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    Allianz: Predicting direct debit with machine learning

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    Author
    Van der Schraelen, Lennert
    Willems, Emma
    Stouthuysen, Kristof
    Verdonck, Tim
    Grumiau, Christopher
    Thoppan Mohanchandralal, Sudaman
    Publication Year
    2022
    Publication Number of pages
    9
    
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    Abstract
    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.
    Keyword
    Debit Payments
    Knowledge Domain/Industry
    Accounting & Finance
    URI
    http://hdl.handle.net/20.500.12127/7194
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