SERVICES
A controlled data layer across administrators, banks, brokers and portfolio sources.
Collect, map, normalise and validate fragmented operating data so teams stop rebuilding the same spreadsheet every reporting cycle.
Overview
Data aggregation brings information from providers, systems, files and documents into a reusable governed dataset. Sources can include administrators, custodians, prime brokers, banks, OMS/PMS, market-data vendors, portfolio companies, borrowers, underlying funds and internal spreadsheets.
It is the foundation for reconciliation, portfolio reporting, risk, performance, management reporting and AI-enabled operations.
Why it matters
The challenge is not merely connecting APIs. Financial data differs in identifiers, dates, currencies, definitions, timing and granularity. Without mapping, quality rules and lineage, aggregation can create false confidence.
Common operating challenges
- Many provider formats and delivery methods.
- Repeated spreadsheet copying/joins.
- No common security/entity/account identifiers.
- Definitions differ across reports.
- No lineage for where a number came from.
- Permissions inconsistent across datasets.
What we deliver
| Capability | What it covers |
|---|---|
| Source inventory | Catalogue data, owners, frequency and permissions. |
| Ingestion | Connect files, APIs, databases and documents. |
| Mapping | Standardise identifiers, entities, accounts and fields. |
| Harmonisation | Align units, currency, dates and definitions. |
| Quality control | Check completeness, duplicates and reasonableness. |
| Publishing | Release governed datasets to downstream workflows. |
Our role can be configured around a defined operating mandate: a recurring managed service, a technology-enabled client workflow, or a co-sourced model in which execution and review are split between Kelton, the client and appointed providers.
Inputs, workflow and outputs
Typical inputs
- Administrator files
- Custodian/PB/bank data
- OMS/PMS
- Market/reference data
- Portfolio-company / borrower data
- Underlying fund statements
- Spreadsheets/databases/documents
Controlled workflow
| Step | Activity | What happens |
|---|---|---|
| 1 | Inventory | Define source, owner, frequency and field meaning. |
| 2 | Ingest | Bring data into controlled staging. |
| 3 | Map | Standardise identities and definitions. |
| 4 | Validate | Run quality/reconciliation checks. |
| 5 | Resolve | Route exceptions to source/owner. |
| 6 | Publish | Release approved dataset with lineage. |
Typical outputs
- Source catalogue
- Data dictionary
- Mapped/harmonised dataset
- Quality exception report
- Source lineage
- Reusable reporting/analytics layer
Controls and review
The workflow is designed so that automation does not obscure responsibility. Routine processing can be standardised; exceptions, material judgements and formal approvals remain visible and attributable.
- Source ownership/permissions.
- Field-level lineage.
- No silent transformation rules.
- Versioned mappings/data definitions.
- Reconciliation to authoritative sources.
Responsibility boundary
Data aggregation does not make third-party information authoritative and does not constitute investment advice. Source ownership, provider records and interpretation remain with responsible parties.
Technology & expertise
Our operating model combines specialist knowledge with controlled technology. Domain experts define the rules, review logic and exception criteria; the technology layer makes the workflow repeatable, traceable and scalable.
Technology
- ETL/ELT pipelines.
- File/API/document ingestion.
- Entity/security master mapping.
- Data-quality rules.
- Lineage/metadata and permissioned access.
Expertise
- Investment-operations data.
- Administrator/bank/PB file structures.
- Data governance/mapping.
- Operational exception management.
Expert knowledge is converted into controlled rules, SOPs, checklists, validation tests and exception criteria so that the operating standard is embedded in the workflow rather than dependent on one individual.
Delivery models
| Model | How it works |
|---|---|
| Managed Operations | We execute the agreed recurring workflow. Client and appointed-provider approvals remain explicit. |
| Technology Enablement | We implement the data, workflow and control layer for the client team to operate. |
| Hybrid / Co-sourced | Execution and review are shared through a documented responsibility and escalation model. |
| Transition & Implementation | We mobilise the workflow during a launch, provider change or target-operating-model transition. |
Frequently asked questions
Is this just a data warehouse project?
It may use a warehouse, but the commercial service is a governed operating-data layer, not infrastructure for its own sake.
Can Excel remain part of the workflow?
Yes. The aim can be to govern/connect existing tools rather than force immediate replacement.
Why does lineage matter for AI?
AI outputs are safer when the underlying source, definition, date and permission are traceable.
Discuss Data Aggregation
Start with one workflow, one operating issue or one provider transition. We will map the current process, responsibility boundaries, required data and a practical first engagement.