A credit limit approval process for B2B that sales and finance both trust

In most B2B businesses, credit is where sales and finance meet, and not always happily. Sales wants a quick yes so the order can ship. Credit control wants to avoid the next bad debt. The customer just wants to know where they stand.

A clear credit limit approval process takes the heat out of that conversation. Here is how to build one.

Why credit decisions go wrong

The same few problems come up again and again:

• Limits are set once at account opening and never reviewed
• Requests for more credit arrive by email and sit in someone's inbox
• The rules live in the head of one experienced credit controller
• Different people give different answers to the same request
• Nobody can say later why a limit was raised, or who agreed it

None of these are about bad people. They are about a policy that was never written down in a form anyone else can use.

The building blocks of a credit limit approval process

1. The facts you need

Decide which facts feed the decision. Typical ones are:

• Requested limit and current limit
• Trading history, such as months as a customer
• Payment behaviour, such as average days to pay and overdue balance
• External risk score, if you use a credit reference agency
• Security, such as a personal guarantee or credit insurance
• Sector or country risk

Keep the list short. Every fact you add is one more thing someone must find before they can decide.

2. Risk bands

Group customers into a small number of risk bands, based on those facts. For example: low, standard, elevated and high. Each band gets a maximum limit that can be approved automatically.

3. Approval tiers

Then decide who can approve above the automatic limit. A simple pattern:

1. Within the automatic limit for the risk band: approved straight away
2. Up to a set multiple of that limit: credit controller
3. Above that: finance manager
4. Very large or high-risk: finance director

4. Hard stops

Some cases should never be approved automatically, whatever the numbers say:

• The account is on credit hold
• There is an overdue balance above a set amount
• The customer is in a restricted country or sector
• The external score has dropped since the last review

Write these as short, unambiguous rules. They are the ones an auditor will ask about first.

Make the process fast for sales

A credit process that takes three days will be worked around. Aim for most requests to get an answer at the point of order, from the system, without anyone opening an inbox. Save human judgement for the cases that really need it.

That means the rules must be callable. Your ERP or CRM should be able to ask "can this customer have this limit?" and get an answer back straight away, with the reason.

Make it safe for finance

Speed is only safe if you can see what happened. For every decision you want:

• The facts that were used
• The rule that gave the answer
• The version of the policy that was live on the day

With that, a disputed decision becomes a two-minute conversation instead of a forensic exercise.

Keep the numbers where credit can change them

Risk bands, automatic limits and restricted sectors change. When they live in code, every change waits for a developer. When they live in a spreadsheet, nobody else can call them, and nobody is sure which copy is current.

Hold them in a table that the credit team owns, separate from the logic. Change a band, test it against recent requests, and publish.

How Condexa helps

With Condexa, the credit policy becomes a visual workflow the credit team can read. Risk bands and limits sit in lookup tables, which can read live from SQL Server or Dataverse, so the decision uses current payment data. You test with real customer examples and read the trace before publishing. Your ERP or CRM calls the Active version over a REST API and gets an answer in milliseconds.

Every call is kept in run history with its inputs, outputs and trace, so when a customer or an auditor asks why a limit was refused or approved, you can show them.

Next steps

Explore the credit decisions use case, or read about the risk of tribal knowledge in credit teams. Then see your own credit decision running in 30 minutes.