Every WealthTech skill we track.

Boxing your own workflow into stages an agent can execute under your supervision — the agentic-era skill that separates operators who stay in front of automation from those who get eaten by it.

End-to-end understanding of how accounts are opened, funded, managed, and closed across RIA, BD, and private-bank channels including KYC, onboarding, billing, and servicing.

Practical knowledge of clearing, settlement, trade confirmation, client reporting, and compliance workflows specific to registered investment advisers and broker-dealers.

Account open, ACAT, money movement and corporate actions across the major custodians (Pershing, Schwab, Fidelity, BNY/Pershing X, Altruist).

Resolving breaks between custodian feeds, portfolio accounting, and CRM systems.

How modern PMS platforms (Orion, Tamarac, Black Diamond, Addepar, Advyzon) actually model households, sleeves, models, performance and billing — and where they differ.

Reading Reg BI, Form ADV, and FINRA notices and translating them into product requirements.

Envestnet's Tamarac suite providing model-based rebalancing, trading, performance reporting, and CRM for RIAs, widely used by independent advisors on the Envestnet platform.

REST / SFTP / webhook patterns to read positions and write trades back into Orion, Tamarac, Addepar et al.

Extracting, transforming, validating, and loading historical investment data (positions, transactions, performance history) from legacy systems to target wealth platforms.

Model definitions, drift-band thresholds, cash-raise rebalances across thousands of accounts.

How the major planning tools (eMoney, MoneyGuide, RightCapital, Holistiplan) model goals, taxes, Monte Carlo and the plan-to-proposal handoff — and where they differ.

Building, prioritizing, and communicating a product roadmap for a wealth technology platform, balancing advisor needs, regulatory constraints, and technical feasibility.

Positions, securities, trades, models, accounts, households — the schemas every PMS exposes (or hides).

Writing and optimizing SQL queries against investment data warehouses covering positions, transactions, performance, client demographics, and fee data.

Setting up tiered/blended schedules, household billing, edge cases like joining mid-period.

Running discovery, writing PRDs, and decomposing epics for back-office migrations.

Applying sprint-based delivery, backlog management, user story writing, and stakeholder ceremonies in regulated wealth and fintech environments.

SS&C's Black Diamond platform providing portfolio reporting, performance, billing, and client portal tools for RIAs and wealth managers.

pandas, numpy, scikit-learn applied to financial data engineering.

Evaluating when to configure a wealth SaaS platform within its standard feature set versus building custom extensions, with implications for upgrade risk and vendor support.

Designing the future-state organizational structure, processes, and technology interactions for a wealth management firm undergoing platform or business transformation.

Operationalizing suitability assessment and Reg BI documentation requirements in technology workflows for broker-dealers and investment advisers.

Migrating off APL, Broadridge mainframes, and batch ledgers toward real-time platforms.

Choosing tax-lot relief methods and avoiding wash-sale traps in rebalances.

Designing and building extract-transform-load (or ELT) pipelines that ingest, clean, and deliver financial data from custodians, market data vendors, and operational systems.

Time- vs money-weighted return, GIPS composites, fee impact, account-level vs household.

Salesforce Financial Services Cloud as the primary platform (households, financial accounts, action plans, rollups, FSC data model) plus the alternatives wealth firms still run on: Redtail, Wealthbox, Practifi.

Designing the go-live weekend cutover sequence, rollback decision criteria, and contingency playbooks for wealth platform migrations.

Drafting and managing professional services agreements, scope definitions, and change orders for wealth platform implementation and integration engagements.

Evaluating how platform migrations and new technology implementations affect compliance with SEC, FINRA, and state regulatory obligations.

Diagnosing 'not in good order' tickets that block account opening and trades.

Compliance-aware cloud architecture: KMS, audit trails, regional pinning.

Running RFPs, vendor scorecards, and total-cost-of-ownership models for platform decisions.

Leading financial planning software platforms used by advisors for cash-flow analysis, retirement projections, estate planning, and client-facing interactive plans.

Designing weighted scorecards and scoring shortlists against client constraints.

Using financial data aggregation services to retrieve held-away account data, enrich client profiles, and power holistic wealth reporting.

Reviewing flagged events and deciding file vs escalate vs dismiss.

Industry data exchange standards governing how financial account, transaction, and market data flows between institutions, custodians, and technology platforms.

Building retrieval pipelines over 10-Ks, ADV filings, and internal compliance manuals.

Structured methodology for managing people-side change during wealth platform rollouts, including stakeholder analysis, resistance management, and adoption measurement.

Parsing, transforming, and mapping financial data payloads between vendor-specific schemas used by custodians, PMS platforms, and CRM systems.

Building transformation layers on Snowflake using dbt for custodial data standardization, performance metrics, and advisor-facing analytics pipelines.

Managing capital call schedules, distribution notices, NAV updates, and performance reporting for private equity, hedge fund, and real assets allocations in wealth portfolios.

BlackRock's enterprise risk and portfolio-management platform adapted for wealth managers, enabling factor-based risk analysis, model management, and discretionary portfolio management at scale.

Trust structures, gifting schedules, life-insurance ladders inside an integrated plan.

Implementing secure single sign-on and delegated authorization between wealth platform components using industry-standard identity protocols.

Designing asynchronous, event-driven systems where platform actions (trade execution, account opening) trigger downstream workflows in real time.

Composing LLM + retriever + validator + human-in-loop pipelines (n8n / LangGraph thinking).

Decomposing portfolio return relative to benchmark into allocation, selection, and interaction effects using Brinson model or factor-based attribution.

Designing the household-level reporting & secure-doc experience without breaking advisor workflow.

Broadridge's back-office and advisory platform suite used by broker-dealers and banks for account processing, advisory fee billing, and wealth operations.

Using integration-platform-as-a-service tools to orchestrate data flows between siloed wealth management applications without point-to-point custom code.

Using the Databricks Lakehouse platform and Spark for large-scale custodial data ingestion, transformation, and AI/ML workloads in wealth management environments.

Applying ML/statistical models to portfolio risk, factor attribution, and prediction.

Reading and explaining Monte Carlo plan outputs — when the 80% success number lies.

Electronic messaging standard for real-time securities order communication between wealth managers, OMS platforms, and broker execution venues.

Structured interviews with HNW/UHNW clients and translating goals into a plan.

Using embeddings and vector search (Pinecone, Weaviate, Azure AI Search, pgvector) to build semantic retrieval systems over financial documents and client data.