Artificial Intelligence (AI) combined with Chargebacks911’s unique proprietary consortium data, dramatically enhances digital cognition and data recognition in fight against fraud
Chargebacks911, the leading dispute technology specialist that powers chargeback remediation for the largest global eCommerce businesses, as well as the world’s financial institutions, today celebrates a 3x boost to its automated dispute response platform. The addition of AI further propels Chargebacks911’s worldwide market advantage, as the leading dispute technology platform*.
The utilization of data from a vast consortium of businesses across a number of verticals, enables the technology to be ‘trained’ to dynamically identify data points related to post transaction fraud, including first party fraud. This is then enriched to exponentially improve underlying dispute intelligence and insights for merchants.
First party fraud, also known as ‘Friendly Fraud’, refers to an illegitimate chargeback filed on a legitimate transaction and costs the eCommerce industry staggering amounts each year. This accounts for up to 25% of a merchant’s profits, highlighting how catastrophic this problem is for the global economy. Post transaction fraud surged by 23% in 2021** however, first party fraud, a subset within this category, has surged 56%*** making it one of the fastest growing fraud types on record.
One of the primary reasons for the growth in first party fraud is due to unavailable feedback from the merchant. As a result of the mammoth quantity of chargeback data that online merchants receive, and the time it takes for a human operator to investigate each chargeback and determine whether it is legitimate or not; the vast majority of cases expire, inadvertently contributing to this negative trend and its unintended consequences.
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To slow this worrying growth trajectory, and keep pace with evolving data sets, the industry needs to adopt more intelligent automation in order to scale. In contrast to a costly human led strategy, Chargebacks911 revolutionizes the data collection process, transforming the concept of end to end automation by digitizing even the most complex and unstructured formats to maximize data insights and leverage rule-based data driven automation.
Monica Eaton-Cardone, Founder of Chargebacks911, says: “We know that chargebacks are out of control and this can be devastating, especially in today’s desperate economic climate. However, by further fueling the power of AI in our digitization of the disputes management process, the heavy lift of data aggregation is optimized, providing insight and flexibility that easily accommodates the changing landscape of chargeback rules and payments. Creating a more sustainable ecosystem is all about replacing friction with intelligence, and applies to all stakeholders – merchants included. This is really something to celebrate!”
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Monica adds: “Models that primarily leverage a BPO service or outsourced human workforce to manually prepare dispute responses fall short – today’s merchant not only requires automation for scale, but also for scope as data continues to evolve. With increasing economic pressure it’s imperative that merchants are able to learn from this vital insight.”
Chargeback911’s AI enabled automated dispute response platform allows merchants of all sizes across dozens of verticals to intelligently fill the knowledge gap and thwart growth in first party fraud. Without an in depth understanding of the post transaction data types, chargeback rules, and dispute reason codes, which differ between card networks and alternative payment methods, merchants risk becoming victims to increasing chargeback fraud. Chargeback911’s platform acts as a multidimensional orchestration layer, powering rules based logic, Machine Learning (ML), and AI driven calculations that work in unison, to dynamically analyze and classify data input and compile a dispute response. When compared to automation alone, a yield of up to 3X results are achieved with the addition of data driven AI enablement, further enhancing the added benefit of rich data analytics.
