Solution
For portfolio managers, CROs, and credit risk teams at banks and private lenders: current, source-cited answers to exposure and covenant questions across the whole book.
The problem
Portfolio reports are assembled by hand from documents someone read weeks ago — accurate the day they were built, out of date the day they are presented.
Exposure lives in one spreadsheet, covenant status in another, ratings in a third. When the board asks which one is right, someone spends a night finding out.
Covenant tightening surfaces at the annual review, long after the financial package that showed it arrived.
The product, not a promise
How it works
Pull spread financials, covenant results, ratings, and loan terms from across the portfolio.
Put every obligor on the same definitions so exposures and metrics actually compare.
Compute concentration by sector, geography, and obligor; track covenant health and rating drift.
Produce board, investor, and regulatory views where every number carries its citation.
Who it's for
Portfolio manager
Chief risk officer
Head of regulatory reporting
Portfolio questions are simple to ask and expensive to answer. What is our exposure to this sector? Which borrowers are trending toward covenant breach? How does this quarter’s book compare to last year’s? In most institutions the answer lives in spreadsheets assembled by hand from documents someone read weeks ago — accurate the day they were built, stale by the time they are presented.
Botminds builds portfolio reporting on data it has already extracted and cited: spread financials, covenant calculations, loan terms, risk ratings, and reporting packages collected across the book. Every obligor’s data is normalized to the same definitions, so portfolio-level aggregation is trustworthy — concentration by sector, geography, product, and single-name exposure computes from comparable numbers rather than reconciled approximations.
Covenant health rolls up the same way. Instead of learning about deterioration at the annual review, the portfolio team sees which borrowers are tightening against their thresholds as each new financial package lands. Comparative views — this obligor against its peers, this vintage against the last, this quarter against the trend — come from the same governed base, so the comparisons hold.
The difference between a dashboard and a portfolio report is what happens when someone challenges a number. Here every figure in every view traces back through the calculation to the source document and page it came from. Reports for the board, investors, or a regulator are reproducible on demand: same data, same definitions, same citations. Analysts spend their time on the exposures that need judgment — and the judgment, as everywhere on the platform, stays human, made with the evidence already assembled.
Objections, answered
Citations survive aggregation. Any figure in any view drills through the calculation to the source document and page it came from, and extractions the platform is less confident about are flagged for review before they enter the rollup.
Yes. Normalization maps every obligor to your definitions — your exposure formulas, your covenant calculations, your chart of accounts. The point is comparability on your terms, on a fixed external taxonomy only if you choose one.
Reports are reproducible on demand: same data, same definitions, same citations on every rerun, with the record of who reviewed what. An examiner challenging a number gets walked to the source page, not to a spreadsheet archaeology exercise.
Reporting builds on the spreads, covenant results, and loan terms Botminds extracts, so views stand up as the document base does — no data warehouse project first. It deploys in Botminds cloud, private cloud, or on-prem.
Watch it answered live — concentration, covenant health, or peer comparison — with every figure cited to the source document.
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