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    Asset Modelling
    Asset Modelling for Informed Investment Decisions

    A structured approach to asset data, valuation, and analysis.

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    Key Challenges in Asset Modelling Today

    Complex portfolios, fragmented data, and manual modeling slow insights and weaken confidence in real estate valuations.

    Polestar Analytics Approach to Asset Modelling

    Asset modelling combines governed assumptions with automated calculations in a unified framework for consistent valuation and return analysis across assets, SPVs, and portfolios.

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    Core Capabilities of an EPM-Driven Asset Modelling Solution
    Centralized Asset and Assumption Management

    Rental, operating, capital, and financing assumptions are handled in one organized model. This approach ensures consistency across assets and SPVs.

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    Automated Cash Flow and Debt Modelling

    Cash flows, debt schedules, and financing effects update automatically when assumptions change. This cuts down on the need for manual work.

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    Continuous Valuation and Forecasting

    Valuations and return metrics change in real time. This gives a clear view of how assets and portfolios are performing.

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    Scenario-Based Investment Analysis

    Market, financing, and exit assumptions can be tested to see how they affect returns before making decisions.

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    Governed Models with Full Traceability

    Changes, scenarios, and approvals are recorded. This helps investment committees, audits, and compliance requirements.

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    Portfolio-Level Insights for Decision-Making

    Dashboards give a clear view of how assets perform, the liquidity situation, and the expected returns across the portfolio.

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    Advanced Features of Smarter Asset Modelling
    Role-Based Modeling & Collaboration
    Role-Based Modeling & Collaboration Drives collaboration across investment, finance, and asset teams.

    • Specify who can enter, review, or approve assumptions and valuations.
    • Ensure clear ownership across assets, SPVs, and portfolios.
    • Minimize version conflicts and informal hand-offs.
    ML-Driven Forecasting and Trend Analysis
    ML-Driven Forecasting and Trend Analysis Machine learning predicts future asset performance.

    • Identify patterns in rental income, occupancy, and cash flows.
    • Support better assumptions for long-term projections.
    • Cut down on dependence on static, manually adjusted forecasts.
    AI-Powered Scenario Modeling
    AI-Powered Scenario Modeling Embedded intelligence highlights changes for proactive testing.

    • Automated alerts highlight key differences across assets and markets.
    • Instant what-if scenarios test market and rate changes.
    • Comparisons reveal risks in returns, liquidity, and debt coverage.
    Natural Language Data Querying and Analysis
    Natural Language Data Querying and Analysis Ask portfolio questions in plain language, no technical skills needed.

    • Query portfolios in plain language for IRR or debt maturities.
    • Access real-time insights without navigating multiple dashboards.
    • Enable non-technical users to extract insights independently.
    Potential Outcomes Enabled by Intelligent Asset Modelling
    Data
    More reliable valuations and return visibility Consistent asset, cash flow, and financing data with full traceability across SPVs & portfolios.
    Outcome
    ~1-2% better valuation accuracy with less rework in portfolio reviews.
    Process
    Faster analysis without slowing decisions Valuations and cash flows update on planning timelines, eliminating manual refreshes.
    Outcome
    50-60% shorter modeling cycles accelerate investment and refinancing decisions.
    People
    Stronger governance and decision discipline The assignment of ownership to assumptions, reviews, and approvals diminishes the need for human involvement.
    Outcome
    Audit-ready decision-making strengthens cross-functional alignment.
    Customer Success Stories
    Improving Valuation Speed and Accuracy Across Diverse Asset Classes
    Improving Valuation Speed and Accuracy Across Diverse Asset Classes
    • 67%

      Reduction in NAV and IRR reporting time

    • 70%

      Increase in IRR forecasting accuracy

    • 3X

      Faster validation of valuation assumptions

    Strengthening Governance and Stress-Test Agility with Versioned Portfolio Modelling
    Strengthening Governance and Stress-Test Agility with Versioned Portfolio Modelling
    • 73%

      Faster turnaround for investor-ready stress-test reports

    • 90%

      Improvement in audit compliance

    • 47%

      Reduction in time spent preparing governance materials

    Enabling Smarter Capital Planning with Real-Time Portfolio Visibility
    Enabling Smarter Capital Planning with Real-Time Portfolio Visibility
    • 2X

      Faster decision-making on asset hold/sell scenarios

    • 53%

      Reduction in delays across capital committee cycles

    • 74%

      Increase in risk-weighted allocation precision

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