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The human-centered AI approach of Symend

Published: May 13, 2024Author: Rebecca Kates

Key Takeaways

Symend emphasizes the importance of combining Artificial Intelligence with Human Intelligence. The company believes that AI and HI are complementing each other to create a deeply individualized experience.

Understanding Conscious Engagement

Conscious Engagement represents the combination of data science, behavioral science and technology. The approach integrates behavioral scientists who use experimentation and academic research alongside data scientists who analyze performance metrics. The platform uses AI-embedded expertise to suggest content, channels, and best next steps for positive customer engagement.

The Role of AI Assistants

The solution operates through two layers: analytical and generative. The analytical layer builds engagement strategies based on human interactions, while the generative layer creates tailored outreaches aligned with individual goals.

AI Applications

Symend has embedded AI in three primary ways:

  1. Engagement Optimization Assistant — Develops data-driven strategies without requiring extensive manual analysis
  2. Content Assistant — Generates customized messaging for multiple channels
  3. Customer Feedback Analyzer — Interprets responses to inform strategy refinement

A Human Approach

The company acknowledges that both AI and HI are capable of biases and must complement each other, working together to responsibly normalize and humanize the approach to customer engagement.

Key Takeaways

  • Conscious Engagement defined: Symend's approach combines data science, behavioral science, and technology to individualize every customer interaction at scale—replacing generic outreach with strategies grounded in human psychology.
  • Two AI layers working together: The analytical layer builds engagement strategies from real human interaction data; the generative layer creates tailored outreach aligned to each individual customer's goals and circumstances.
  • Three embedded AI applications: The Engagement Optimization Assistant, Content Assistant, and Customer Feedback Analyzer remove guesswork from collections strategy—so teams act on insight, not intuition.
  • AI and Human Intelligence must complement each other: Both artificial and human intelligence carry biases; responsible, effective collections requires both to work together to normalize and humanize the customer experience.
  • The methodology that delivers it: Behavioral science defines the variables, data science defines the methodology, and the platform executes. Proprietary Delinquency Archetypes decode each customer's capacity to pay and readiness to act, delivering empathetic, personalized outreach that resolves accounts and preserves the relationship.

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