wealthschema/archetypes/b-01-financial-anxiety-avoider
B-01BehavioralAccumulationlow tax complexity

Financial Anxiety / Avoider

Individual with high financial anxiety, avoids opening statements, procrastinates on financial decisions, needs coaching.

B-01 is the corpus where the balance-sheet inputs look ordinary but the behavior breaks the product: statements go unopened, contribution decisions are deferred, and onboarding completion rates collapse. It is the testing surface for nudges, defaults, and coaching paths.

Age Range
25–50
Net Worth
$0–$100k
Cohort
Behavioral

About this archetype

B-01 isolates a behavioral pattern that is invisible in pure-number archetypes: a household with reasonable income ($63k median) and a non-trivial net worth ($321k median) whose financial state is being shaped by avoidance, not by structural disadvantage. The diagnostic surface is the gap between balance and engagement — under-utilised employer-sponsored plans despite eligibility, low contribution rates relative to income, emergency funds short of any conventional benchmark, and a tendency to leave money in default cash sweep rather than make an allocation decision. For tax-software and benefits products this archetype is where auto-enrollment, default-deferral escalation, and SECURE 2.0 emergency-savings sidecars (the new $2,500 in-plan emergency account) actually pay off. For wealth-platform onboarding it is where multi-step forms and 'risk tolerance' questionnaires lose users mid-flow.

The cash-flow profile is mass-market dual-earner with credit-card revolving balances on all 20 households and student loans on a meaningful minority. Retirement appears as a goal in every record, but on-track flags are predominantly false. Liquid assets ($58k median) sit well below the household's net worth, suggesting the balance sheet is real but the working capital is thin. Twelve of twenty carry an active home-purchase goal that they are usually behind on. This is the household that defers refinancing, defers HSA enrolment, defers 401(k) rebalancing — not because the math is wrong but because the action does not get taken.

What separates B-01 from neighbouring behavioral archetypes is the direction of the bias. B-02 acts too much; B-03 spends too much; B-01 acts too little. The corpus is intentionally calibrated so the underlying capacity to save exists — income is mass-market, not poverty-line — which means the failure mode is psychological rather than structural. That makes it the right test population for engagement features (statement re-reading, gamified savings, coach-mediated planning, retirement-readiness nudges) rather than for hardship workflows.

Defining characteristics

  • Financial avoidance
    Households defer engagement with statements, allocation choices, and benefits-election deadlines. Behavioral flags drive features like auto-escalation and re-enrolment defaults rather than active-choice flows.
  • Low financial literacy
    Confusion between Roth and traditional, conflation of HSA and FSA, and uncertainty about employer match mechanics are typical. Plain-language UI and decision-aid copy are the relevant test surfaces.
  • Procrastination on goal funding
    All 20 households have a retirement goal but most are behind. Twelve carry a home-purchase goal; nine carry an education-funding goal. Goal flags are populated, action is delayed.
  • Coaching need
    This is the cohort where human-in-the-loop coaching, advisor matching, and SECURE 2.0 financial-wellness benefits show measurable lift. The corpus supports A/B tests against pure-self-serve flows.
  • Behavioral intervention surface
    Default contribution rates, auto-enrolment, sticky-default emergency savings, and pre-filled benefits elections are the relevant feature set. Active-choice UX patterns systematically underperform here.
  • Mass-market income with thin liquidity
    Median income of $63k and liquid net worth of $58k means the household has assets but limited working capital — a profile that is structurally bankable but behaviorally unbanked-adjacent.

Corpus signature

n = 20 households

Aggregated across the 20 B-01 households in the shipped v3 corpus corpus. Numbers describe the corpus, not population claims.

Median income
$63k
p25–p75 $57k–$73k
Median net worth
$322k
mean $293k
Liquid net worth
$58k
median
Investable assets
$77k
median
Income distribution
$50k–59k
8
$59k–68k
5
$68k–77k
4
$77k–86k
3
Net-worth distribution
$15k–165k
7
$165k–315k
3
$315k–465k
6
$465k–615k
4
Goals across the corpus
Retirement20 / 20
Home purchase12 / 20
Education funding9 / 20
Emergency fund7 / 20
Debt payoff4 / 20
Liability composition
Credit cards20 / 20
Auto loans11 / 20
Mortgages8 / 20
Student loans4 / 20
  • 8 of 20 (40%) are homeowners; the remainder rent.
  • IL, NJ, CA account for 8 of 20 households — 40% of the corpus.
  • Median adult-member age is 42 (range 22–52 across primaries and spouses).
  • 9 of 20 (45%) carry one or more dependents.

Representative household

B-01-seed-4
Grace A.Married filing jointly·Champaign-Urbana, IL

Grace and Matthew sit slightly above the income median for B-01 but well below it on net worth — the household has not yet started compounding. Liquid assets cover only about a year of household expenses and total liabilities are negligible, which means there is no debt-crisis story here; there is a missing-engagement story. Both home-purchase and retirement goals are flagged off-track despite ample raw capacity to contribute, which is the diagnostic pattern this household surfaces.

Combined income
$65,745
Net worth
$138,914
Liquid NW
$56,730
Ages
33 / 34
Top goals on this household
Home purchase
$52,596
Retirement
$1,220,700

Schema fields covered

Every B-01 household ships with — at minimum — these JSON fields populated. The full schema is documented in the data set you purchase.

members[].age
income.combined_gross
net_worth.total
filing_status
longitudinal.monthly[].net_cash_flow
longitudinal.monthly[].savings_rate
stress.scenarios[]
liquidity.months_of_expenses

Who builds against this archetype

Three buyer profiles draw on B-01 most heavily. Recordkeeping and 401(k) platforms use it to validate auto-enrollment, auto-escalation, and SECURE 2.0 in-plan emergency savings features where the participant is opted in by default rather than electing actively. Behavioral-finance and financial-wellness vendors use it as the control population for coaching-engagement experiments and statement-redesign A/B tests — the gap between balance and engagement is exactly what their products are sold against. Tax-software teams use it to test prompt fatigue and abandonment patterns in multi-step return flows, particularly around HSA contributions, IRA deduction worksheets, and saver's credit eligibility, where avoidant users routinely leave money on the table.

Testing scenarios this corpus is calibrated for

  • 01Auto-enrolment and auto-escalation testing against participants whose active-choice rates are historically near zero.
  • 02SECURE 2.0 in-plan emergency-savings sidecar ($2,500 cap) eligibility and uptake modeling.
  • 03Behavioral-nudge experiments: statement redesign, retirement-readiness scoring, and re-enrollment campaign targeting.
  • 04Financial-coaching workflow fixtures with a population that has measurable capacity to save but a documented engagement gap.
  • 05Saver's Credit eligibility testing — meaningful share of corpus falls within the AGI bands but the credit is routinely missed without prompt.
  • 06Abandonment-funnel analysis on multi-step onboarding flows; this corpus is the target population for flow-simplification work.

Edge cases and what's not in this corpus

B-01 is not a hardship archetype. Median net worth of $321k means the corpus has accumulated assets, and credit cards are revolving but liabilities are modest. Households in active financial distress live in S-02 (bankruptcy recovery), S-03 (medical-debt crisis), or U-02 (low-income working family) — reach for those when the failure mode is structural rather than behavioral. Households where avoidance compounds an existing crisis (medical-debt avoidance, post-divorce paralysis) are better tested via overlays onto S-01 or S-03. B-01 also excludes overconfident self-directed investors (B-02) and lifestyle-inflation spenders (B-03), which are the opposite behavioral failure modes. Children with neurodivergent diagnoses driving avoidance are X-04 territory.

Calibration notes

Income and net-worth bands during v3 synthesis were anchored to the mass-market segments of the Survey of Consumer Finances and to BLS Consumer Expenditure Survey saving-rate distributions for working-age households. Behavioral flags (statement non-opening, default-cash holdings, missed enrolment deadlines) were synthesised as overlay attributes rather than estimated from a probabilistic model — there is no published behavioral prior we can cite for this archetype. Goal on-track flags lean systematically false by design. Per CLAUDE.md §9 the v3 corpus is frozen and not regenerable from current code, so calibration claims are descriptive of the shipped fixtures rather than reproducible from a seed.

How this differs from related archetypes

Frequently asked questions

What does the B-01 archetype represent?+

B-01 — Financial Anxiety / Avoider represents a mass-market household with reasonable income and assets whose financial outcomes are shaped primarily by avoidance behavior: deferred decisions, unopened statements, low engagement with employer-sponsored plans, and persistent off-track goal flags despite measurable capacity to save.

How is B-01 different from a low-income hardship archetype?+

B-01 has a median net worth of $321,503 and a median income of $63,121 — the underlying capacity to save exists. The failure mode is psychological, not structural. Households in active financial hardship live in S-02 (bankruptcy recovery), S-03 (medical-debt crisis), and U-02 (low-income working family).

What product features does B-01 typically exercise?+

Auto-enrolment, auto-escalation, SECURE 2.0 in-plan emergency-savings sidecars, default contribution rates, behavioral nudges, statement redesign, financial-coaching workflows, and Saver's Credit prompts. Anything where the design choice is between active-choice and default-in matters here.

Why are most goal flags off-track in this corpus?+

Off-track flags are intentional. The archetype is calibrated so households have capacity to contribute but are not contributing at a rate that funds their stated goal. That gap between stated goal and actual contribution is what makes B-01 useful for engagement and nudging features.

How were B-01 households generated?+

Deterministically from a seeded sampler (Mulberry32 PRNG) in src/lib/generation/, with behavioral flags applied as overlay attributes during synthesis. Per-domain version constants (DEMOGRAPHICS_VERSION, FINANCIALS_VERSION, etc.) are surfaced in each household's _meta block.

Is the B-01 corpus regenerable?+

No. The shipped 1,451-household v3 corpus is frozen and not regenerable from current code (drift confirmed 2026-05-09). Sampler improvements land in a future v4 release with per-archetype golden fixtures in CI to prevent silent drift.

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