RIA Onboarding Stress Test Pack

Why this Data Set exists

Most onboarding workflows are designed for the modal client and tested against three or four hand-built test fixtures. The result is friction that surfaces only in production: the form that requires a Social Security Number when an ITIN is what the prospect has; the goal-capture flow that doesn't have a category for caregiver-of-aging-parent; the initial-recommendation engine that breaks when the prospect's income is a six-month-trailing-average rather than a current monthly figure.

These aren't edge cases — they're the modal cases for important RIA growth segments. Cross-border professionals, gig-economy earners, recent immigrants, and life-transition clients are the highest-LTV prospects most firms underserve because the onboarding system rejects or misroutes them. Firms find out only after the fact, when win rates from those segments are quietly half what they should be.

This Data Set surfaces the friction in advance. The 400 prospects span 12 archetypes covering every wealth tier, life stage, employment type, and family structure your intake system needs to handle. The broadest archetype coverage of any single bundle in the catalog — that's intentional.

Use Cases

Who uses this Data Set

What's inside

The 400 prospects span 12 archetypes — the widest archetype coverage of any single Wealth Data Set: from F-01 (New Graduate Tech Worker) and AR-01 (Artist with Royalty Income) on the formation end, through dual-income professionals and small business owners in mid-career, to retirees and complex life-transition cases. Wealth tiers span $50K to $30M+ so every advisory engagement model is represented.

Every prospect has a complete KYC record: identity verification fields (with realistic edge cases — ITIN filers, dual citizens, recent name changes), beneficial ownership for entity-owning prospects, source-of-wealth narrative, and risk-tolerance questionnaire results. Goal capture covers the full goal taxonomy (retirement, college, home purchase, business sale, charitable, transition) with structured priority rankings and time horizons. Initial recommendation outputs include the canonical first-meeting deliverables: asset allocation suggestion, account-type recommendation (which bucket to fund first), insurance gap analysis, and estate planning readiness flags (will/POA/HCD presence, beneficiary completeness).

Field names follow CRM-compatible conventions so direct ingestion into Salesforce, Wealthbox, or Redtail requires minimal transformation. The Data Set ships as JSON (one file per prospect plus a manifest) and CSV (long-format with normalized account/goal/recommendation tables for SQL ingestion), accompanied by the WealthSynth Methodology PDF — covering the field schema, the CRM-mapping appendix, and the calibration source for each archetype's KYC/goal/recommendation defaults.

Preview a sample household

A redacted summary of one household from this Data Set — names, employers, exact balances, and metro area are stripped. Ages are bucketed, income and net worth are reported as bands. The full record (and all 400 like it) ships in the ZIP.

Technical Highlights

Sample Schema Fields

{
  "demographics.household_profile": <value>,
  "accounts.summary_balances": <value>,
  "goals.primary_financial_goals": <value>,
  "kyc.identity_verification_fields": <value>,
  "planning.initial_recommendations": <value>
}

Sample queries

prospects.filter(p =>
  ['1099', 'K-1', 'royalty', 'business_draw'].includes(
    p.income.primary_source_type
  )
)

prospects.filter(p =>
  p.kyc.identity_verification_fields.itin_filer ||
  p.kyc.identity_verification_fields.dual_citizen ||
  p.kyc.identity_verification_fields.recent_name_change ||
  p.credit.thin_file_flag
)

prospects.map(p => ({
  id: p.id,
  routing_specialty: p.equity_comp.grants?.length > 0 ? 'equity_comp'
    : p.business.entity_type ? 'business_owner'
    : p.estate.trust_structures?.length > 0 ? 'estate'
    : 'general'
}))

prospects.map(p => {
  const required = ['risk_tolerance', 'goals',
    'income', 'expenses', 'assets', 'liabilities',
    'beneficiaries', 'insurance'];
  const present = required.filter(k => p[k] != null);
  return { id: p.id, completeness: present.length / required.length };
})

Methodology

Each prospect is generated against a randomly weighted draw from 12 archetypes, with the weighting deliberately equalising across wealth tiers and life stages so no single segment dominates the 400-prospect corpus. KYC fields draw from realistic distributions of identity-verification scenarios (about 4% ITIN filers, 6% dual citizens, 2% recent name changes — calibrated against Pew demographic data on the financial-services-customer population). Goal-capture and risk-tolerance fields use FINRA Rule 2090–compliant structures. Initial recommendation outputs are produced by the same recommendation logic that generates the WealthSynth canonical onboarding outputs, so the recommendations exhibit realistic variation across archetypes. The full corpus passes the WealthSynth consistency validator (KYC fields reconcile, goal priorities sum correctly, recommendation logic is deterministic given inputs) and the LLM-as-judge gate. Annual refresh re-runs against current FINRA interpretive guidance and CFP Board CIP standards.

Included Archetypes (12)

Frequently asked questions