B2B credit risk management where the agents watch every customer and you sign every limit
Bad debt kept down without blocking good orders, every limit change cited and signed.
See one case, screen by screen ↓B2B credit risk management software reviews customer credit files, sets credit limits and flags deterioration before it turns into bad debt. B2B Credit Risk Management puts eight agents on every customer every night: they read payments, liens, filings, bureau and insurer notices and news, re-score the customer, propose a limit with a cited memo and test it against your credit policy. The credit manager decides and signs.
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A seller on 30- to 60-day terms is lending to thousands of business customers, yet most limits are set at onboarding and looked at again at the annual review. The warning signs arrive in a dozen places: slower payment in the aging, a blanket lien filed by a new lender, going-concern language in a quarterly report, a plant closure in the local press, a credit insurer cutting cover. Bureau alerts land in one analyst's inbox, news is noticed by chance, and a 10-Q note is rarely read at all.
Meanwhile good customers' orders sit on credit hold behind stale limits, and analysts spend their mornings releasing them by hand. When a limit does change, the memo is rewritten from scratch, the approval happens by email, the ERP is updated by hand and sales hears last. At quarter end the controller and the auditors ask for the support behind large limits and the forward-looking part of the allowance, and it is spread across email and spreadsheets.
Estimated split for one limit decision on a mid-size trade account, by hand and with the solution.
Eight agents watch every customer nightly, re-score, propose a cited limit and check it against your policy; the credit manager signs.
Tarrant Steel Fabrication of Erie, Pennsylvania, has bought plate and coil from Kestrel & Vane Metals Distribution since 2014 — about $3.1M a year on Net 45, with a $500,000 limit set at its March review. In twelve days it had a blanket lien, a going-concern note and an idled production line. Here is how Helen Ward, the credit manager, works it with the agents in one conversation, screen by screen.
Helen opens Tarrant Steel's credit file. The dial shows exposure of $479,660 — 96% of the $500,000 limit, $20,340 of headroom — and a blue tick at the proposed $350,000. Six signals sit around it. Beside the dial, the credit team has already written to her: 37 signals on 35 customers overnight, 9 re-scored, 6 decisions waiting, Tarrant first.
Credit lead: “Four warnings in twelve days — a blanket lien, going-concern language in its quarterly report, a production line idled, and last night days to pay reached 67.”
Helen clicks the quarterly report signal. The 10-Q for the quarter to 31 August opens at Note 2, with the passage the agent used highlighted: a net loss of $6.8 million for the nine months and a breach of the fixed charge coverage ratio on the revolving facility. Note 7 describes a waiver from its lenders to 15 December.
“These conditions raise substantial doubt about the Company's ability to continue as a going concern.”
The recommender proposes cutting the limit from $500,000 to $350,000: eight weeks of expected purchases after the line idles, under the class D cap of $390,000. Ship while past due over 30 days stays below $25,000, and re-review on 15 December when the lenders' waiver ends. The memo has six sections, every statement cited, and 11 sources quoted — the UCC-1 filing, the 10-Q notes, the aging, the bureau report, the credit group report and Credit Policy CP-7.
Each paragraph can be edited, or the recommender asked to rewrite it; every edit is a new version.
The policy checker works on its own, rule by rule, against Credit Policy CP-7 revision 2026.2. Within the approver's authority, under the class D cap, inside the going-concern cap of 8 × $45,000, a lien re-review 74 days after the lien, Rosa Delgado and the sales VP told of a cut over 25%, every signal sourced and no older than 30 days, recommender and approver not the same, and the open orders shown before approval: 8 of 8 pass.
“The recommender cannot overrule it.” A disagreement always goes to a person.
Helen types her question into the thread. The credit lead answers with its sources: at $350,000 Tarrant can keep buying about $45,000 a week, roughly $1.2M of orders over the next six months. Only the two open orders, $61,400, wait, and they release as soon as the $142,880 past due is paid. Rosa Delgado will be told why, in plain words, before it takes effect.
Other questions she can ask in the same place: “Why not hold everything?” · “Show the going-concern passage” · “Make it $300,000”.
On the what-if screen a slider runs from $200,000 to $600,000. At $350,000 the expected loss is $19,740, SO 7781204 ($38,900) and SO 7781266 ($22,500) hold, and all eight policy rules pass. Told in the thread to “make it $300,000”, the recommender re-proposes, expected loss falls to $16,920, and the policy checker re-tests it: still 8 of 8. She keeps $350,000.
Approve opens the decision: cut the credit limit, $500,000 → $350,000. Reason codes are required; she ticks RC-02 payment behaviour deteriorated and RC-03 public distress signals. She confirms she has read the memo and the policy check, and signs with the meaning “I approve this credit decision”.
Sign and approve stays greyed out until there is a reason code and the confirmation.
Acting on the signed decision, the hold and release agent writes $350,000 to the ERP credit master and gets it confirmed, holds the two open orders with the reason, tells Rosa Delgado and the sales vice president in plain words, schedules the re-review for 15 December with Daniel Osei, and logs evidence pack DEC-2026-10-0418 — memo v1, 11 sources, the policy test and the signature.
“Draft the letter to Tarrant's payables team — waits for you to press Send.”
Rosa sees her 46 customers with credit words replaced by plain ones. Tarrant: “Credit limit lowered to $350,000 today. Tarrant has been paying later each month and has new debts in its public reports.” Below it, what she can do — and a box to ask credit, answered by the credit team, which passes anything that needs a decision to Helen Ward.
“What you can do: Ask Tarrant to pay $142,880 that is more than 30 days late: SO 7781204 and SO 7781266 ($61,400) then ship at once.”
Rosa has asked to raise Halvorsen Building Supply from $750,000 to $1.2M for a $640,000 hospital order. The recommender proposes $1.0M, with exposure peaking near $980,000, once the owner's guarantee is renewed. The policy checker disagrees on two rules: the personal guarantee expired on 30 September and the financial statements are 14 months old. $1.2M is above Helen's authority, so it can go to Graham Whitlock, the group CFO.
Policy checker: “I disagree on two rules … §6.2 needs both for a limit above $500,000.”
The same credit decision, seen by the five people who carry it — what their week looked like, and what it looks like now.
Eight agents watch every customer nightly, re-score, propose a cited limit and check it against your policy; the credit manager signs.
Talks with the credit team: each morning summarises what changed overnight, presents each recommendation and the policy verdict, and answers questions from the credit files with a citation for every fact.
Reads the receivables ledger, aging and bank lockbox file every night: days to pay by month, past due, returned payments and remittances in transit.
Watches lien filings, court dockets and public company filings for every customer and its parent, and quotes the passage; insolvency filings go to legal at once.
Reads bureau reports, credit insurer notices, industry credit group reports and the news, and records each score change.
Re-scores a customer whenever a signal changes, lists each driver with its points and its source, and works out the 12-month probability of default and the expected loss at the current and proposed limits.
Drafts a new limit with conditions and a re-review date, writes the credit memo with every statement cited, and shows which open orders the limit would hold and what releases them.
Independently tests every recommendation against each rule of the written credit policy, with the evidence, says agrees or disagrees with its reasons, and routes the decision by the authority matrix.
After a signed decision, writes the limit to the ERP credit master, holds or releases orders with the reason, tells the sales account manager, schedules the re-review and drafts the letter to the customer.
Decides with a reason code; above $1M the CFO. The agents propose; a named person decides.
Ask about any customer, signal, hold or limit — or tell the agents what to change. Every answer points to its source, and nothing reaches the ERP until a person confirms.
Which customers got riskier this week?
Nine moved to class D or E this month; three this week stand out. Tarrant Steel, 71 → 44, after a blanket lien and a going-concern note. Ostrander Freight Lines, 58 → 9, Chapter 11 on 12 Oct. Whitcombe Electrical: its credit insurer halved cover to $250,000.
Why did Tarrant Steel's score drop?
From 71 to 44 in two weeks: the going-concern note cost 11 points, the payment trend 7 — days to pay 38 → 67 — the blanket lien 5, the idled line 2 and the bureau 2. That crosses into class D, so the recommender proposed a lower limit.
Release Larkspur's held orders
Larkspur has three orders held, $86,250; it pays in 29 days on Net 30 and a raise to $400,000 is proposed. I have selected the three orders in Holds — press Release 3 and give a reason; nothing goes to the ERP before you do.
Add a rule: re-review any customer with a going-concern note within 30 days
Added to the policy rules, waiting for Graham Whitlock's approval as policy §1.4 requires. Today it would catch 3 customers: Tarrant Steel, Lowick Medical and Quillon Marine. The policy checker tests it from tonight.
13 screens from the working solution, on its sample data. Pick one to see it large.
The agents read your written credit policy and turn it into rules you approve. Thresholds, weights, authority and service levels are settings, and every change is on the audit trail.
| Setting | Default | Choose from |
|---|---|---|
| Going-concern cap | 8 weeks of expected purchases (policy §4.3) | Step up or down, one week at a time |
| Order tolerance before an order holds | 2% over the limit | Step up or down, one point at a time |
| Re-review after a blanket lien | 90 days (policy §4.5) | Step up or down, in days |
| Signal that triggers a recommendation | Score drop of 8 points in one week | Step up or down, one point at a time |
| Scoring weights | Payment trend 30 · public filings 20 · liens 15 · bureau 15 · trade references 10 · news 10 | Must total 100; sent to the group CFO for approval |
| Risk classes by score | A 80 and above · B 65–79 · C 50–64 · D 35–49 · E below 35 | Class D cap: lower of 10% of tangible net worth or $400,000 · class E: secured or cash in advance |
| Approval authority | Analyst $100,000 · credit manager $1,000,000 · group CFO above | Credit committee above $5,000,000 · agents disagree: always a person |
| Service levels | Class change to D or E decided in 1 business day | Held order reviewed in 4 working hours · insolvency told to credit, legal and the sales manager the same hour · escalate to the CFO after 2 business days |
Every figure is labelled: a target the solution is built to, an estimate, a typical published result, or a proven one.
“demo” = seen in the working solution, on its sample data · “target” = the design goal, measured in the live solution · “estimated” = our estimate · “typical” = published figures (Atradius Payment Practices Barometer, United States 2024 — half of B2B invoices overdue, bad debts averaging 8% of B2B credit sales; Allianz Trade Global Insolvency Report, Oct 2025 — global business insolvencies forecast to rise 6% in 2025). ASC 326 and IFRS 9 are named as context only. People, companies, lenders, publications and filing numbers named on this page are fictional — characters and sample data in the working solution.
B2B credit risk management software reviews customer credit files, sets credit limits and flags deterioration before it turns into bad debt. B2B Credit Risk Management puts eight agents on every customer every night: they read payments, liens, filings, bureau and insurer notices and news, re-score the customer, propose a limit with a cited memo and test it against your credit policy. The credit manager decides and signs.
Three watchers read the receivables ledger and lockbox file, lien and court records and public filings, and bureau reports, credit insurer notices, industry credit group reports and the news. Every signal carries the passage it came from, and a news signal needs two independent sources. On the sample data they found 37 signals on 35 customers in one night.
The credit scorer re-scores the customer and explains every point it moved, with the probability of default and the expected loss. The limit recommender then proposes a limit within your policy caps, with conditions, a re-review date, a credit memo with every statement cited and the open orders the limit would hold.
The policy checker tests every recommendation on its own, rule by rule, and the recommender cannot overrule it. A disagreement always goes to a person, and a limit above the credit manager's authority goes to the group CFO with both agents' reasoning.
It proposes. The agents check payments received, remittances in transit and proposed limit changes, and mark each held order release or keep with a reason — 9 of 14 for release on the sample morning. Nothing is written to the ERP until a person confirms with a reason.
The monthly portfolio report includes an allowance note for the controller: expected loss by risk class, the forward-looking adjustment from class migrations and the change in expected loss from each limit decision, every number linked to the credit file it came from. ASC 326 and IFRS 9 both ask for forward-looking information in the allowance on trade receivables.
Yes. Agents never change a limit, release or hold an order, contact a customer or change the policy on their own. Every decision needs a reason code and an e-signature, routes by your authority matrix, and is written to the ERP only after it is signed.
The Agentic Solution Engine builds and deploys it from your requirements and documents — your credit policy, authority matrix and a sample of credit files — and it goes live once every quality gate has passed. First-time setup connects the ERP, reads your policy into rules you approve and back-tests 20 of your analysts' past decisions before the watchers start.
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1-min demoWe'll run B2B Credit Risk Management on a sample of your own credit files, against your own credit policy.