Digital Transformation and Post-COVID Customer Journeys

Fraud
Management/mitigation
Machine Learning
Olga Sokolovskaya and Mike Kasley -- ACI Worldwide
Nov 18, 2020
Webinars
The COVID-19 pandemic has caused significant changes to how, when, and where customers are making retail purchases. To align with these new customer journeys, merchants are transforming -- and, in some cases, even reinventing -- their processes. This webinar looks at the effects of the novel coronavirus on eCommerce, including transaction volumes and acceptance rates. ACI then discusses the advantages machine learning can bring to fraud mitigation and the role data plays in fraud prevention. A brief Q&A session concludes the broadcast.

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Customer Recognition System - A New Tool of Detecting Fraud

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At Intuit, our customer recognition system (named Core ID, internally)  is focused on finding out if one customer or one family/close cluster uses one or more entities to register many accounts for products, such as QuickBooks Payments and QuickBooks Payroll customers. 

Normally, if the customer is identified with one set of entities, we can use existing solutions for ID-mapping, which rely on “exact” matching among entities to create clusters and graphs. However, this absolute linkage will fail if the customer is associated with multiple entities or changes entities (device IDs, IP address, etc.). 

To solve this problem, we have devised a methodology for recognizing one customer, or one household, from different angles by applying several AI-driven technologies. 

Intuit’s customer recognition system reveals relationships among different entities, serving as a complement to existing linkage-based graph analytics to more quickly identify or predict the association between customer accounts. Understanding these underlying connections more quickly is one strategy for building long-lasting customer relationships.

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