Day 2 of 14 · AI in Trade Credit Control

Your Credit Control AI Toolkit

⏱ 6 min 📊 Beginner

Yesterday you saw why credit control is ripe for AI. Today you get equipped: which assistant to use, the one confidentiality rule you must never break, and three prompts to run before the end of the day.

The good news: the setup is genuinely ten minutes. You don't need new software, integrations, or an IT project. A general-purpose AI assistant in a browser tab covers most of what this course teaches.

The big three assistants

Three general-purpose assistants dominate, and for credit control work they're more alike than different:

ChatGPT (OpenAI) — the most widely used, strong at drafting emails and restructuring messy data into tables and summaries.

Claude (Anthropic) — excels at long documents, careful reasoning, and nuanced tone — useful when a chaser needs to be firm without burning the relationship.

Gemini (Google) — integrates well if your business already runs on Google Workspace.

All three have free tiers that are plenty for this course. Paid plans (typically priced like a modest monthly software subscription) give you stronger models, longer documents, and more usage — worth it once AI becomes part of your daily routine, but not required to start. Pick one, create an account, and don't agonize: the prompts you'll learn work on all of them.

The confidentiality rule

Before you paste anything, burn this in: customer financial data is confidential. Never paste real customer names, account numbers, contact details, or full ledgers into a consumer chatbot.

Consumer AI tools may process your input on external servers, and depending on your settings it could be retained or reviewed. Your customers' payment histories, balances, and credit terms are sensitive business information — and in many jurisdictions, personal data rules apply too. Check your company's data policy and, if in doubt, ask your compliance or IT lead.

The working fix is simple: anonymize before you paste.

Do: replace names with codes ("Customer A", "ACC-104"), round or scale amounts if they're identifying, strip contact details, and keep only what the AI needs — ages, amounts, and payment behavior.

Never: paste a raw ledger export, credit application, or email thread containing real names, bank details, or personal information.

The pattern, the analysis, and the drafting all work exactly as well on "Customer A owes 12,400, 60 days overdue" as on the real name. You lose nothing by anonymizing — and you stay on the right side of your data obligations.

Three AI assistant cards above a data-hygiene panel showing anonymized extracts marked as safe and raw customer ledgers marked as never paste

The tool choice matters far less than the hygiene habit. Anonymize once, and every prompt in this course is safe to run.

Knowledge Check

You want AI to summarize your aged debtors report. What's the correct way to do it with a consumer chatbot?

A

Don't use AI for ledgers at all; it's only safe for writing emails

B

Replace customer names with codes, strip contact details, and paste only the anonymized extract

C

Export the full ledger and paste it in — speed matters most

D

Paste the real data but ask the AI to keep it confidential

Anonymize first: codes instead of names, no contact or bank details, just ages, amounts, and behavior. The analysis works just as well — and asking a chatbot to "keep it confidential" does nothing about where the data is processed or stored.

Three prompts to run today

Prompt 1 — Summarize an aged debtors report. Paste an anonymized extract and ask: "You are an experienced credit controller. Summarize this aged debtors extract: total overdue by bucket, the three accounts that need attention first and why, and any patterns I should worry about." Thirty seconds later you have the briefing that used to take an hour of squinting at rows.

Prompt 2 — Draft a polite chaser. "Draft a short, polite payment reminder for an invoice of 8,200 that is 10 days overdue. Professional and warm — this is a good customer who usually pays on time. Include the invoice number placeholder, the amount, and a clear ask for a payment date." You'll refine tone ladders on Day 8; today, just see how fast a send-ready draft appears.

Prompt 3 — Explain retention of title in plain English. "Explain what a retention of title clause is in a B2B supply contract, in plain English, and why it matters if a customer becomes insolvent. Keep it under 150 words." AI is excellent at turning legal concepts into plain language you can use in conversations — though actual contract wording always goes through a lawyer, as you'll see on Day 5.

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ChatGPT

online

You are an experienced credit controller. Summarize this anonymized aged debtors extract and tell me what to act on first: Customer A — 12,400 — 61 days overdue — 2 reminders sent Customer B — 3,150 — 8 days overdue — none sent Customer C — 22,700 — 34 days overdue — disputed delivery Customer D — 1,900 — 92 days overdue — no response to 3 reminders Customer E — 7,800 — current, due in 5 days

Here's your briefing: **Total overdue: 40,150** across four accounts (E is current). **Act first:** 1. **Customer C — 22,700, disputed.** Your largest exposure, and it won't move until the dispute does. Get the delivery evidence together and resolve or escalate this week. 2. **Customer D — 1,900, 92 days, silent.** Small amount, worst signal — three ignored reminders means this needs a phone call and an escalation decision, not a fourth email. 3. **Customer A — 12,400, 61 days.** Two reminders sent; time to step up to a firm notice with a specific payment deadline. **Routine:** Customer B just needs a friendly first nudge. Send Customer E a pre-due courtesy note to keep it current. **Pattern to watch:** most of your risk sits in two accounts — C and A are 87% of the overdue total. Want me to draft the three emails?

↻ Replay conversation

Knowledge Check

In the chat demo, why did the AI rank tiny Customer D (1,900) above larger Customer A (12,400)?

A

Three ignored reminders at 92 days is a serious warning signal that needs a call and an escalation decision, not another email

B

The AI made an error — the largest amount should always be chased first

C

Smaller amounts are always faster to collect, so they come first

D

Older debts must legally be chased before newer ones

Amount isn't the only signal. An account that has gone silent through three reminders at 92 days is showing classic bad-debt behavior — the risk of losing it entirely outweighs its size. Prioritization blends amount, age, and behavior, which you'll go deep on in Day 7.

Ten minutes, then compounding returns

That's the whole toolkit: one assistant, one hygiene rule, three prompts. Notice what just happened in the demo — a five-line extract became a ranked action plan with reasoning, and the AI offered to draft the emails on the spot. You'd still review every word before sending — but the blank page is gone forever.

Tomorrow you point this toolkit at the decision that prevents bad debt in the first place: checking a new customer before you extend credit terms.

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Day 2 Complete

"Ten minutes of setup, then every chaser, summary, and report draft gets faster."

Tomorrow — Day 3

AI-Assisted Customer Credit Checks

Tomorrow you'll learn what to check before extending credit terms and how AI turns a dense credit report into a one-page risk snapshot.

Continue to Day 3 →