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Q1: What is the difference between master data and aging data?

Your master file is the single source of truth about each customer: who they are, how they are structured, how to reach them and what you agreed with them. Your aging data is the record of outstanding balances, built from the invoices captured into your ledger. They are captured in different places, but the one feeds the other.

Q2: Where does master data come from?

Several parts of the business feed it. The credit application is usually the starting point, with pricing added by sales and delivery dates agreed by operations, often recorded in a service level agreement or pricing agreement. A data capture team, or someone capturing on behalf of each department, then loads it.

How the data flows:

1. Credit application received.
2. Information collected and verified.
3. Master file created or updated.
4. Transactions flow in against the account.
5. Latest aging data is produced.

Q3: What should a master file hold?

A complete master file holds the customer’s legal entity details, group structure, contact and delivery details, credit terms, and the identifiers and links (such as registration and VAT numbers) that connect the account to other records. Most systems have space for far more information than you are forced to complete, but whatever you skip at onboarding you will have to chase later.

What to do:

• Ask for the information you will need from the beginning, including parent and associated companies.
• Map the customer’s process to positions, not people. For example: the invoice leaves with the delivery note, the receiver signs, procurement signs, then the central GM approves.
• Capture addresses, contact details and email addresses accurately, as every later touch point relies on them.

Q4: Why does accurate master data matter so much for credit decisions?

Good data leads to good decisions and bad data leads to bad ones. Your master data drives who you invoice, what your statements say, and how your customer is matched to bureau and payment behaviour data. If the customer is matched incorrectly, including in Trade Shield, the recommendation you receive will describe the wrong picture. In Martin’s experience, roughly 90% of bad debt traces back to bad data: wrong invoicing, wrong timing, missing purchase orders, wrong pricing or the wrong product. Put simply, your master data reflects how well your admin is run.

Q5: Why should I avoid acronyms and trade names in master data?

Always capture the registered legal name, not an acronym, abbreviation or trade style. “STD Bank” and “FNB” are not registered names; the legal entities are Standard Bank of South Africa Limited and First National Bank of South Africa. The same applies to trading names: a franchise trading as Spar is its own legal entity, and that entity (not Spar) is who you are exposed to and who you must assess.

What to do:

• Capture the name exactly as it is registered with CIPC.
• Record the trade style in a separate field, so it is never confused with the legal entity.
• Do not accept a salesperson’s shorthand. Confirm who the legal entity is before the account is opened.

Q6: What happens when a customer changes, for example from a CC to a Pty Ltd?

A converted company receives a completely new registration number, and its members may have become directors, or left altogether. If your master file is not updated, you keep invoicing the old entity, and any matching or assessment is run against the wrong business. Legally you are under no obligation to get a new credit application signed after a CC converts, but that is exactly the gap that causes problems.

What to do:

• The moment you hear about a change, ask from what date it is effective, so that invoices and statements are correct from that date.
• Ask whether the structure has changed: new directors, members who have converted, or a new holding company.
• Make sure sales, operations and debtors staff pass on any change they notice, such as a new logo, name or signature.
• Update the master file and the aging before the next invoice or statement goes out.

Q7: Why do duplicates, stale records and mismatched entities creep in?

Usually through pressure and process gaps rather than carelessness. Common causes are urgent onboarding, branches and divisions each opening their own accounts, system migrations, name variations (one person creates “STD Bank”, another creates “Standard Bank”), a customer genuinely registering a new entity, and having no duplicate checks. On top of that, every record decays: phone numbers stop working and emails bounce.

What to do:

• Train credit controllers to ask questions when something looks different, such as a new company name, signature or email footer. Have they changed name or been bought out?
• Check customer details on a regular basis, not only at onboarding.
• Run a duplicate check before any new account is created.

Q8: How does poor master data affect risk reporting and compliance?

Duplicate or unlinked accounts distort exposure by group, concentration risk, aging and escalations, provisioning and bad debt write-offs. If several companies in your group trade with the same buyer under different names, you will never see your total risk. A board report on total exposure to one customer will also not agree with sales figures if the legal entities are not linked correctly, and your credit control team is left to explain the difference. There is a compliance angle too: POPIA, FICA, record keeping for an audit trail and data subject requests all depend on knowing exactly who you hold information about.

Q9: What is “cleaning from the back” and why is it risky?

It means tidying the aging by allocating payments and credit notes in whatever way clears the problem, instead of in line with what the customer actually paid. Sooner or later a customer will ask where invoices they have paid have gone, or why invoices they paid are still showing as 120 days overdue. You have also distorted your overdue statuses, and your DSO and collections can look better than they really are, hiding poor collections performance or training gaps.

What to do:

• Apply credit notes and payments on time.
• Allocate payments according to the remittance advice.
• If a customer does not send remittance advices, agree the allocation with them by email so you always have something to go back to.

Q10: How do I verify a new customer before I start trading?

Verify the legal entity before anything is captured: the registered name, registration number and VAT number, checked against CIPC, ideally before the account is set up and before the details go into Trade Shield. Use the registration number and VAT number together, as a participant in the session also pointed out. A credit application on its own is not verification.

What to do:

• Compare the credit application with the bureau report: name, registration number, VAT number, address and bankers.
• Confirm you are looking at the company itself and not a division or branch.
• Watch for trade names that closely resemble the legal entity of a large, well-known business.
• Do not assume a registration number’s age shows how long a company has traded. For larger limits, support the decision with financial statements, bank statements and bureau reports.
• If a customer says details have changed but CIPC still shows the old ones, they have probably not yet updated CIPC. Wait for the update.
• Record in your credit policy what you collect, why, who must get it, how it is verified and how often.

Q11: Are trade references and bank codes enough to assess a customer?

They still have a place, but measured payment behaviour is far more reliable. When you phone for trade references you tend to get short, unsubstantiated answers: terms and limits are “confidential”, and “they pay on time” means different things to different businesses (five days after month end for one, the last day of the month for another). Payment behaviour measured from actual aging activity, such as Trade Shield’s payment risk, gives a more accurate picture, and it is faster and easier to obtain.

Q12: What practical checks can I run without a data project?

You can start today with a spreadsheet. Run these checks on your master file and fix what you find before you carry on trading.

Checks to run:

• Duplicate registration numbers across accounts.
• Fuzzy name matching, to find the same customer captured under different variations of a name.
• Completeness of key fields such as registration number, VAT number and contact details.
• Dormant accounts that still carry live credit limits. A customer in trouble elsewhere may suddenly buy from you.
• Limits set against group structures, so you can see total exposure.
• Red flags in documents, such as financial statements for a Pty Ltd that refer to “members” instead of directors, or an aging file showing a Pty Ltd name with a CC registration number.

Q13: How do I build data hygiene into everyday work?

Make it part of the process rather than a project. Prevention costs minutes, while correction costs hours, so spending two extra minutes at capture is always cheaper than fixing the problem later.

What to do:

• Use an onboarding checklist so the right information is captured correctly from the start.
• Give the data an owner. Whether it is the credit controller, the debtors clerk or the salesperson, someone must be accountable for it.
• Make sure everyone who interacts with the customer, from debtors and admin staff to operations and delivery teams, reports any change they notice.
• Keep your credit policy and credit application up to date, and revisit the basics regularly.

Need more help?

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