WealthSynth vs. Building Synthetic Data In-House
Synthetic data is approachable enough that nearly every team considers building their own corpus rather than buying one. The argument is intuitive: 'we know our requirements, we have engineers, how hard could it be?' The answer is that the easy 80% is genuinely easy and the hard 20% — calibration, validation, maintenance — usually consumes more engineering time than the team budgeted. This comparison walks through the realistic build cost and the situations where buying is the more economical path.
The two options
Buy WealthSynth
Curated 31-bundle catalog + Master Corpus, calibrated against authoritative sources, refreshed against regulatory updates, with a documented Methodology PDF per bundle.
- Available immediately — buy and ingest in days, not months
- Calibration depth — bundles are calibrated against FINRA, FinCEN, IRS, NAIC, Cerulli, and other authoritative sources, with citations documented
- One-time pricing — pay once per bundle; no per-call fees, no required subscription
- Edge-case coverage — bundles are deliberately weighted toward the rare-but-important fact patterns regulators and product teams need
- Documentation — each bundle has a Methodology PDF covering field-by-field derivation, calibration sources, and use-case mapping
- Privacy contract — conditional demographic overlay (race / religion) is governed by an explicit contract; in-house implementations rarely think through this layer
- Bundle scope is fixed — if your use case needs a corpus structured differently from any of the 31 bundles, custom engagement is needed
- External-vendor dependency — some compliance contexts have vendor-management overhead
- Refresh cadence for buyers is still being defined — currency-sensitive deployments should confirm the latest before purchase
Choose WealthSynth when: (1) your team's time-to-value is more valuable than the cost savings of building in-house; (2) your use case maps cleanly to one or more of the existing bundles; (3) you need edge-case coverage you don't have time to calibrate; or (4) you'd rather have a vendor track regulatory changes than dedicate internal headcount to it.
Build In-House
Engineer your own synthetic-data generation pipeline, calibrated against the sources your use case requires, owned and maintained by your team.
- Full control over scope — generate exactly the bundles your use case needs, structured exactly how your platform consumes them
- No vendor dependency — once built, there's no external license cost (only your own engineering time)
- Internal IP — the generation pipeline is an internal asset that can be reused across multiple internal use cases
- Customization depth — for use cases that don't fit any standard bundle structure, in-house is the only path
- Calibration is the hard part — building a generator that produces a 130-household Reg BI corpus that actually matches the fact patterns regulators cite takes 200+ engineering hours plus 100+ compliance-specialist hours
- Maintenance is permanent — keeping the corpus current against regulatory changes requires ongoing engineering investment, not a one-time cost
- Edge-case coverage requires deliberate work — naive synthetic data over-represents modal customers and under-represents edge cases; fixing this requires explicit calibration weights
- Validation is a research project — verifying that the generator produces realistic distributions requires comparing against authoritative benchmarks (Cerulli, FDIC, IRS) on every refresh
- Documentation burden — examiner-defensible documentation of the methodology is a substantial separate effort
Choose to build in-house when: (1) your use case is sufficiently specific that no standard bundle fits; (2) your team has both engineering and compliance-specialist capacity for the build and the ongoing maintenance; (3) the recurring vendor cost is meaningfully more than the engineering opportunity cost; or (4) the corpus must integrate so deeply with internal systems that an external vendor's structure would require substantial transformation.
Decision framework
The decision math depends on three factors: time-to-value, total cost over a 3-year horizon, and use-case fit.
Time-to-value: WealthSynth is available in days. In-house build is typically 3-6 months for a single bundle, longer for a multi-bundle catalog. If the team needs to ship a feature requiring synthetic data in the next quarter, buy.
Total cost over 3 years: For a single bundle, a typical in-house build costs about 200 engineering hours initial plus 50 hours per year of regulatory-tracking maintenance, roughly $50K-$100K depending on rates. For a multi-bundle catalog (5+ bundles), the cost scales meaningfully — calibration work scales sub-linearly but doesn't drop to near-zero. The break-even point with WealthSynth varies by bundle, but for most multi-bundle scenarios, buying is the lower TCO.
Use-case fit: For use cases that map cleanly to one of the 31 existing bundles, buying is straightforward. For use cases that require structurally different corpus shape (e.g. 'I need 5,000 households of a very specific archetype mix not represented in any standard bundle'), custom engagement with WealthSynth or an in-house build are the only paths.
The most common pattern is a hybrid: buy WealthSynth for the 80% of use cases that map cleanly, and build a small in-house generator for the 20% of use cases that require firm-specific customization.
Bottom line
For most wealth-tech teams, buying WealthSynth is the lower-TCO and faster-time-to-value path for the canonical use cases (Reg BI testing, fee benchmarking, retirement income sequencing, equity comp planning, etc.). In-house build makes sense for use cases that require firm-specific corpus shape that doesn't fit any standard bundle. The hybrid approach — buy the catalog, build the few specialized cases — works well in practice and is the pattern most mature teams converge on.
FAQ
What's the realistic engineering cost of an in-house build?+
For a single Reg-BI-equivalent bundle (130 households with 5 fact patterns calibrated): 200-300 hours of engineering time for the initial build, plus 100+ hours of compliance-specialist time for calibration. Maintenance is 50-100 hours per year to track regulatory changes. Total over 3 years: $80K-$200K depending on rates and scope. For a 5-bundle catalog: 600-1,000 hours initial, 200+ hours per year maintenance.
Can I license the WealthSynth generator to build on top of?+
Not currently. The generator itself is internal IP. The catalog (output of the generator) is what's licensed. For custom corpus generation that doesn't fit a standard bundle, custom engagement is the path — WealthSynth can run the generator against your specific calibration requirements and deliver the corpus.
What about open-source synthetic-data tools (SDV, Faker, etc.)?+
Open-source tools handle the structural side (generating records that look statistically reasonable) but not the calibration side (ensuring the records exhibit the fact patterns your use case requires). For wealth-management-specific use cases, the calibration work is the bulk of the effort, and open-source tools don't shortcut it. Open-source tools are useful as building blocks for an in-house generator; they're not a substitute for a calibrated catalog.
How do I evaluate whether a WealthSynth bundle fits my use case?+
Read the bundle's Methodology PDF — it documents the population calibration, the field-by-field structure, and the specific use cases the bundle is designed to exercise. If your use case is in the documented list, the bundle is a fit. If your use case requires a different structure, custom engagement is the path.
Can I combine multiple WealthSynth bundles?+
Yes. Bundles are designed to compose — buying B01 (Reg BI) and B14 (RIA Onboarding) gives you both bundles' households without overlap conflicts (different archetype focus, different bundle-tag assignments). The Master Corpus B31 is the integrated 'buy everything' option for teams whose product surface spans multiple bundles.
How does the corpus stay current?+
We re-run the generation pipeline against current-year tax tables, FINRA / SEC interpretive guidance updates, and any new archetype variants added during the year. Each refresh produces a new corpus version; existing versions are not edited in place. Refresh cadence and scope for buyers are still being defined — we are not currently charging for refreshes. Reach out if regulatory currency is critical to your evaluation.