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Reliability Score

65

4365(+22 pts)

Real Estate: Reported vacancy_loss for 2025-12 is 5.1%, but recomputed value from raw events is 0.0%. Discrepancy of +100.0%.

BayesIQ's audit surfaced 4 findings and enabled targeted remediation that improved the reliability score from 43 to 65.

LP distributions calculated on fabricated 5.1% vacancy loss — actual vacancy is 0.0%. Investors received distributions based on false occupancy assumptions

Reported

5.1%

vacancy loss · 2025-12

Audited

0.0%

Overstated 100%

Decision Exposure

LP distributions calculated on fabricated 5.1% vacancy loss — actual vacancy is 0.0%. Investors received distributions based on false occupancy assumptions

Reported

2.7%

delinquency · 2025-12

Audited

2.9%

Understated 8.7%

Decision Exposure

Delinquency understated to investors at 2.7% — actual is 2.9%, masking $200K+ in uncollected rent

Reported vacancy_loss for 2025-12 is 5.1%, but recomputed value from raw events is 0.0%. Discrepancy of +100.0%.

Illustrative Example

BayesIQ Data Reliability Audit

Real Estate

Audit Period: December 2025

65

Reliability Score

Fair — significant data quality issues detected

Illustrative example — representative of BayesIQ audit deliverables

BayesIQ audits a real estate firm's portfolio performance reporting across vacancy tracking, tenant delinquency, and collection rates. The audit surfaces 4 issues — including a complete vacancy loss fabrication (reported 5.1%, actual 0.0%), null tenant IDs breaking lease-level aggregations, and 60 duplicate property records. LP distributions had been calculated on fundamentally incorrect occupancy assumptions. After remediation, the reliability score improves from 43 to 65.

4 findings3 high1 medium

Key Metrics: Reported vs Audited

MetricPeriodReportedAuditedDelta
vacancy_loss2025-125.1%0.0%overstated 100%
delinquency2025-122.7%2.9%understated 8.7%

Top Findings

high

vacancy_loss misreported for 2025-12 (off by +100.0%)

LP distributions calculated on fabricated 5.1% vacancy loss — actual vacancy is 0.0%. Investors received distributions based on false occupancy assumptions

medium

delinquency misreported for 2025-12 (off by -8.7%)

Delinquency understated to investors at 2.7% — actual is 2.9%, masking $200K+ in uncollected rent

high

Near-duplicate rows detected

60 duplicate property records inflating portfolio size metrics reported to LPs

60 rows affected

high

Null values in required column: tenant_id

32 leases missing tenant_id — cannot track delinquency or vacancy at the tenant level

32 rows affected

Recommended Actions

  1. 1

    Investigate duplicate records. Add dedup logic keyed on non-key fields.

    Owner: Data Engineering|Effort: Mediumhigh
  2. 2

    Fix null values in required column 'tenant_id' at the source.

    Owner: Data Engineering|Effort: Mediumhigh
  3. 3

    Investigate root cause of vacancy_loss discrepancy for 2025-12. Check for duplicate events, missing data, or filter logic differences.

    Owner: Data Engineering|Effort: Mediumhigh
  4. 4

    Investigate root cause of delinquency discrepancy for 2025-12. Check for duplicate events, missing data, or filter logic differences.

    Owner: Data Engineering|Effort: Smallmedium
Prepared by BayesIQ · 2025-12

Why this matters

vacancy_loss misreported for 2025-12 (off by +100.0%)

high

LP distributions calculated on fabricated 5.1% vacancy loss — actual vacancy is 0.0%. Investors received distributions based on false occupancy assumptions

delinquency misreported for 2025-12 (off by -8.7%)

medium

Delinquency understated to investors at 2.7% — actual is 2.9%, masking $200K+ in uncollected rent

Near-duplicate rows detected

high

60 duplicate property records inflating portfolio size metrics reported to LPs

What working with BayesIQ looks like

43

Discovery

4 findings identified

62

Remediation

Data Engineering resolved key issues

65

Steady State

Metrics verified and trustworthy

?

Your Data

This could be your story

What makes BayesIQ different

Findings connected to business meaning

Operational and executive surfaces produced

Remediation governed and tracked

Evidence and decisions preserved

Metric confidence legible over time

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