Category: Risk, Page 2

Read and learn about fraud risk and how to reduce it with the following articles and posts by Ekata, a Mastercard company.

Managing Ecommerce Risk to Increase Monthly Revenue

Ekata

Case Study: Reduced False Declines and Increased Monthly Revenue Through Ekata Risk Scores

While the approach to capturing fraud and false declines varies from company to company and from industry to industry, one thing is certain: implementing an end-to-end identity verification solution into your risk assessment model is essential (to reduce ecommerce risk). In this case study, Ekata performed a historical analysis on previous transactions accepted and declined […]

2.1.2021

Ekata

Ekata Executive Series, Part II: Trust Starts at the Source: Credit Risk Versus Fraud Risk

Welcome to Ekata’s Executive Series. In this series, our CEO, Rob Eleveld, will be outlining the dynamics we see developing in the global identity verification (IDV) market and highlight Ekata’s response to continuous market demands. Today, we are digging into the deterministic approach of credit risk and comparing it to the probabilistic approach of fraud […]

11.30.2020

Ekata

Assessing Risk in Uncharted Times

Welcome to part two of a three-part series in which we look at the impacts of COVID-19 on digital commerce and fraud patterns, and insights our data provides on identifying fraudulent behavior. In our last blog, Where have all the Fraudsters Gone? we looked at data that showed overall ecommerce shopping trends are up, reflecting increased […]

6.16.2020

Identity Network and Online Fraud Detection

Ekata

The Good, the Bad, and the Risky: Catching Fraudulent Activity with Network Score

Companies today face a rapidly evolving landscape of fraud attack types such as account takeover and credential stuffing. Bad actors are constantly changing their tactics to find new ways to commit fraud, leaving businesses challenged to stay proactive and vigilant against malicious attacks. As stolen personally identifiable information (PII) becomes increasingly prevalent, fraudsters can often […]

6.14.2020

Ekata

New Feature in Pro Insight: Network Risk

We researched and assessed the needs of our users to ensure this release would provide absolute value and are extremely excited that with the Network Risk panel, Pro Insight is now the only manual review solution that enables agents to investigate both the validity of identity elements as well as activity and usage patterns of […]

6.4.2020

Ekata

Using AI to Assess Identity Risk and Treat Good Customers Better

The democratization of artificial intelligence has had a dramatic impact on how businesses approach identity risk. Prior to its introduction, there were already an influx of data points streaming into digital businesses, from site behavior, to device IDs, to digital signatures like IP addresses. Traditional rules-based approaches to onboarding customers were overwhelmed by new access […]

10.3.2019

The Conflicting Pressures of the Evolving Payments Ecosystem

Ekata

The Evolving Payments Ecosystem's Conflicting Pressures

From the customers who make the transactions to the merchants, payment service providers, and card issuers who facilitate those transactions, the payments ecosystem is made up of a number of distinct players with individual needs. This has always been the case. But as the payments ecosystem evolves through the addition of new technologies, more sophisticated […]

8.28.2019

Ekata

Transaction Risk API: The Value it Brings to the Market

Transaction Risk API was built for easy integration into sophisticated machine learning (ML) models and is designed to help eCommerce merchants, marketplaces, payment processors, and others manage payment fraud. Understanding market requirements In our first blog of the series, we covered the evolution of fraud and how the landscape of today requires fraud detection earlier […]

4.25.2019

Ekata

Transaction Risk API - How we Built It

Fraud is getting more sophisticated as the payments industry continues to see massive disruptions, and merchants, lenders, and payment processors are turning to machine learning models to detect suspicious qualities in a transaction. Our goal with Transaction Risk API was to provide a powerful tool to help in this space. One of the biggest factors […]

4.16.2019