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Allianz: Predicting Direct Debit with Machine Learning

Lennert Van der Schraelen, Emma Willems, Kristof Stouthuysen, Tim Verdonck, Christopher Grumiau, Thoppan Mohanchandralal Sudaman

商品編號:W27310
出版日期:2022/11/30
再版日期:
商品來源:
商品主題:Finance
商品類型:Case (Field)
涵蓋議題:Direct Debit;Machine Learning;P & C claims;Working Capital
難易度:5 - MBA/Postgraduate
內容長度:9 頁
地域:Belgium
產業:Finance and Insurance
事件年度:2021

In January 2021, the chief data and analytics officer (CDAO) at Allianz Benelux SA (Allianz) spotted a possible opportunity to optimize cash flow with direct debit. Direct debit was a pre-authorized financial transaction between two parties where the amount due was directly and automatically collected from the payer’s bank account. Direct debit would allow Allianz to shorten payment processes, reduce risks by anticipating payments, and improve customer loyalty. Despite the clear advantages of direct debit for both clients and insurers, only a few of Allianz’s clients were currently making use of direct debit. It was not clear what drove Allianz’s customers or brokers to implement direct debit. This was where the CDAO and his data office team came in. The data office possessed a large amount of data on Allianz’s property and casualty insurance contracts and customers. Now the team needed to investigate how this data could be leveraged to determine the value drivers and develop a strategy to convert more clients to direct debit payments.

教學手冊:Allianz: Predicting Direct Debit with Machine Learning - Teaching Note
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