Portfolio Reporting
AI drafts monthly reports for boards, investors and capital partners. Your finance team approves them.
See how it worksIndustries · Financial Services · Portfolio intelligence workflow
Know how your portfolio will perform.
Your team spends days each month building the same portfolio reports. We help them deliver trusted reports faster, with more time for analysis.
The problem
Where the portfolio intelligence workflow slows down.
Each month, the same numbers are pulled, checked and explained by hand.
Track
Vintage and concentration reports are rebuilt by hand each month.
Forecast
Loss forecasts run in spreadsheets on partial data.
Explain
Allowance and variance write-ups take days each quarter.
Report
Board and investor packs are assembled from many files.
A trusted monthly report frees your team for analysis. That is where we start.
The workflow
One workflow, four agents, built one at a time.
A workflow is a chain of stages, and each stage needs its own AI agent. Portfolio intelligence has four stages, from tracking performance to the final report. We map the agent each stage needs with your team. We build the first agent, take it live, then add the next.
- 1
Map the workflow
We walk through each stage with your team and name the agent it needs.
- 2
Build agent 1 and go live
We build Portfolio Reporting first, test it on last quarter's reports and take it live.
- 3
Add the next agent
Each new agent reuses the same data, rules and templates, so it goes live faster.
The four agents in the portfolio intelligence workflow
Portfolio Performance
AI tracks vintage, segment and concentration, and explains what changed. Your analysts review it.
Loss Forecasting
AI forecasts CECL losses by vintage and segment. Your risk team approves them.
Allowance Narratives
AI drafts the quarterly allowance write-up. Your CFO signs off.
Agent 1
Portfolio Reporting
Every monthly report drafted from one trusted set of numbers. Your finance team approves each one.
Each figure links to its source, so reviewers can check it fast.
Loan, payment and loss dataFrom your data foundation
AI agentDrafts the report and commentary
Finance approvesEach report, before it goes out
Board, investors and partnersEach in their own format
- 1
Gather
Pulls the month's loan, payment and loss data.
- 2
Check
Compares each figure with last month and flags large changes.
- 3
Draft
Writes the report and commentary, with a source for each figure.
- 4
Review
Your finance team checks the draft and approves it.
- 5
Publish
Sends the approved report in each audience's format.
Every figure links to its source, and every change is logged.
Use cases
What one set of portfolio numbers makes possible.
Each measure is defined once, so every team uses the same numbers. Each card shows the data it needs.
Vintage tracking
See how each origination year performs against plan.
NeedsLoansPayments
Concentration limits
See exposure by product, region and borrower type against your limits.
NeedsLoansLimits
Examiner requests
Answer regulator and auditor questions from the same numbers.
NeedsLoansGeneral ledger
Investor data requests
Answer capital partner questions from one source.
NeedsLoansServicingPayments
Account-level actions sit in Collections. Built on the customer and loan data foundation ›
Banks, credit unions and lenders
What this workflow can deliver
Typical results for portfolio reporting and analysis, based on industry averages.
Typical
50%
Less time on monthly portfolio reports
Typical
2 days
Faster quarter-end close
Typical
30%
Less time on allowance write-ups
Typical
Every figure
Traced back to its source
We will add measured client results as the work goes live.
Questions
Questions finance and risk leaders ask us.
Do we need all four agents?
No. Each agent works on its own. We map all four so they share data and rules. Then we build them one at a time, fastest payback first.
Does this score individual customers?
No. It works at the portfolio, vintage and segment level. Account-level actions sit in our collections workflow.
Loan system and reporting vendors offer AI. Why build ours?
Vendor tools see only their own system. Ours works across your loan, finance and risk data. You own the agents, and every figure traces to its source.
Does this work for non-bank lenders?
Yes. Most US lenders reporting under GAAP follow CECL. All report to boards or investors.
Which systems do you work with?
Your loan servicing system and general ledger, on your data platform.
Where does our data live?
In your own environment, on your platform.
Get started
Find where AI pays back first in finance and risk.
4 minutes
AI Readiness Diagnostic
Ten questions about your data, systems and teams. You get a score and a clear place to start.
Take the AI Readiness DiagnosticDownload a sample report ›2 to 3 weeks
Data Readiness Assessment
Our data engineers score your data and give you a ranked plan for the first projects.
Book a Data Readiness AssessmentDownload a sample report ›5 days
AI Use Case Prioritization
Your AI ideas scored and ranked, with the right agent, model and size for each.
Book AI Use Case PrioritizationDownload a sample report ›