Statistical Risk Scoring for Self-Reported Income: Improving Income Approach Valuation

Presentation Category

02 COLLECTING AND MAINTAINING PROPERTY DATA

General Session Description

This session presents a data-driven framework to improve the reliability of self-reported income and expense data in income-based valuation. Using statistical density models, machine learning, and distribution-based scoring, this approach generates continuous risk scores to support valuation quality control, audit targeting, and compliance review in mass appraisal.

Audience Expertise

Intermediate (Ideal for the participant with a general knowledge within the areas covered.)

Location

Telus 101/102

Start Date

10-16-2026 2:45 PM

End Date

10-16-2026 3:45 PM

Moderator

Russ Thimgan, Thimgan & Associates

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Oct 16th, 2:45 PM Oct 16th, 3:45 PM

Statistical Risk Scoring for Self-Reported Income: Improving Income Approach Valuation

Telus 101/102

This session presents a data-driven framework to improve the reliability of self-reported income and expense data in income-based valuation. Using statistical density models, machine learning, and distribution-based scoring, this approach generates continuous risk scores to support valuation quality control, audit targeting, and compliance review in mass appraisal.