Case studiesDebt collection
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.

  1. 01

    Respect channel consent and permitted contact windows

  2. 02

    Confirm identity before disclosing account information

  3. 03

    Understand payment, dispute or support intent

  4. 04

    Offer only policy-approved self-service options

  5. 05

    Record the customer response and next action

  6. 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.

+9 points

Successful right-party contacts

Baseline18%
Modelled27%
+26 points

Eligible arrangements self-served

Baseline6%
Modelled32%
−71%

Collector preparation time

Baseline2 min 10 sec
Modelled38 sec
+12 points

After-hours engagement

Baseline4%
Modelled16%
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.

01

Encode contact, consent and arrangement policies

02

Design language for respect and clarity

03

Connect account status with minimum necessary access

04

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.

Model the opportunity in your organisation.

We can replace these assumptions with your contact volumes, workflows, service targets and operating costs.

Build my business case
SAM JOBS

See what roles SAM's can do

Browse 81 Typical SAM Roles — from receptionist and claims specialist to compliance, sales and operations — each a Digital Employee powered by ANNA and managed by AIM.

See what roles SAM's can do
ENQUIRE WITH AIIT

Start a conversation about collections self service.

Tell us what you want to improve. Your enquiry will go directly to the AIIT team in Auckland.

Your enquiry is sent securely to hello@aiit.co.nz.