GenAI in Asset Management: The digital edge

Redefining asset management customer service and distribution

In asset management, exceptional client service is not just a differentiator – it is a fundamental requirement. Advisors and investors depend on rapid, clear responses to inquiries related to transactions, product details, and regulatory guidance. The integration of artificial intelligence (AI) into customer service operations is revolutionizing client interactions by reducing response times, streamlining query resolution, and offering seamless self-service.

Key challenges of traditional customer service

Traditional customer service models in asset management often struggle with challenges ultimately affecting client satisfaction and operational efficiency. These include:

  • Latency and productivity loss due to lengthy response times
  • Inconsistent answers from service agents
  • High escalation rates for routine inquiries

Implementing the agentic framework: AI-driven customer service transformation

Adopting an AI-driven framework that utilizes advanced technologies like large language models (LLMs) and retrieval-augmented generation (RAG), asset management firms can significantly improve key service metrics.

Implementation considerations

To successfully deploy AI-powered customer service, firms should consider the following:

  • Piloting AI on FAQs and simple inquiries
  • Securing a comprehensive knowledge base
  • Ensuring robust traceability for compliance
  • Providing frontline coaching for agents
  • Continuously optimizing AI capabilities

The future of asset management customer service isn’t waiting – it’s unfolding now. Where do you stand in this journey?

Dive into our thinking:

GenAI in Asset Management

The digital edge: Redefining asset management customer service and distribution

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