AI Agents

Context

Built for banking in the Customer churn & retention stack, this agent is used for early warning across deposits, cards, and consumer lending. Typical scenarios include monitoring day-to-day product usage and digital engagement, capturing service/complaint effects on behavior, and prioritizing customers for timely retention actions.

What it does

The agent analyzes recent customer activity and surfaces early churn signals with an explainable driver summary. It tracks usage patterns (balances, transactions, card activity), digital interactions (logins, sessions), and service events, then flags sustained declines or abrupt breaks that historically precede attrition. The output is a risk flag and score per customer, plus concise reasons linked to the underlying events so teams know who to address and why.

Core AI functions

Per-customer and cohort baselining to establish “normal”; change-point and trend detection for deteriorating usage and engagement; engineered features for recency, frequency, intensity, and volatility; association of complaint/service markers with subsequent churn; and reason-code generation (e.g., “30-day decline in logins and card spend” or “multiple service issues in one cycle”). Thresholds and look-back windows are tuned to retention objectives.

Problem solved

Churn indicators live in multiple systems and are noisy, leading to late or misdirected outreach. This agent consolidates the earliest reliable signals and explains movement, so effort targets accounts where timely action changes outcomes.

Business impact

Higher retention through earlier identification, better retention actions guided by clear drivers, improved customer experience from relevant, timely contact, and improved NPS as emerging issues are addressed before customers decide to leave.

Integration complexity and adjacent use cases

Integration is light–moderate: read product-usage, transaction, digital, and service/complaint feeds from the warehouse or stream; write churn flags, scores, and reasons to CRM/CDP or journey orchestration; no core replacement required.

Common combinations in this stack

• Root cause identifier (complaint & sentiment),

• Document-driven feedback & closure validator, and

• Churn retention exception handler.