Schwab + Fidelity + Pershing + Altruist data finally in one place. The infrastructure RIAs are quietly standardizing on.

Snowflake for RIAs is a cloud-native data warehouse that consolidates custodian feeds, portfolio management data, CRM, billing, and financial planning outputs into a single normalized analytical layer — giving advisors and operations teams a unified view of the entire book that no single vendor system can provide.

Most RIAs today run somewhere between six and twelve software systems. Each one holds a slice of the client picture. Schwab holds positions. Orion holds performance history. Salesforce holds relationship notes. MoneyGuidePro holds planning scenarios. None of them talk to each other at the data layer. The result is a firm that knows a lot but can see very little of it in one place at one time.

Snowflake changes that architecture. It is not another reporting tool. It is the data layer underneath your reporting tools — a cloud warehouse where every system's data lands, normalizes, and joins. For an overview of how this fits the broader financial services landscape, see our Snowflake for Financial Services pillar.

Why RIAs Are Choosing Snowflake

The shift toward Snowflake among growth-oriented RIAs is not driven by technology enthusiasm. It is driven by a specific operational pain that accumulates as firms scale: the multi-custodial reconciliation problem.

The Multi-Custodial Reconciliation Problem

An RIA with $2 billion in AUM typically has clients at three to five custodians. Each custodian delivers overnight position files in its own format, on its own schedule, with its own quirks. A Schwab position file does not look like a Fidelity position file. Pershing's transaction codes do not match Altruist's. Reconciling these into a single book view requires either expensive custom middleware or manual work by back-office staff who spend Monday mornings correcting Friday's numbers.

Snowflake does not solve the custodian data problem alone — but it gives firms the platform to solve it once, correctly, and permanently. Pre-built connectors normalize each custodian's data into a consistent schema. Once in Snowflake, a Schwab account and a Fidelity account are just accounts in the same table. Cross-custodian queries run in seconds.

The Reporting Tool Ceiling

Portfolio reporting tools like Orion, Black Diamond, and Tamarac are excellent at what they were designed to do: produce client-facing performance reports and support rebalancing workflows. They were not designed to be analytical data warehouses. Their data models are proprietary. Their query interfaces are limited. Joining portfolio data with CRM data or billing data requires exporting to spreadsheets and assembling manually.

Snowflake sits behind these tools, not in place of them. It receives data from Orion, from Schwab, from Salesforce — and makes all of it queryable together. The reporting tool keeps doing what it does well. Snowflake handles what it cannot.

The AI Readiness Problem

RIAs increasingly want to use AI for client segmentation, churn prediction, and advisor productivity analytics. AI models require clean, structured, queryable data — exactly what Snowflake provides. A firm whose data lives in custodian portals and portfolio system exports cannot effectively leverage AI tools. A firm whose data lives in Snowflake can. See also: AI-Ready Data for Wealth Management.

Without Snowflake

✕Multi-custodian reconciliation done manually each week

✕Portfolio data and CRM data never in the same query

✕Billing calculated in spreadsheets each quarter

✕Compliance monitoring reactive and manual

✕AI and advanced analytics out of reach

✕Each new system integration is a custom project

With Snowflake

✓Automated daily reconciliation across all custodians

✓Portfolio, CRM, billing, planning data in one schema

✓Billing calculated and reconciled automatically

✓Compliance thresholds monitored continuously

✓Structured data ready for AI and ML workflows

✓New integrations added via standardized connectors

What Lives in a Snowflake-Powered RIA Stack

A Snowflake-powered RIA data stack is not a single system — it is a data layer that receives from, enriches, and feeds back into every major system the firm uses. Understanding what data lives in Snowflake clarifies why it is foundational rather than redundant.

Custodian Feeds

Daily position, transaction, and account files from Schwab, Fidelity, Pershing, Altruist, and any other custodian the firm uses. Pre-built connectors normalize each custodian's proprietary format into a consistent schema. Accounts, positions, and transactions at different custodians share common column names and data types — enabling cross-custodian analysis with standard SQL.

Portfolio Management System

Performance history, account groups, benchmarks, and model allocations from Orion, Black Diamond, Tamarac, or Addepar. Snowflake receives this data and enables analysis that the portfolio system's own reporting cannot support — such as comparing performance across custodians, linking performance to client segmentation data, or joining performance records with billing histories.

CRM Data

Client relationship data from Salesforce, Redtail, Wealthbox, or Practifi — including household structure, relationship type, referral source, life events, and service tier. Joined with portfolio data in Snowflake, CRM data enables client segmentation analytics that reveal which client profiles are most profitable, which have highest attrition risk, and where advisory capacity is best deployed.

Billing and Fee Data

Advisory fee schedules, billable AUM calculations, and fee revenue by client, advisor, and service tier. Billing data in Snowflake enables revenue analytics that portfolio systems and CRMs cannot produce in isolation — monthly recurring revenue by segment, effective fee rate by AUM tier, revenue impact of client churn or growth.

Financial Planning Outputs

Planning scenario data from MoneyGuidePro, eMoney, or RightCapital — including projected retirement income, Monte Carlo results, and goal-funding status. When planning outputs land in Snowflake alongside actual portfolio data, advisors can track how client outcomes are tracking against plan and surface accounts where a planning conversation is overdue.

130+

Pre-built integrations covering custodians, portfolio systems, and CRM platforms

Daily

Automated multi-custodian reconciliation with exception alerting

1 schema

Normalized data model across all custodians and systems

How Snowflake Solves the Multi-Custodial Reconciliation Problem

Reconciliation is the unglamorous core of RIA operations. Every business day, positions held at multiple custodians must be verified against portfolio system records. Discrepancies must surface. Exceptions must be investigated and resolved. For firms running this manually, reconciliation consumes hours of back-office time every morning — time that does not scale linearly with AUM growth.

The Normalization Layer

Snowflake's role in reconciliation begins with normalization. Pre-built connectors pull each custodian's overnight files and transform them into a common schema: a standardized account table, a standardized position table, a standardized transaction table. Security identifiers are resolved to a common reference (typically CUSIP or ISIN). Custodian-specific account codes are mapped to the firm's internal account structure. This normalization happens before any analyst touches the data.

Once data is normalized, cross-custodian reconciliation becomes a SQL query rather than a manual spreadsheet exercise. Position counts from Schwab and Fidelity on the same security are directly comparable because they share the same schema. Discrepancies between custodian records and portfolio system records surface as exceptions in a structured report rather than requiring manual comparison.

Automated Exception Reporting

With all custodian data in Snowflake and the portfolio system feeding records into the same warehouse, automated exception detection becomes straightforward. A scheduled query runs each morning, comparing custodian position balances against portfolio system records, flagging any account where the discrepancy exceeds a defined threshold. Back-office staff see a prioritized exception list rather than raw position files to compare manually.

The same approach applies to cash reconciliation, transaction matching, and corporate action processing. Each reconciliation type becomes a repeatable query rather than a manual process — consistent, auditable, and scalable as the firm grows without adding back-office headcount.

Architecture pattern

Custodians in, one schema out.

Schwab, Fidelity, Pershing, and Altruist each deliver daily files. Connectors normalize each feed into Snowflake's unified position, transaction, and account tables. Portfolio system records reconcile against these tables automatically. Exceptions surface as structured alerts. Analysts see a clean exception list rather than raw custodian files.

This is the architecture that turns multi-custodial reconciliation from a daily manual exercise into a supervised automated process — one that scales to five custodians or fifteen without changing the back-office workflow.

Snowflake for RIAs vs. Building Your Own Stack

Some RIAs — typically those with engineering resources and a specific vision for their data infrastructure — choose to build Snowflake integrations in-house. Others work with a platform like Milemarker that brings pre-built connectors, a purpose-built data model, and managed pipelines. The right choice depends on the firm's engineering capacity, timeline, and long-term infrastructure ambitions.

Time to first data

• Build In-House: 6–18 months of engineering

• Milemarker on Snowflake: 6–10 weeks with pre-built connectors

Custodian connectors

• Build In-House: Built and maintained by your team

• Milemarker on Snowflake: 130+ pre-built, Milemarker-maintained

Data model

• Build In-House: Designed from scratch

• Milemarker on Snowflake: Purpose-built RIA data model, production-proven

Custodian format changes

• Build In-House: Your engineering team absorbs the change

• Milemarker on Snowflake: Milemarker absorbs the change

Data ownership

• Build In-House: Full — your Snowflake account

• Milemarker on Snowflake: Full — your Snowflake account

BI tool flexibility

• Build In-House: Any tool you choose

• Milemarker on Snowflake: Any tool you choose — plus pre-built Navigator dashboards

Ongoing engineering cost

• Build In-House: Dedicated team required

• Milemarker on Snowflake: Milemarker team handles pipeline maintenance

Risk of integration failure

• Build In-House: Internal — requires on-call engineering

• Milemarker on Snowflake: Milemarker SLA-backed with monitoring

Both paths lead to the same outcome: a Snowflake data warehouse the RIA fully owns and controls. The difference is time, cost, and ongoing maintenance burden. For firms without a dedicated data engineering team, the build-in-house path routinely takes 18 months and significant budget before any analytics are possible. Milemarker's approach compresses that to weeks.

Where Milemarker Fits

Milemarker is a Snowflake-native platform built specifically for wealth management firms. For RIAs, that means pre-built connectors to every major custodian and portfolio system, a purpose-built RIA data model, and managed pipelines that keep data flowing without requiring internal engineering resources to maintain them.

Augments, Never Replaces

Milemarker does not replace your existing Snowflake setup if you have one. It augments it. If you have already built pipelines from Schwab or Orion, Milemarker can add the connectors you are missing, extend your data model with Milemarker's purpose-built schema, or take over pipeline maintenance so your engineering team can focus on higher-value work.

If you are starting from zero, Milemarker builds the entire Snowflake infrastructure — account provisioning, connectors, data model, and BI layer — deploying into a Snowflake account that you own. Your data never lives in a Milemarker-controlled black box. The Infrastructure for Wealth is the phrase we use to describe this: foundational, firm-owned, purpose-built.

Milemarker Navigator

For RIAs that want to move from raw data to operational analytics quickly, Milemarker Navigator is a pre-built analytics layer that runs on your Snowflake warehouse. AUM dashboards, client segmentation reports, billing analytics, and advisor productivity metrics — all available out of the box and fully customizable because they read from your warehouse directly.

01

Snowflake-Native Architecture

All data lands in a Snowflake account you own. No proprietary storage. Full SQL access to every table.

02

130+ Pre-Built Connectors

Every major custodian, portfolio system, CRM, and planning tool — pre-built, maintained, and monitored by Milemarker.

03

RIA Data Model

A purpose-built schema for multi-custodial RIA data — households, accounts, positions, billing, and planning in one normalized model.

04

Managed Pipelines

Milemarker manages the pipeline infrastructure. When custodians change their formats, Milemarker absorbs the change. No on-call engineering required.

05

BI-Agnostic Output

Connect Tableau, Sigma, Looker, Power BI, Hex, or any other tool to your Snowflake warehouse. Navigator provides pre-built dashboards for firms that want to start fast.

06

AI-Ready Data Structure

Normalized, structured data in Snowflake is the foundation for AI-powered analytics — client scoring, churn prediction, advisor productivity. See our AI-ready data guide.

For RIAs exploring a broader data platform strategy beyond Snowflake-specific infrastructure, see our guide to data warehouse architecture for RIAs and our overview of wealth management data platforms more broadly.

Frequently Asked Questions

Why are RIAs choosing Snowflake over their portfolio reporting tool's built-in data?

Portfolio reporting tools like Orion, Black Diamond, and Tamarac are excellent at producing client-facing reports but were not designed as analytical data warehouses. They lock data inside proprietary schemas, limit ad hoc querying, and make it difficult to join portfolio data with CRM, planning, or billing data. Snowflake gives RIAs a neutral data layer where every system's data lives together, queryable in standard SQL, accessible to any BI tool, and shareable with outside partners without giving up control of the source data.

How does Snowflake handle multi-custodial data for RIAs?

Snowflake ingests position, transaction, and account data from each custodian — Schwab, Fidelity, Pershing, Altruist, and others — through pre-built connectors that normalize the data into a consistent schema. Once in Snowflake, accounts at different custodians appear in the same tables with the same column names. RIAs can run cross-custodian performance attribution, billing reconciliation, and compliance queries without writing custodian-specific logic for each data source.

Is Snowflake secure enough for RIA client data?

Yes. Snowflake maintains SOC 2 Type II certification, encrypts data at rest and in transit by default, and supports role-based access controls down to the column level. For RIAs operating under SEC and state RIA regulations, Snowflake's audit logging, multi-factor authentication, and network policy controls meet enterprise security standards. Data never leaves your Snowflake account unless you explicitly configure a share.

What does it cost to run Snowflake as an RIA?

Snowflake pricing is consumption-based: you pay for storage per terabyte and compute credits consumed by queries. For a typical mid-size RIA running daily reconciliation and moderate BI query volume, annual Snowflake infrastructure costs typically range from $15,000 to $80,000 depending on data volume. The larger cost consideration is implementation — building pipelines and a data model from scratch typically costs $300K to $1M over 12 to 18 months. Milemarker's pre-built RIA data model and 130+ integration library reduce that dramatically.

How long does it take to get an RIA onto Snowflake?

With Milemarker's pre-built RIA data model and managed pipelines, RIAs with standard custodian connections typically see initial production data within 6 to 10 weeks. Full BI dashboard deployment — connecting Tableau, Sigma, or Hex to the Snowflake warehouse — typically adds 2 to 4 weeks. The total timeline from kickoff to operational analytics is typically 8 to 14 weeks, compared to 12 to 24 months for a custom build.

Can I keep my existing portfolio reporting tool and add Snowflake?

Yes — and this is the typical pattern. Snowflake augments rather than replaces portfolio reporting tools. Orion, Black Diamond, or Tamarac continue to handle client-facing reporting and rebalancing. Snowflake sits behind them as the analytical data layer — receiving data from custodians and portfolio systems, enabling deeper analysis, and feeding BI tools. Milemarker is specifically built on this pattern: augment your existing stack with a proper data infrastructure without ripping out what already works.

What BI tools work with Snowflake for RIAs?

All major BI tools connect natively to Snowflake via JDBC/ODBC or native connectors: Tableau, Looker, Power BI, Sigma, Hex, and others. dbt and other transformation frameworks also work directly against Snowflake. RIAs can use whichever tool their team is most comfortable with — or multiple tools for different audiences — all reading from the same underlying data warehouse.

What is Milemarker Navigator and how does it relate to Snowflake?

Milemarker Navigator is a purpose-built analytics platform for wealth management firms that runs natively on Snowflake. It provides pre-built dashboards for AUM analysis, client segmentation, billing reconciliation, and advisor productivity — all reading from the firm's own Snowflake warehouse. Navigator accelerates time-to-insight for RIAs that want operational analytics without building custom dashboards from scratch.

RELATED RESOURCES

Pillar Snowflake for Financial Services & Wealth Management By Segment Snowflake for Broker-Dealers: One Warehouse for the Whole Enterprise By Segment Snowflake for TAMPs: The Multi-Tenant Data Layer Behind a Modern TAMP Data Platform What is a Wealth Management Data Platform? AI Readiness AI-Ready Data for Wealth Management

Related guides

Part of the Snowflake for Wealth series:

• Snowflake for Financial Services & Wealth Management

• Migrating from On-Prem to Snowflake

• Snowflake vs Databricks for Financial Services

• Snowflake Cortex for Financial Services. AI Where Your Data Already Lives.

• Implementing Snowflake at a Wealth Firm: 8 Weeks vs 18 Months

• Snowflake vs BigQuery for Wealth Management