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September 25, 2026 Content Type Case study

Strengthening pipeline governance and deal data integrity across the investment lifecycle for an alternative asset manager

September 25, 2026 Content Type Case study
 

    Background

     

    A leading global alternative asset manager was looking to strengthen data governance across its private credit investment platform. The client required an adaptable Governance framework capable of delivering high-quality and reliable pipeline data. The objective was to provide precisive pipeline view to enable assessment of investment timelines, allocation and liquidity positions.

    Challenges

     

    Data breaks and inconsistent deal information between Investment Committee memorandums and central deal management platforms were impacting deal flow data accuracy and operational efficiency.

    Our solution

     

    Established strong pipeline data controls:

     

    • Formulated a structured data review process to verify accuracy of the deal pipeline data across the stages.
    • Created governance checkpoints to ensure timely incorporation of allocation updates from investment allocation teams, reducing information latency.
    • Conducted independent validation of key metrics, including leverage, loan-to-value, interest coverage, and debt service calculations versus the underlying financial assumptions; flagged any discrepancies with the relevant teams.
    • Introduced standardized data templates providing sections of missing data, to accelerate issue resolution and improvise teams’ ownership.

     

    Streamlining pipeline dataflow and management reporting

     

    • Developed a reporting framework, with Sigma-based stage-level pipeline tracker to cover full investment cycle from screening to final closing, which captured data breaks and deal progress
    • Presented weekly data health statistics providing realtime visibility into data gaps and the concerning deal information.
    • Produced monthly and quarterly management analytics with commentaries about lagging deals and bottlenecks which allowed the senior leadership to proactively address quality risks.

     

    AI-led quality enhancement

     

    • Deployed AI-based Agents for extracting critical deal metrics from IC memorandums, term sheets, commitment letters, and supporting credit documentation.
    • Instituted a validation mechanism for accurate reconciliation of the transaction structure, sources and uses, debt hierarchy, pricing mechanics, maturity and amortization, covenant package, collateral coverage, guarantees, and allocation terms.

    Impact

    Reduced the average deal-level data errors and data breaks to near-zero from approximately 40-50% at the final closing pipeline stage.

    Increased field-health metrics improving to 99% upon funding, from roughly 70% at early-stages.



    Improved the speed and consistency of pre-closing reviews by systematically identifying material deviations from approved investment cases.

     

    Created a review trail by linking validated pipeline fields to source documents, ensuring traceability and audit readiness.

     

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