Synthetic Wealth Data
Built for Financial Services

The definitive synthetic dataset for Reg BI suitability testing. 143 households spanning all risk tolerance profiles, investment objectives, and time horizons — with documented recommendation rationale for each.

806 households with complete tax lot histories, unrealized gain/loss positions, and wash-sale scenarios — the gold standard dataset for validating tax-loss harvesting algorithms.

380 retiree and near-retiree households with detailed decumulation scenarios, Social Security optimization paths, RMD sequences, and late-life care events.

468 households with detailed banking layer data: paycheck timing, overdraft cycles, emergency fund adequacy, and auto-pay schedules — purpose-built for cash flow and liquidity product testing.

469 households with detailed mortgage portfolios, property valuations, LTV ratios, DTI calculations, and real estate stress scenarios — purpose-built for mortgage underwriting and real estate lending platforms.

The most comprehensive middle-market dataset available: 1,203 households spanning all income bands, family structures, and life stages — for broad-coverage financial product testing, model training, and platform QA.

536 family households with dependent children, education savings plans, life insurance needs, and household budget complexity — for family financial planning software and education savings platform testing.

376 high-income professional households with complex tax situations, equity compensation, deferred compensation, and wealth accumulation strategies — for high-income planning software and tax optimization tool testing.

628 households with diverse tax situations spanning all filing statuses, income types, deduction strategies, and tax optimization opportunities — the broadest tax planning dataset in the WealthSynth catalog.

All 1,451 WealthSynth households in a single dataset: every archetype, every income band, every life stage, and 96 months of longitudinal financial data per household. The definitive synthetic wealth dataset.

461 households with detailed investment portfolios spanning equities, fixed income, alternatives, and retirement accounts — for portfolio analytics, rebalancing engine, and performance attribution testing.

155 high-net-worth households with trusts, beneficiary designations, estate tax exposure, and multi-generational wealth transfer scenarios — for estate planning software validation.

40 households with cryptocurrency holdings, DeFi positions, NFT portfolios, and digital asset tax complexity — for crypto platform compliance, tax reporting, and risk modeling.

28 ultra-high-net-worth households with complex entity structures, family office operations, concentrated equity positions, and multi-jurisdictional tax exposure — for UHNW platform and family office technology testing.

224 households with detailed credit profiles, debt portfolios, delinquency scenarios, and credit score trajectories — for credit risk model training, debt management platform testing, and lending algorithm validation.

164 households with detailed insurance coverage profiles across life, disability, long-term care, and property — for insurance needs analysis software testing and coverage gap modeling.

357 households with diverse income structures: rental income, business distributions, royalties, capital gains, and gig economy income — for tax planning software and income analysis platform testing.

82 business owner and self-employed households with entity structures, business valuations, succession planning scenarios, and exit strategy modeling — for business planning software and M&A advisory tool testing.

52 FIRE (Financial Independence, Retire Early) households with high savings rates, investment-income-dependent lifestyles, and sustainable withdrawal rate modeling — for early retirement planning software testing.

263 young professional households with student debt, entry-level income, first home purchase scenarios, and early investing behaviors — for financial wellness and early career planning platform testing.

102 households with concentrated equity positions, vesting schedules, 10b5-1 plan scenarios, and diversification strategies — for equity management platform testing and concentrated position advisory tool development.

310 households experiencing major life transitions: divorce, job loss, inheritance, relocation, and health crises — with documented financial impact sequences for life event planning software testing.

58 households with international income, foreign assets, FBAR/FATCA obligations, and treaty-based tax planning scenarios — for cross-border financial planning software and international tax tool testing.

187 households with disability income sources, special needs trust structures, ABLE account scenarios, and government benefit coordination — for disability planning software and special needs advisory tool testing.

85 households covering the full active duty to veteran financial transition: VA benefits optimization, TSP rollover decisions, disability rating scenarios, and civilian income transition planning.

127 households with student loan complexity spanning PSLF eligibility, IDR plan optimization, refinancing decisions, marriage penalty scenarios, and employer benefit coordination.

120 households with healthcare cost complexity: HSA optimization, COBRA transition scenarios, high-deductible plan strategies, and medical debt accumulation — for healthcare finance platform and benefits technology testing.

389 households experiencing major life transitions: divorce in progress, post-bankruptcy recovery, medical-debt crisis, sudden wealth, and empty-nester downsizing — for transition planning software and life event advisory tool testing.

166 households with gig economy, freelance, creator, and variable income profiles — for tax planning, cash flow management, and benefits portability platform testing.

117 underbanked and underserved households: prepaid card users, ITIN filers, post-bankruptcy unbanked, and cash-economy participants — for CDFI product testing, CRA compliance validation, and financial inclusion platform development.

210 households with documented behavioral finance risk patterns: financial anxiety, overconfidence, lifestyle inflation, and loss aversion — for behavioral coaching platform testing and financial wellness intervention tool development.