Mitigating Risk with Generative AI in Credit Customer Assistance and Collections

Mitigating Risk with Generative AI in Credit Customer Assistance and Collections

The credit customer assistance and collections sector is mitigating risk with generative AI, enhancing efficiency, and improving customer outcomes, according to an article by McKinsey and Company.

Technological disruptions, accelerated by the COVID-19 pandemic, have driven advancements like machine learning, digitization, and automation, making customer assistance more streamlined and data-driven. 

The emergence of generative AI (Gen AI) is transforming credit customer assistance and collection functions by enhancing operational efficiency, effectiveness, and customer outcomes.  These technologies enable better services, renegotiation pathways, and improved settlement conditions, strengthening customer relationships and improving financial health.

Gen AI, the latest advancement, has the potential to significantly impact customer assistance by personalizing customer contact, boosting agent capabilities, and automating routine tasks. This technology can aid regulatory processes by organizing and synthesizing information. 

Its adoption goes beyond reducing delinquencies, as it can improve customer interactions and treatment, reduce collection costs, and retain collections in-house, enhancing customer loyalty and competitiveness.

The McKinsey article highlights that organizations deploying Gen AI in customer assistance and collections can achieve significant cost reductions, improved recoveries, and increased customer satisfaction. Gen AI can address core issues in customer interactions, gather insights, support agents, and automate interactions, leading to better customer outcomes.

Implementing Gen AI requires a structured approach, starting with high-value internal use cases that require limited development efforts and minimal risk. Early use cases should be simple and manageable, with clear guardrails. Over time, more advanced applications involving real-time output and unstructured data can be developed, leading to transformational changes in operations.

Integrating Gen AI can improve support for customers in financial distress, benefiting both customers and institutions. A structured roadmap is necessary to capture value, minimize risks, and maximize cross-organizational investment for long-term success.