Wealth Management M&A · Data Integration
Keep RIA acquisitions moving when data conversion becomes the bottleneck.
Every acquisition brings another combination of portfolio systems, CRM data, custodians, billing rules, performance history and legacy conventions.
DataLux adds specialist data engineering during acquisition peaks. We profile, map, transform, reconcile and remediate data inside your existing integration program—without replacing your team or your platform vendor.
Source environment
Defined data workstream
Acquirer’s standard platform
Vendor-managed standard migration + agreed data handoff
The problem
The acquisition date is fixed. The data complexity isn't.
Each acquired firm carries its own operating history. The standard conversion path rarely accounts for every convention, source and exception—and several deals can pile up at once.
Legacy surprises surface late.
Historical depth, custom fields, spreadsheets and undocumented rules become visible after the cutover plan is already underway.
Client-facing history must tie out.
Positions, transactions and performance history need to reconcile to the agreed source of truth before teams can rely on the new environment.
Billing rules aren't a simple import.
Tiered fees, household aggregation, negotiated rates and legacy exceptions can produce discrepancies if the logic is not explicitly tested.
The capacity mismatch
Acquisition workload spikes. Permanent teams don't.
Bring in a defined specialist workstream when the integration queue exceeds the capacity of the team you already have.
Where DataLux fits
We don't replace your integration team. Or your platform vendor.
The cleanest engagement leaves ownership where it already belongs and adds engineering only where the workload is hard to absorb.
Your integration team
- Acquisition integration plan
- Business decisions and stakeholders
- Platform strategy
- Final acceptance
DataLux
- Source profiling
- Mapping and transformation
- Historical and non-standard data
- Reconciliation and billing validation
- Exception remediation and cutover support
Platform vendor
- Destination data model
- Native import tooling
- Standard platform onboarding
- Vendor-specific conversion process
One integration program. Clear ownership. Extra engineering where the workload peaks.
What we take off your team
A bounded data workstream. Not an open-ended consulting assignment.
Scope is agreed around the acquisition and closes against deliverables, acceptance criteria and a documented handoff.
Profile the acquired environment
Inventory systems, extracts, custodians, historical depth, custom fields, billing rules and dependencies.
Map source to destination
Define source-to-target mappings across accounts, households, holdings, transactions, CRM entities and required datasets.
Transform and clean
Normalize inconsistent data, implement transformation rules and prepare non-standard sources for conversion.
Reconcile what moved
Validate positions, transactions, historical performance, entities and other critical datasets against agreed rules.
Validate fees and billing
Test fee schedules, household-level aggregation, negotiated rates and exceptions before they surface downstream.
Close exceptions before cutover
Classify discrepancies, remediate what can be fixed, rerun validation and produce a documented handoff.
Example engagement
One acquisition. One workstream. A measurable finish line.
A typical scope moves from discovery into engineering, validation and handoff rather than disappearing into an open-ended pool of hours.
Discover & profile
Source inventory, historical-depth assessment, data-quality profiling, mapping requirements and acceptance criteria.
Map & transform
Source-to-target mappings, normalization, cleanup, transformation engineering and conversion support.
Reconcile & remediate
Positions, transactions, performance history, billing, household structures and exception closure.
Close the workstream
Agreed deliverables complete, critical exceptions resolved or formally escalated, and a documented handoff accepted.
Timing is illustrative. Actual duration depends on source systems, history, access, volume, custom rules and destination-platform requirements.
The operational difference
Same acquisition. Less conversion work on your internal team's critical path.
Without a specialist workstream
Internal team absorbs itAcquisition closes
Your team begins profiling unfamiliar legacy data.
Migration progresses
Standard conversion moves forward while non-standard exceptions accumulate.
Cutover approaches
Senior staff are mapping, reconciling and chasing missing data at the same time.
Final weeks
The integration team itself becomes the remediation team.
With a DataLux workstream
Defined ownershipAcquisition closes
DataLux profiles the agreed data scope alongside your integration owner.
Migration progresses
Mappings, transformations and non-standard sources are handled in parallel with vendor migration.
Reconciliation starts early
Exceptions are classified, investigated and closed against agreed thresholds.
Cutover approaches
Your integration lead keeps ownership while DataLux finishes the defined engineering workstream.
Why this delivery model
More than another pair of hands before cutover.
Scope you can actually approve
The engagement has defined outputs, assumptions and a finish line rather than an indefinite allocation of engineering hours.
Financial-data engineering depth
Portfolio data, history, billing, account structures and reconciliation behave differently from generic enterprise datasets.
Capacity at acquisition peaks
Add specialist engineering around integration peaks without permanently staffing for the busiest quarter of the year.
Why DataLux
Financial-services engineering, not a generic IT staffing pitch.
DataLux has worked in financial-services technology and data since 2008, delivering software, integration, analytics and data-engineering solutions in environments where accuracy, traceability and operational reliability matter.
Financial-services background
Experience spanning complex financial data, analytics, reconciliation and enterprise integration.
Senior delivery model
Experienced engineers and solution architects rather than a large junior delivery pyramid.
Business + data + engineering
The same delivery team can understand the source problem, engineer the transformation and validate the resulting data.
The data landscape
The environments an acquisition can bring together.
We scope the real source-to-destination combination, including legacy data and workflows the native import may not cover.
Portfolio & reporting
Orion · Tamarac · Addepar · APX · Axys · Black Diamond
CRM & household data
Salesforce · Wealthbox · Redtail · bespoke systems
Custodial data
Multiple custodians · account structures · transaction feeds
Other operational sources
Billing · spreadsheets · custom reporting · historical archives
Products are illustrative examples of systems encountered in the sector, not claims of DataLux certification, partnership or completed integrations with each vendor.
Data access & delivery
Work where your data already lives.
Where appropriate, delivery takes place inside your controlled environment rather than requiring an additional DataLux-hosted copy of sensitive datasets.
Access, endpoints, data handling and vendor due diligence are reviewed with your security team as part of engagement planning. Working in your environment does not eliminate your vendor-oversight process.
Request security informationClient-controlled access
Work inside agreed systems and access boundaries where appropriate.
Security review during scoping
Confirm controls, access and vendor requirements before engineering begins.
Defined data-handling terms
Document the working model and handoff rather than relying on informal assumptions.
Frequently asked questions
What integration leaders ask first.
Clear answers on scope, platform responsibilities and how the work is delivered.
Ask us about your situationYes—and we expect them to. DataLux does not replace the destination platform's native conversion process. We scope the adjacent engineering work: non-standard sources, transformations, reconciliation, billing validation, historical data and exceptions outside the standard import.
No. Your integration owner retains program decisions, stakeholders and final acceptance. DataLux is responsible only for the agreed technical workstream and its deliverables.
We propose a bounded project with a source inventory, agreed inputs, outputs, assumptions and completion criteria. If your need is simply for an indefinite named contractor, that is a different purchasing model.
Ideally once source systems and the target platform are known. Early profiling and acceptance-rule design can reveal data dependencies before the most time-sensitive conversion stages. Pre-close access depends on the transaction and your access constraints.
These can be scoped as specialist workstreams. We first establish available source records, historical depth, destination requirements and validation logic, then agree which transformation, comparison and remediation activities are feasible.
A narrowly scoped workstream is proposed at roughly three weeks; a broader acquisition-data workstream is usually planned around four to six weeks. Complex multi-platform or deep-history work needs separate discovery and estimation. These are scoping ranges, not a guaranteed timeline.
We agree completion criteria at the start. Typically these include delivered mappings and transformations, reconciliation against specified thresholds, a classified exception register, resolution or formal escalation of critical blockers, and an accepted handoff to your integration owner.
We can discuss delivery alongside an existing consultancy or implementation partner, subject to scope, commercial terms, access and your organization's security and vendor-approval requirements.
Bring us the real workstream
Have an acquisition in flight?
Bring us the integration problem sitting on your critical path. In a short working conversation, we'll establish whether specialist data engineering can take a defined piece of it off your team's plate.
- Source & destination stack
- What the vendor already covers
- Exceptions & target cutover
Prefer the website form? Contact DataLux here. If the work belongs with your existing team or platform vendor, we'll say so.