All work Case Study Commercial Credit AI Decisioning
Credit Scorecard

A credit decision,
reasoned end to end
in one surface.

We built an AI-powered credit risk scorecard that fuses trade-credit signals, rating-agency intelligence, and real-time news into a single underwriting view — so a credit analyst can see, understand, and defend a limit recommendation in under a minute.

Client Commercial credit team
(confidential)
Domain B2B trade credit
underwriting
Built on Alera — agents,
flows & web UI
Timeline Weeks,
not quarters
Credit scorecard header: $750,000 suggested credit line, 24-month score trend chart, R+ Rating of 57 with low confidence, and a flagged risk advisory.
The Problem

Credit analysts were making
seven-figure decisions with
scattered evidence.

A commercial credit team was extending terms to hundreds of accounts. The data existed — trade experiences, rating agency reports, payment aging, public news — but lived in a half-dozen systems.

An analyst opening a file saw raw numbers. The reasoning that connects those numbers to a limit recommendation happened inside someone's head, on a scratch pad, or in a review meeting. Decisions were defensible but slow, inconsistent across analysts, and almost impossible to audit months later.

Worse, the signals that actually mattered most — a rating agency downgrade, a sudden past-due spike, a news report about an unsustainable capital structure — were the hardest to surface. They arrived after the limit had already been set.

The team didn't need a new database. They needed a decision surface: a single page that shows every relevant signal, weighs it, explains itself, and proposes a limit an analyst can accept, adjust, or override.

The brief

Give a credit analyst one page, per account, where the suggested limit, the reasoning behind it, the scenarios around it, and the evidence supporting it all live together — and make it fast enough to review the entire book in a morning.

What We Built

Five views of the same decision,
stitched into one page.

Every account rolls up to a scorecard with a recommended credit line, a confidence-adjusted rating, and four drill-downs that explain exactly how the system got there.

01

Recommended Line

A single suggested credit line with a range, a confidence indicator, and the headline reason — visible above the fold, alongside a 24-month score trend.

02

Factor Breakdown

Seven weighted factors — payment score, 12-month high credit, past-due, profitability, tenure, balance sheet strength, UCC filings — each with its own AI-generated analysis and optional manual override.

03

Scenario Analysis

Four pre-modeled scenarios (Restrictive, Conservative, Moderate, Aggressive) with dollar limits, expected loss estimates, and the specific conditions each requires.

04

Trend & Signals

A 24-month score trajectory annotated with flash alerts, paired with risk flags and positive signals pulled from the underlying data.

05

News & Intelligence

Sentiment-tagged news events with cited sources — so a material-negative article from Fitch or S&P is visible on the same page as the trade credit recommendation.

06

Evidence & Terms

Flash alerts, payment aging, key metrics, suggested payment terms with conditions, and a document vault — all cross-linked to the reasoning above.

Deep Dive · Factor Breakdown

A score that explains itself, not a black box.

The headline rating isn't a number from a model nobody can audit. It's a weighted roll-up of seven factors — each scored independently, each explained in natural language, each overridable.

Every factor has a weight (in points), a score out of 100, and a weighted contribution to the final rating. Analysts can click any factor to expand the full AI-generated analysis, see the underlying fields the model looked at, and type their own override if they disagree.

Factor Breakdown tab showing seven weighted scoring factors — Payment Score 13.6, 12-Month High Credit 8.5, % Current and Past Due 8.4, Profitability 7.2, Years in Business 7.0, Balance Sheet Strength 6.8, UCC Filings 5.2 — each with progress bars. Flash Alerts panel on the left, Payment Aging chart and Key Metrics on the right.
Factor Breakdown tab. Seven weighted factors roll up to a single R+ Rating. The surrounding panels — Flash Alerts, Payment Aging, Key Metrics — are visible on every tab so context never disappears.
Annotated version of the Factor Breakdown explaining each element — unified score, individual field analysis, optional manual override, score out of 100, weight, weighted score. The Payment Score factor is expanded to show the full narrative analysis.
The anatomy of a factor. Every factor exposes its weight, its score, its weighted contribution, the fields it reasoned over, and a written summary — plus editable override fields for the analyst.
Why this matters

Most credit models are opaque. This one is a receipt. If an analyst accepts the recommendation, they can defend it. If they override it, the override is captured alongside the original reasoning — and the next review cycle learns from it.

Deep Dive · Scenarios

Four limits.
Four different risk appetites.

The system doesn't hand an analyst a single number and walk away. It proposes four credit lines — Restrictive, Conservative, Moderate, Aggressive — each tied to a specific set of conditions the business would need to accept.

One is flagged as the recommendation. The others are one click away. Each scenario includes an expected loss estimate, suggested payment terms, and the guardrails that would be required if the business chose to extend that much credit.

Scenario Analysis tab showing four scenario cards: Restrictive $400,000, Conservative $750,000 (recommended), Moderate $1,000,000, Aggressive $1,500,000. The Conservative scenario is expanded to show it limits exposure to approximately 36% of 12-month high credit, with Net 15 terms, 6% expected loss, and five specific conditions including monthly credit review, immediate investigation of the past-due spike, and required personal guarantees for single orders exceeding $250,000.
Scenarios tab — Conservative selected (recommended). $750,000 at Net 15 with monthly monitoring, 6% expected loss, and five explicit conditions. The recommendation is pre-selected but the analyst can freely switch scenarios.
Scenario Analysis tab with the Moderate scenario selected, showing $1,000,000 at Net 20 terms with 10% expected loss and four conditions including monthly monitoring, past-due resolution thresholds, automatic holds on balances aging beyond 45 days, and credit insurance recommended for exposure above $500,000.
Moderate scenario. Switching scenarios rewrites the terms, the expected loss, and the conditions — so the trade-offs of each posture are immediately visible.
Deep Dive · Trend & Signals

A 24-month story,
not a month-end snapshot.

Credit risk is a trajectory. The Trend & Signals tab plots the account's trade credit score over the last two years, annotates every flash alert on the timeline, and pairs the chart with explicit risk flags and positive signals pulled from the same underlying data.

Every annotation on the chart is hover-expandable, linking back to the source alert. Risk flags and positive signals are generated from the live dataset — not from a report someone wrote six months ago.

Trend and Signals tab with a 24-month line chart titled 'Trend: Recovering', tracking scores from a pre-crisis peak of 94 through a trough of 23 in March 2025 and recovery to 92 in February 2026. Flash alert markers are plotted along the timeline. Below the chart are two columns: Risk Flags listing four concerns and Positive Signals listing four supporting data points.
Score trajectory with inline alerts. Every red marker is a flash alert on the timeline. The story — crisis, trough, restructuring, recovery — is visible in one glance.
Same trend chart with a flash-alert tooltip expanded for HMS Mfg. Co., showing the Final Demand 30-day letter sent in May 2025 and explaining that it indicates unresolved payment issues approximately nine months prior and was the most recent alert around the time of the restructuring.
Drill into any marker. Hovering an annotation surfaces the underlying flash alert in plain language — with dates, amounts, and the source vendor.
Deep Dive · News & Intelligence

Trade credit data
meets the outside world.

Trade credit numbers tell you how a customer has paid you. They don't tell you Fitch just flagged the company as distressed. Our News & Intelligence agent pulls public news, rating agency actions, and material filings — classifies each event as positive, neutral, or negative — and summarizes what it means for the trade credit recommendation.

Every event is timestamped, sentiment-tagged, and cited. Analysts can expand the sources, read the original article, and see the specific sentence that triggered the alert.

News and Intelligence tab showing the executive summary narrative and a list of news events. The first event, 'Major Credit Agencies Flag Gabe's as High Bankruptcy Risk' is tagged MATERIAL NEGATIVE and summarizes that Fitch, Moody's, and S&P all flag distressed levels with default expected within 12-24 months. Red annotation arrows indicate that clicking the advisory at the top takes the user to the News and Intelligence tab.
News & Intelligence tab. A top-level advisory in the header deep-links straight to the relevant news event below, so critical outside signals are never more than one click away.
Same News and Intelligence tab with the sources for the first event expanded — showing two underlying sources, Retail Dive and TheStreet, each with the specific paragraph and quote that was extracted as evidence.
Every claim is sourced. Click a source count and the underlying articles unfold inline — with the exact quoted passage the AI relied on — so nothing is unverifiable.
Deep Dive · Evidence & Terms

A decision isn't done
until the terms are written.

Every scorecard closes with the paperwork: suggested payment terms, explicit conditions, flash-alert history, payment aging, and a document vault with direct links to the credit application and any supporting files on record.

The suggested terms aren't generic. They're generated from the selected scenario — so if the analyst switches from Conservative to Moderate, the suggested terms and conditions rewrite themselves accordingly.

Bottom half of the scorecard showing Risk Flags and Positive Signals side by side, a Flash Alerts panel with four negative alerts for HMS Mfg. Co., Footwear Unlimited, Clarks Americas, and Outdoor Recreation Group, a Payment Aging chart, a Key Metrics panel comparing my experience with industry data, a Suggested Terms block with Net 15 Conservative Enhanced Monitoring and monthly review cadence, and a Document Vault table with a link to the Credit Applications on file.
The full supporting dossier. Flash alerts, payment aging, key metrics, suggested terms with conditions, and a document vault — all on the same page as the recommendation that relies on them.
Under The Hood

Seven agents.
One scorecard.
Built on Alera.

The scorecard looks like one document. Behind it, a small choir of specialist AI agents each own a slice of the reasoning — and their outputs are stitched together into the final view by Alera's agent orchestration and flow optimization pipeline.

  1. 01

    Factor agents score each dimension

    One agent per factor. Each one has a narrow job — score Payment, score Past Due, score Balance Sheet — and each one writes its reasoning in plain language so the output is auditable.

  2. 02

    A news agent curates the outside signal

    A research agent queries public news, rating agency releases, and filings, classifies each event, extracts the citation, and flags anything that contradicts the internal trade credit trend.

  3. 03

    A scenario agent models the limits

    Given the factor scores and the news signal, a scenario agent produces four calibrated options — each with a dollar limit, expected loss, and set of conditions the business would need to accept.

  4. 04

    A summary agent writes the headline

    A final flow composes the executive summary — the narrative that ties the R+ rating, the recommended line, and the dominant risk factor together into the first thing an analyst reads.

  5. 05

    Alera keeps the agents in sync

    The whole pipeline runs on Alera — our AI-native platform. Agents invoke each other, flows version themselves, grading rubrics score the outputs, and the optimization pipeline improves the prompts over time without manual tuning.

Results

What the team got.

1 page

per account — recommendation, reasoning, evidence, and terms in a single surface

< 60s

to review a file, accept the recommendation, or override with captured rationale

4

scenario models per account — the trade-offs of each risk posture always visible

100%

of recommendations cite their sources — every claim traceable to a field or article

Work With Us

If your team is making decisions
with scattered evidence,
we can fix that.

The Credit Scorecard is one of many systems we've built for clients on Alera. If you've got a decision-heavy workflow that needs to collapse into a single, defensible surface, let's talk.

Start a conversation See the platform