Report · PCT-012 · Sourced card · live demo
Maturity wall by BDC
An insurer's credit team wants to know how much of each BDC's book comes due by 2028, and in which sectors.
Today vs automated
- Open each 10-QAnalyst · manual
- Copy maturity datesAnalyst · manual, re-keying
- Bucket by year by handHead of research / IR · manual
- Email / meeting hand-offAnalyst → Head of research / IR
- Quarter-end, or a new filing is publishedTrigger: starts on its own
- Read every maturity tagAutomated · Data store
- Bucket by yearAutomated · LLM
- Show where it concentratesAI draft, human review · Reporting template
- What refinancing risk this really means for each nameApprove / override · Head of research / IR
AutomatedAI draft, human reviewHuman onlyTools: Filing feeds, Data store, LLM, Reporting template
Estimated valueestimate
12–90 analyst hours a year
$2k–$22k of time, vs an assumed $10k–$40k tool cost
Net: −$38k to $12k a year net of tool cost; at the low end of the assumptions it does not cover the tool cost.
Assumptions
- 4–8 analyst hours per quarterly review today; 0.5–1 hours with an agent, including review
- 4–12 quarterly reviews a year for one team
- $150–250 per hour loaded cost
- Tool or build cost $10,000–40,000 a year (in-house)
Estimate, based on the assumptions shown; your numbers will differ. How we estimate
What else it can do for the team
- Overlay your own book's maturities
- List names maturing within 18 months
- Flag maturities with weak marks
- Draft the refinancing-risk note
- Track extensions quarter to quarter
How you get thereFour steps from prompting to an agentic workflow; most teams start at step 2.
Needs: an approved AI tool, a confidentiality policy.
Risk: unchecked answers, data pasted outside policy.
Needs: field definitions, a template, document parsing.
Risk: breaks silently when formats change.
Typical starting point
Needs: inbox/doc-store access, system write-back, logging.
Risk: acting on a misread; needs review gates.
The automated lane above
Needs: shared data model, permissions, audit trail, exception queue.
Risk: errors compound across steps; needs monitoring.
Solution optionsBuy (3 vendors listed), build or hybrid, with the trade-offs of each.
An LLM API, a document parser, a vector or document store, your data warehouse, and a review queue.
Fits your definitions exactly; you own maintenance and controls.
Vendor extraction feeding your own checks, templates and systems.
Common middle path; two things to integrate and govern.
Listing is not endorsement.
What changes for the team4–8 h → 0.5–1 h per quarterly review (estimate); coverage goes from the names someone had time to pull to the full set, refreshed when sources change.
How it works
Full title: The 2027–28 maturity wall, BDC by BDC, and which borrowers can't refinance at today's rates
“Here is how much of each big BDC's book comes due by 2028.”
This card now includes former PCT-026 (Refi or extend? A CRE loan book tested against today's rates, loan by loan).
Scenario
Public: an insurer's credit team wants to know how much of each BDC's book comes due by 2028, and in which sectors.
What the human still decides
What refinancing risk this really means for each name.
Why it matters
PitchBook LCD: more than a third of the top BDCs' book is due by 2028, with software and PIK debt prominent.
What the record shows
Checked 2026-10-15.
Across 10 BDCs' 30 Jun 2026 SOIs, only 8.5% of dated fair value ($6.7bn of $78.1bn) matures in the next 24 months, so the wall is not an aggregate problem. It is concentrated: GSBD has 32.6% ($0.93bn) due within 24 months, BCSF 22.2%, PFLT 20.2% and MSDL 20.0%. The workflow is to find those names and check refinancing paths, not to chart the total.
Try it: prompt and data
From the SOI rows for {quarter}, bucket principal by maturity year (≤2026, 2027, 2028, later) per BDC and by sector. Flag PIK and software rows. Output a table and chart with filing links.Data
Public inputs only (SEC/EDGAR filings, published methodologies, public signals). Every figure is cited.
Who uses it, vendors and build
- Segments
- BDCs, Research & ratings
- Who uses it
- Credit analyst, LP / credit research
- Build
- Buildable in-house
- In-house
- Simple aggregation on the SOI pipeline. Estimate: 2–3 days.
- Last verified
- 2026-10-15
Vendors that claim this capability
Tags reflect each vendor's own public claims at the linked page (checked 2026-10-15). Not tested, ranked or endorsed.
Sources and related
Next step
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Not investment advice. Names marked SAMPLE are fictional. Found an error? See the corrections log.