraud detection.

15 Minute Lightning Talks + Q&A

This demo explores fraud prevention in healthcare applications

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.

This video is about Healthcare: Opioid Fraud Detection & Avoidance.

Transaction investigation and treasure mapping with KPIs using graph technology, high performance search, and high performance analytics.

Use Machine Learning and Graph to Stop Fraud Before it Happens

Lock Down Funding for Intelligent, Graph-Enhanced Fraud Solutions

Use Machine Learning and Graph to Stop Fraud Before it Starts

Money laundering and credit card fraud detection by graph machine learning.

Thwart Fraud Using Graph and AI

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.

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.

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.

This post explores Actimize Complement