[Webinar]: CSA: Robot overlords, AI… and a cup of tea: Automation in collections – presented by Indigo Cloud

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Link: Robot overlords, AI… and a cup of tea: Automation in collections – presented by Indigo Cloud

In this discussion, Indigo Cloud delve into the challenges and opportunities presented by AI, cloud services, and technology in the debt collection sector. They emphasize the importance of laying a solid foundation, focusing on customer-centric approaches, and leveraging cloud-based systems for scalability and cost management. The conversation touches upon the need for secure infrastructure, automation capabilities, and the potential risks associated with outdated technology.

Key Points

  • The “squeeze middle” phenomenon in 2008 has led to increasing costs and debt, necessitating process flexibility and split testing.
  • Customer-centricity and enabling reporting are crucial for debt collection operations.
  • Biased data sets and limited access to niche data pose challenges in developing AI and machine learning models.
  • Cloud-based systems offer scalability and cost advantages, with Microsoft Azure and other major providers being reliable options.
  • Platform-as-a-service models enable smaller and mid-sized companies to access advanced features and functionalities.
  • Security and robust infrastructure are paramount in the cloud environment, although risks remain with external components and legacy systems.
  • New channels like WhatsApp are gaining importance for customer communication and collections.
  • Keeping an eye on future developments and technological advancements is essential.
  • Implementing new technologies and staying updated with cloud-native solutions, such as SQL Azure, can provide efficiency and automation.
  • Legacy systems and outdated technology hinder progress and pose security risks.
  • Continuous improvement and adaptation are vital to navigate the evolving landscape of debt collection.
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Key Statistics

  • The costs of processing data and storage, along with data accessibility, are significant challenges in AI development.
  • Microsoft Azure, Google, and IBM are among the major cloud service providers.
  • Cloud services offer automated security features, ensuring timely application of patches and adherence to policies.

Key Takeaways

  • Establish a solid foundation before incorporating AI and other advanced technologies.
  • Leverage cloud-based systems for scalability, cost management, and accessibility to advanced features.
  • Prioritize security in the cloud environment, considering potential risks and focusing on robust infrastructure.
  • Embrace automation capabilities and new communication channels like WhatsApp for improved efficiency.
  • Stay up-to-date with technological advancements and cloud-native solutions for competitive advantage.
  • Address biases and limitations in data sets to ensure AI models are accurate and reliable.
  • Smaller and mid-sized companies can benefit from platform-as-a-service models for advanced functionalities.
  • Focus on customer-centricity and enable comprehensive reporting to enhance debt collection operations.
  • Continuously analyze and mitigate risks, keeping operational and security concerns in mind.
  • Adapt to the changing landscape and evolving customer preferences to remain competitive.
  • Modernize legacy systems and avoid reliance on outdated technology to maximize efficiency and minimize security risks.
  • Collaborate with reputable cloud service providers to ensure reliable and secure infrastructure for debt collection operations.

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