Browsing by Author "Francisco, Daniela Ferreira"
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- How artificial intelligence can help banks improve the customer experience of buying a housePublication . Francisco, Daniela Ferreira; Romeiro, Paulo Alexandre Mendes RamosThe focus of this thesis is to understand how artificial intelligence can help banks in general to improve the customer journey of buying a house. Since the financial crisis, banks have been struggling to maintain profitability. The drivers for change in the industry are now the new competitors emerging in the financial landscape, new regulations implemented in the industry and the new customers’ expectations regarding technology. This thesis argues that banks could use their natural advantage with mortgage loans and their investments in artificial intelligence to improve the customer journey of buying a house. After conducting research, dept interviews and customer research, the customer journey was outlined and concluded that overall, the buying of a house is a complicated and unfamiliar process. Followed AI focused research, a new and enriched customer journey was drawn and complemented. It is suggested that banks implement AI to make the process more transparent and easier to navigate. A virtual real-estate agent powered by AI would assure the bank that the process is completed and guarantee the banks revenues for customer loans. Leveraging AI algorithms and customer information the bank can help the customer narrow down its searches presenting viable housing options to the customer which allows the bank to increase customer satisfaction, reduce customer churn, reduce the banks operational costs and ensure the revenues from mortgage loans.