AI in Receivables Management from the CIO's Perspective - German

The document presents a comprehensive case for implementing AI-driven solutions that can automate complex collections processes while improving customer experience and operational efficiency. Through real-world examples, including a detailed case study of Česká spořitelna's successful implementation, the authors demonstrate how these AI technologies can reduce operational efforts by up to 25 percent while maintaining stable performance metrics. The article emphasizes that these solutions represent manageable technology deployment challenges for CIOs while offering substantial value in terms of cost reduction, improved customer treatment, and enhanced decision-making capabilities.

• How Ccnversational AI can automate six key collections scenarios - including negotiation, payment processing, hardship identification, and fraud detection - while providing pre-defined, compliant responses that eliminate the risk of AI hallucinations
• How AI-powered decision optimization can mathematically determine optimal treatment strategies - enabling organizations to balance competing targets like operational effort and cure rates, optimize resource allocation, and make data-driven decisions about which customers to contact, when, and through which channels
• Practical implementation insights and measurable results - see how Česká spořitelna used AI-powered collections optimization to significantly reduce operational costs while maintaining portfolio performance and improving customer satisfaction