Executive summary
Wealth data is distributed across CRM, onboarding, core and custody, portfolio accounting, planning, market data, document, communication, supervision, compliance, billing, reporting, and vendor platforms. The same client, household, product, asset, goal, restriction, or advisor may be represented differently in each system.
Before using AI for recommendations, summaries, alerts, service actions, or analytics, the institution needs governed data products tied to material decisions. Ownership, meaning, lineage, quality, access, consent, retention, issues, and evidence must be clear enough for operators and reviewers to trust the result.
Prioritize critical decisions and data
Begin with use cases such as onboarding, suitability, household reporting, advice preparation, service prioritization, supervision, fees, complaints, or attrition. Identify the elements whose failure could change the outcome or create client harm.
Assign authority and stewardship
Name business owners for client, household, account, product, portfolio, goal, risk, advisor, interaction, consent, and control domains. Define authoritative sources, permitted consumers, quality expectations, and issue decisions.
Trace lineage through transformations
Document how data enters, changes, aggregates, resolves identities, derives features, feeds models, appears in reports, and reaches decisions. Include vendor and manual transformations, not only internal pipelines.
Govern AI use explicitly
Record training and inference sources, feature definitions, permitted purpose, sensitive attributes, access, retention, explanations, monitoring, human review, outcome feedback, and change approval.
Foundation controls to establish first
- Authoritative client, household, account, product, and advisor identifiers
- Critical-data definitions, owners, lineage, quality thresholds, and exceptions
- Consent, privacy, access, retention, and permitted-use rules
- Reconciled metric and reporting definitions
- AI and analytics inventory linked to data products and material decisions
From guidance to operating capability
Governance should make trustworthy use easier, not create a parallel documentation exercise. The strongest model embeds ownership and controls in the systems, workflows, pipelines, decisions, and issue routines where data changes an outcome.
Cicrim helps wealth organizations design data domains, ownership, quality, lineage, access, monitoring, issues, evidence, and responsible AI operating controls.
