Fraugster teams up with Elvah to tackle fraud in the ecommerce sector

Image Credit: Last week, payment intelligence provider Fraugster announced that it had formed a partnership with e-mobility company Elvah to create a new managed payment protection service. In the future, Elvah will offer users chargeback protection, risk management and credit scoring through a single AI-driven platform.

The service will enable Elvah to better detect identity fraud thanks to an AI-based fraud prevention engine, which offers real-time risk scoring for ecommerce transactions. The engine uses over 2,500 variables in each transaction to decide whether to approve or block the payment. No compatible source was found for this media.

The engine doesn’t rely on a fixed algorithm to identify fraud but rather uses three main machine learning models. One is a self-learning model designed to catch complex, well-defined fraud patterns. Another is a logistic regression model to measure the strength of cause-and-effect relationships in structured data sets. There’s also an AI-powered clustering model that can identify fraudulent patterns that aren’t based on historical data or other ML models. The challenge of mitigating fraud

The announcement comes as identity fraud has remained a serious threat to ecommerce providers, enterprises and consumers alike, with the cost of ecommerce fraud rising from $17.5 billion in 2020 to $20 billion last year.

One key reason for this increase has been that the cost of remediating fraud has increased following the COVID-19 pandemic, with each $1 lost to fraud costing retailers $3.60 in expenses to mitigate, compared to $3.13 pre-pandemic.

As the cost of fraud continues to increase, it’s clear that ecommerce providers and enterprises need to evolve if they want to spot and prevent frauds. This is a challenge because many organizations remain reliant on disjointed data pipelines that make it difficult to gain cohesive insights into the status of fraud.

“The ecommerce ecosystem continues to operate in […]

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