AI in real estate starts with your data
AI is the megatrend, but AI on fragmented, unvalidated data gives confident, wrong answers. What AI-ready real estate data looks like, and why the data layer comes first.
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Perspectives on Swiss real estate portfolio management, fund reporting and data operations.
Articles
What is a good DSCR in real estate?
DSCR tests whether a property earns enough to cover its debt. What a good DSCR looks like (typically 1.25–1.35), a worked example, and a free calculator.
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What is NOI (Net Operating Income) in real estate?
The formula, a worked example, what NOI excludes (debt service, capex, tax), and why it underpins valuation and DSCR.
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ESG data and reporting for real estate funds
ESG reporting is a data problem before anything else. The frameworks (SFDR, GRESB, CSRD, INREV, EPRA, Swiss Climate Scores) and how to consolidate fragmented ESG data into investor reporting.
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Data centre and digital infrastructure fund reporting
Data centres are now a core institutional allocation but report unlike traditional property. The KPIs investors ask for — NOI, WAULT, yield, capex, DSCR — and why consolidating the data is the hard part.
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What is a good WAULT? Benchmarks and how to read it
WAULT signals income durability, so higher is usually better — but the right level depends on sector and strategy. Benchmarks, a worked example, and how to read WAULT to expiry versus to break.
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Key real estate asset management metrics: the KPIs that actually matter
A practical reference to the metrics institutional asset managers and owners track — NOI, WAULT, rental loss, cost ratios, IRR, DSCR, CapEx and ESG — with how each is calculated, and why keeping them current across a portfolio is the hard part.
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From quarterly snapshot to live portfolio view: how real estate data is evolving
Institutional real estate has operated on quarterly data cycles for decades. The technology to change this exists. Here's what moving from batch to continuous data means for Swiss fund managers — and what infrastructure it requires.
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The additive approach: why the best PropTech doesn't replace what you already have
54% of real estate teams cite legacy system compatibility as their number one barrier to technology adoption. The rip-and-replace approach is also the most likely to fail. Here's why the additive architecture wins.
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How to select real estate portfolio management software: a practical framework
Most technology selection projects in institutional real estate fail for the same reasons. A six-step framework covering Swiss-specific requirements, how to test with your data, and what to negotiate in your contract.
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The PAM-PM data handoff: why it breaks down and what to do about it
The relationship between property asset managers and property managers is the most data-intensive in institutional real estate — and the most prone to systematic failure. Here's where it breaks down and how to fix it structurally.
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ESG data in Swiss real estate funds: what institutional investors are now requiring
Swiss institutional investors have moved from asking 'do you have an ESG policy?' to 'show me the data.' What fund managers are now expected to provide, where the collection gaps are, and how portfolio infrastructure determines whether ESG reporting is credible.
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AI in real estate: the data problem that most firms aren't solving first
93% of real estate organisations have AI access. Only 7% have it fully integrated. The gap is not about AI — it's about data. What Swiss fund managers need to address before AI tools will work reliably.
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FINMA and real estate data integrity: what the 2025 Risk Monitor means for fund managers
FINMA explicitly flagged data integrity and cyber risks in its 2025 Risk Monitor. What this means in practice, what examiners look for, and how data infrastructure determines audit readiness.
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What is real estate portfolio management software?
A category guide for fund and asset managers beginning vendor research — what this software does, what it doesn't do, and how to evaluate the options available to Swiss institutional managers in 2026.
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FPRE reporting: what Swiss fund managers need to know
A practical guide to FPRE reporting requirements — what the benchmark standard requires, where data pipelines typically fail, and how to produce FPRE-compliant reports without rebuilding your process from scratch.
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Why Swiss fund managers still use Excel — and what it costs them
Spreadsheets remain the default consolidation tool for most Swiss real estate fund managers. The cost in audit risk, reporting effort and regulatory exposure — and when the threshold for change makes financial sense.
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Data validation before reporting: the step most managers skip
Most real estate reporting errors don't originate in the report — they originate in the data that feeds it. How automated validation at ingestion changes the quarterly cycle and removes the correction loop that costs teams days every quarter.
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What we write about.
STREETS insights focus on the practical realities of managing Swiss real estate portfolios at an institutional level.
Fund reporting
How Swiss fund managers structure reporting for boards, investors and regulators — and where the process breaks down.
Data operations
The mechanics of consolidating data from multiple property managers — validation, standardisation and audit traceability.
Compliance and regulation
Practical implications of FINMA requirements for data integrity, audit trails and reporting standards in Swiss real estate.
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