Independent RIA
Estimated Enterprise Value
Primary: Adjusted EBITDA multiple
Cross-check: Recurring revenue multiple
Profitability receives more weight as operating data and institutional depth become more reliable.
Preparing your view
Preparing your view
Black Scarab uses deterministic, practice-specific calculations. Every method, normalization, and adjustment is versioned and visible.
Structure comes first
The model first identifies what is actually being valued. An independent business and an employed wirehouse team do not have the same ownership rights, cash flows, or transfer mechanisms.
Independent RIA
Estimated Enterprise Value
Primary: Adjusted EBITDA multiple
Cross-check: Recurring revenue multiple
Profitability receives more weight as operating data and institutional depth become more reliable.
IBD / independent practice
Estimated Practice Economic Value
Primary: Recurring revenue multiple
Cross-check: Cash flow / SDE cross-check
Revenue durability, portability, client profile, and advisor dependence shape the indicated range.
Wirehouse advisor / team
Estimated Practice Economic Value
Primary: Trailing production
Cross-check: Transition economics cross-check
The model does not imply legal ownership of accounts and explicitly considers platform and retention risk.
Hybrid advisor / hybrid RIA
Blended value perspective
Primary: Segment-weighted methods
Cross-check: Revenue-quality cross-check
Independent enterprise economics and advisor-practice economics are evaluated separately, then blended.
Illustrative RIA multiple
Illustrative logic only. The live model uses the inputs supplied and enforces methodology-specific floors and caps.
Bounded adjustment logic
The model begins with a practice-specific base multiple, applies discrete adjustments, then enforces a reasonable configured range. The 100-point score provides a diagnostic view; it is not mapped linearly to price.
Black Scarab Value Score
The score highlights the operating qualities that support durability and transferability. Missing inputs earn neutral or conservative treatment and reduce confidence.
A result preserves the assumptions used, even after an administrator publishes a new version.
Data completeness changes confidence—not the underlying definition of a dollar or percentage.
AI may explain structured output. It cannot calculate, modify, or overwrite a valuation.
Complete the guided questionnaire and review every assumption behind your range.
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