Data reconciliation in wealth management is the process of ensuring that information across multiple systems — custodian feeds, portfolio management platforms, CRMs, billing systems, and compliance tools — is consistent, accurate, and up to date. When systems don't share a common data model, reconciliation becomes a manual, daily exercise that consumes operations capacity and introduces errors at every step.
Where Reconciliation Breaks Down
Advisory firms run six, eight, sometimes a dozen systems — and every one of them thinks it's the system of record. The result is a daily matching exercise that operations teams absorb as routine, even as it consumes hours that could go toward firm growth.
Custodian-to-portfolio reconciliation
The most common daily task. Custodian position files arrive in different formats — Schwab vs. Fidelity vs. Pershing each deliver data differently. Portfolio systems reconcile holdings, but discrepancies in cash balances, pending transactions, and corporate actions require manual review. For multi-custodian firms, this scales linearly with complexity. Adding a custodian doesn't add a small amount of work — it adds a full reconciliation workflow.
CRM-to-portfolio reconciliation
Client information — names, addresses, account associations, household groupings — diverges between CRM and portfolio systems. Advisors update the CRM. Operations updates the portfolio system. Neither knows the other changed. Duplicate records, stale data, and household mismatches accumulate over time, quietly corrupting reporting and client communications downstream.
Billing reconciliation
Fee calculations require accurate position data, fee schedules, household groupings, and billing tiers — often sourced from multiple systems. When position data arrives late, accounts are grouped inconsistently, or fee schedules are maintained in spreadsheets alongside the billing platform, errors are inevitable. A $2B AUM firm with even a 0.3% billing error rate leaves significant revenue on the table — and creates client service issues that erode trust.
Planning-to-portfolio reconciliation
Financial plans should reflect current portfolio positions. But planning tools pull data on different schedules than portfolio systems update. Plans based on month-old position data produce recommendations disconnected from reality. Advisors presenting stale plans to clients lose credibility in the moments that matter most — review meetings, market events, major life changes.
Compliance reconciliation
Compliance needs data from every system — portfolio (trading activity), CRM (communications), billing (fee history), and custodians (account changes). When these systems don't reconcile automatically, compliance teams build shadow databases to assemble the views regulators require. This creates its own data quality risk: a compliance database is only as accurate as the manual processes that feed it.
The Cost of Manual Reconciliation
The direct costs are visible — operations staff hours, billing errors, delayed reporting. The indirect costs are harder to see but often larger: talent retention, strategic capacity, and the compounding effect of decisions made on data that was already stale before the meeting started.
Operations labor
Teams spending 15-25 hours per week on manual data matching — hours that belong to process improvement, client experience, and firm growth.
Error propagation
Manual processes introduce errors that cascade through reporting, billing, and compliance. One bad record doesn't stay in one place.
Delayed reporting
Quarter-end reporting takes days because data must be assembled before analysis can begin. By the time reports are ready, the moment has passed.
Scalability ceiling
Manual reconciliation does not scale. Adding a custodian or system adds a linear increase in work — which is why growth creates an operations crisis.
Staff burnout
Talented operations professionals spend their time on data mechanics instead of firm improvement. The best people leave for firms that have solved this.
Audit risk
Manual processes lack the audit trails regulators expect for data handling. Shadow spreadsheets are not compliance documentation.
Operational vs. Analytical Reconciliation
This is the most important distinction that most advisory firms have not made explicitly — and it explains why firms that have "solved" reconciliation through their portfolio system still spend hours every week matching data in spreadsheets.
What portfolio systems do
Portfolio systems like Orion, Tamarac, and Black Diamond reconcile custodian feeds for daily operations — positions, transactions, cash balances. This is their core job and they do it well. Custodian-to-portfolio reconciliation is a solved problem for firms using a quality portfolio management platform.
What almost no firm has solved
Unifying data across all systems — portfolio, CRM, planning, billing, compliance — into a single consistent model for analytics, AI, and business intelligence. This is what portfolio systems were not built to do. Most firms solve operational reconciliation through their portfolio system. Almost no firms have solved analytical reconciliation — which is why cross-system questions still require spreadsheets.
The implication is important: if your operations team still spends significant time reconciling data even though you have a modern portfolio management platform, you are experiencing an analytical reconciliation problem — not an operational one. A better portfolio system will not fix it.
The Unified Data Layer Approach
Milemarker addresses analytical reconciliation — the layer above your portfolio system — by creating a single normalized data model that every system feeds into. The operational workflow of your portfolio system stays exactly as it is. Milemarker sits above it, connecting everything else.
Milemarker ingests data from 130+ advisory technology platforms into a single Snowflake data warehouse, normalized against a wealth management-specific model. The same account structure, same position schema, same client identity — regardless of which system it came from.
How it works
- Broad integration. Milemarker connects portfolio systems (Orion, Tamarac, Black Diamond), CRMs (Salesforce, Redtail, Wealthbox), custodians (Schwab, Fidelity, Pershing), planning tools (eMoney, MoneyGuidePro, RightCapital), billing platforms, and compliance systems through 130+ pre-built integrations.
- Normalized data model. Data from every source is mapped to the same wealth management-specific schema. Client records from Salesforce and Orion resolve to the same master identity. Positions from Schwab and Fidelity use the same structure. Households match across billing and portfolio systems.
- Master data management. Deduplication, household matching, and entity resolution run automatically across systems. The same client doesn't appear as three different records with slightly different names.
- Automated pipelines. Data flows daily — or more frequently — without manual intervention. When the custodian file arrives, it processes automatically. There is no morning queue of files to run.
- Snowflake-native. All data lives in a Snowflake warehouse your firm owns. Your analytics team can query it directly. Your BI tools connect natively. Your AI models have access to every system's data in one place.
The result is that analytical reconciliation — the cross-system matching that currently consumes 15-25 hours of operations time per week — happens automatically, continuously, and at scale. Your operations team stops being a data pipeline and starts being a driver of firm improvement.