AI Diligence and Loan Monitoring for a PE Fund

Key results

20-30 hours

of analyst time reclaimed per deal

~70%

less manual payment reconciliation

~$150K-$225K

in modeled annual labor value

ai for pe fund

Summary

An American mid-market private equity fund was looking to speed up acquisition diligence and catch borrower issues earlier without adding more manual review.
The time spent on turning data-room files, loan schedules, and bank activity into review-ready questions and exceptions felt like a bottleneck for the company.
Cooperation Period
Ongoing
Location
USA
Industry
Finance
Service Provided
AI Automation
mortgage execs

Business Challenge

The deal team reviewed large data rooms on tight committee timelines. Documents were missing, outdated, duplicated, or inconsistent across financial statements, tax records, bank data, loan files, and management spreadsheets.


Questions about revenue quality, EBITDA add-backs, related-party transactions, tax exposure, customer concentration, and debt obligations often surfaced late, after significant analyst time had already been spent.


The fund needed a single workflow that could turn this entire mix of files and transaction data into structured review queues, with a clear audit trail for every flag.

What We Did

  • 1

    Acquisition Diligence Workflow

    For each new deal, the agent runs a first-pass review of the full data room:

    • Indexes every file, from audited statements to one-off management spreadsheets
    • Checks for missing documents, outdated versions, duplicates, and conflicting figures across sources
    • Extracts evidence on revenue, EBITDA, working capital, debt, and tax exposure
    • Links every extracted figure and flagged item to its source document and page
    • Organizes open diligence questions by risk area
  • 2

    Private-Credit Monitoring Workflow

    The system connects loan agreements, amendments, payment schedules, borrower communications, and bank activity, and as new data arrives, continuously:

    • Builds and updates expected-payment records by borrower, due date, interest, fees, and status
    • Matches expected payments against actual deposits and withdrawals
    • Flags short pays, late pays, missing reports, unidentified deposits, unusual fees, and related-party transfers
    • Routes each exception to the right reviewer
  • 3

    Scope and Controls

    • Raw files stay unchanged; agent outputs are versioned separately
    • Every extracted figure and flag links back to the underlying document
    • Assumptions and unresolved questions are labeled, not presented as findings
    • Final tax, legal, accounting, credit, and investment conclusions stay with qualified professionals

Project Results

What changed since launch:

Diligence starts from a complete picture
The first-pass output arrives with missing files, outdated versions, conflicting figures, and open questions already organized by risk area, each with a source link.
Issues surface while there’s still time to act
A short pay or a missing quarterly report now appears as a flagged exception within the same week the data arrives.
Analyst attention goes only to unresolved items
Clean matches pass through without review. What lands in the queue is the deposit with no matching schedule, the short payment, the unexpected fee, the missing report.
CPA and controller handoffs got cleaner
Principal, interest, fees, reimbursements, and related-party transfers arrive separated for professional review, supporting documents attached.