How to train the credit control team to review AI agent decisions

Credit controllers learn to review the agent in four stages: lessons on how it chases, allocates cash and proposes account stops; calibration on held disputes and stops; two weeks of shadowed review; and sign-off. Weight the standard toward decisions that damage relationships if wrong: stopping supply to a good customer, or chasing a disputed invoice.

What does the credit control team review?

A credit control agent typically sends reminder and dunning letters on a set schedule, allocates incoming cash against open invoices, reconciles remittance advice, flags overdue accounts, drafts statements, and proposes actions: putting an account on stop, reducing a credit limit, referring a debt to collection or legal. Routine reminders and confident cash matches run at depth 3. Proposals that affect the customer relationship are held for a controller.

That gives controllers three review jobs. Held proposals, where they decide. Unmatched or uncertain cash, where the agent could not allocate confidently. And a sample of what it did alone: letters sent and cash matched.

The credit manager owns the programme. The sales director should see the sign-off standard for account stops, because stops land on their customers. The agent's owner attends calibration.

What does the programme look like, step by step?

1. Learning, week 1: controllers complete lessons on the agent's decision chain and the specific bounds for this agent: which letters it sends alone, what cash confidence it needs to allocate, and which proposals it must hold.
2. Agent, depth 1: assembles a practice set of past held stops, limit changes, disputes and uncertain cash with their outcomes.
3. Calibration, week 2: controllers decide alone, then compare. Start with account stops on large customers and disputed invoices.
4. Shadow, weeks 3 and 4: controllers review live items, with a senior controller checking every decision.
5. Agent, depth 3 in live work: sends scheduled letters, allocates confident matches, holds the rest.
6. Sign-off: credit manager assesses shadow decisions on accuracy and on relationship impact.
7. Ongoing: weekly sampling of letters and allocations, monthly calibration.

What must controllers learn to check?

Disputes hidden in correspondence. A customer replies to a reminder saying the goods arrived damaged. That invoice is now disputed, and chasing it further damages the relationship and may be pointless. The agent should recognise and hold; controllers check that it did, and sample letters for disputes it missed.

Account stops. Stopping supply to a customer who is a week late but has paid reliably for years is rarely right. Controllers weigh payment history, the size of the relationship, and any reason given. The agent's proposal is a starting point.

Cash allocation. A payment arrives for a round amount with no remittance. The agent allocates to the oldest invoices if confident, or holds. Controllers check the allocation against the customer's own remittance when it arrives, and correct mismatches quickly, before the next letter goes out on a paid invoice.

Remittance advice from outside. A remittance emailed by the customer is external. It can guide allocation; it cannot by itself prove payment. The bank feed is the sealed source.

Credit limit changes. Reductions affect sales. Controllers check the evidence and, where the policy requires, involve sales before agreeing.

Tone of letters. Final demands to long-standing customers need care. Controllers sample for wording that is accurate but harmful.

Which controls leave evidence?

• Lessons before shadow. Evidence: completion dates.
• Shadow decisions checked. Evidence: senior controller's name.
• Stops on key accounts need a second person. Evidence: two names on each.
• Allocations reconciled to bank. Evidence: the reconciliation record.
• Disputes logged with the invoice. Evidence: dispute status on the ledger.

What should you measure?

• Shadow accuracy per controller.
• Letters sent on disputed or paid invoices, which should fall to near none.
• Unallocated cash ageing.
• Account stops reversed within a week, a sign of poor stop decisions.
• Days sales outstanding, watched for change but not used alone, since it can improve while relationships suffer.

Where does it usually go wrong?

The schedule becomes the policy. Controllers let the agent's chase schedule run without looking at who is being chased. Sampling fixes this.

Sales is surprised. Account stops land without warning. Agree a notification rule with sales and train controllers to follow it.

Cash corrections lag. A misallocation is corrected days late, after a wrong letter has gone. Train controllers to work uncertain cash first each morning.

Disputes are settled informally. A controller agrees a credit note by phone and does not record it, so the agent keeps chasing. Every dispute outcome goes on the ledger.

The individual view is in how credit controllers review an AI agent's decisions, and new starters follow the reviewer onboarding checklist for the credit control team. Lending credit teams review very different decisions under the same four stages; see how to train the credit team to review AI agent decisions and how credit analysts review an AI agent's decisions. The full programme is in training teams for AI agents.

Where the Academy fits

Pryme Intelligence Academy's Operator track covers how a governed agent decides, human review, and running the rhythm of daily sampling, with module tests set in the learner's own industry and role. Labs run in a free Build workspace. Controllers who pass the exam, 40 questions with a pass mark of 32, and the two-week practicum become Certified Pryme Operators for 12 months.