06Debt collectionLarge enterprise
Supporting respectful payment self-service
A policy-led digital employee expands contact options, captures circumstances and routes hardship cases appropriately.
Illustrative scenarioAll results shown below are modelled, not verified client outcomes.
THE OPERATING CONTEXT
A realistic starting point.
High-volume outbound campaigns create uneven demand and limited calling-window capacity. Customers often prefer digital contact, while collectors need better context before sensitive conversations.
THE AIIT SOLUTION DESIGN
A digital employee built around the work.
SAM coordinates consent-aware voice, SMS and messaging journeys, completes identity checks, presents approved account information and captures arrangement requests within strict rules. Vulnerability, disputes and hardship indicators trigger specialist review.
END-TO-END WORKFLOW
From first contact to a useful outcome.
- 01
Respect channel consent and permitted contact windows
- 02
Confirm identity before disclosing account information
- 03
Understand payment, dispute or support intent
- 04
Offer only policy-approved self-service options
- 05
Record the customer response and next action
- 06
Prioritise hardship, vulnerability and disputes for people
MODELLED OUTCOMES
What a well-run scenario could change.
Planning estimates only. Not a promise, forecast or report of actual AIIT client performance.
Eligible arrangements self-served
Collector preparation time
After-hours engagement
ASSUMPTIONS
The conditions behind the model.
These boundaries make the scenario interpretable. Change the demand, workflow mix, integration quality or adoption rate and the potential outcomes change as well.
All contacts follow applicable policy, consent and timing controls
No autonomous negotiation occurs outside predefined arrangement limits
Hardship and vulnerability recognition prioritises review rather than diagnosis
Outcome figures do not represent recovery-rate promises
A CONTROLLED PATH TO VALUE
How this scenario could be implemented.
Encode contact, consent and arrangement policies
Design language for respect and clarity
Connect account status with minimum necessary access
Review recordings and escalations with compliance teams
DESIGN LESSONS
What matters beyond automation.
Customer choice of channel affects engagement.
Sensitive work needs stronger exception paths than ordinary service automation.
Operational measures should include appropriate support referrals, not collections alone.
About this scenario: AIIT created this fictional, anonymised operating example to support planning conversations. The figures are calculations based on the assumptions shown above; they do not represent an existing client, testimonial or guaranteed result.
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We can replace these assumptions with your contact volumes, workflows, service targets and operating costs.
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