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Compliance posture travels with the data, or the audit fails.

SOC 2 controls, PCI scoping, data residency topology, audit-trail continuity, and append-only ledger semantics. Platform migrations for FinTech companies carry a compliance surface that gets designed before the first byte moves — not retrofitted after cutover.

What is different about FinTech platform migrations

The distinguishing feature is not technical complexity — it is the compliance surface that attaches to every data object. A transaction table is not just rows; it is a regulatory artifact with retention, residency, and lineage requirements that survive the migration or fail the next audit. Every FinTech migration the team carries is planned around that surface first.

The practical consequence is that Discovery produces two deliverables before execution begins: a technical inventory (tables, views, pipelines, downstream consumers) and a compliance inventory (residency classification per dataset, access control topology, audit log configuration, retention requirements). Execution does not start until both are signed off.

The migration shapes that appear most often

  • Append-only ledger migration. Transaction and ledger tables that are append-only by design are the most tractable to migrate — the source does not change once written. Migration proceeds by time-range batch with row-count and checksum verification per batch. The cutover window covers only the most recent records, minimizing risk. The reconciliation evidence records that the append invariant is preserved on the target.
  • Compliance-driven cloud sovereignty splits. Regulatory requirements that EU customer data stay in EU infrastructure often require a multi-region target topology. Discovery maps every dataset to its residency classification and designs an architecture where data never transits a non-compliant region. Mixed-residency datasets are split at the classification boundary before migration begins.
  • KYC/AML data lineage preservation. Screening decision records need to remain traceable to their data inputs through the migration seam. Source-system record identifiers are preserved, migrated lineage records are tagged with a migration-event marker, and downstream AML reporting queries are verified in parallel run before cutover authorization.
  • Fraud detection signal lakes. Historical signals migrate by time partition with checksum verification. The real-time ingestion path uses a dual-write window during execution — signals write to both source and target while the fraud model trains on current data. The dual-write window closes only after model inference drift stays within a defined threshold for the required period.
  • Transaction reconciliation harnesses. Any migration of tables downstream of payment processing needs a transaction reconciliation harness that compares source and target totals per settlement period. This is deterministic code, not a manual spot check. The harness runs continuously through the parallel-run window and is archived as part of the engagement evidence.

What a FinTech Discovery Sprint surfaces

  • Compliance control mapping: current SOC 2 / PCI controls mapped to their target-state equivalents, with gaps named.
  • Data residency classification: every dataset tagged by residency requirement, with the architecture for any multi-region topology.
  • Audit-trail continuity plan: cutover timestamp, retention window for the source, co-signed reconciliation evidence design.
  • Append-only table inventory: cutover window design per table, checksum approach, invariant preservation proof.
  • AML / KYC lineage map: source-system identifiers, lineage record migration path, parallel-run verification period.
  • Execution scope and fixed-fee quote for the migration.

Related reading

How to start

The fast path is a Cloud Cost X-Ray — 5 business days, names the top-20 cost drivers and the migration shape, compliance surface included, before any commitment. The fee credits 100% against Execution signed within 60 days. If the situation is past the diagnostic phase, book a 30-minute call and we will quote the Discovery Sprint directly.

Questions buyers actually ask

Before you book a call.

How does SOC 2 and PCI compliance posture transfer across a cloud migration? ▾
Compliance posture does not migrate automatically — it has to be re-established on the target. That means the access control topology, audit log configuration, encryption-at-rest and in-transit settings, network perimeter, and data classification tagging all get configured explicitly on the target before any sensitive data moves. Discovery maps the current compliance controls and produces a target-state configuration spec. Execution does not begin until the target environment passes a configuration review against that spec.
What is the audit-trail problem in a data warehouse migration? ▾
Regulators and auditors expect a complete, unbroken chain of record for financial transactions. A warehouse migration creates a seam in that chain if not handled explicitly. The approach is to preserve the source warehouse in read-only state for the regulatory retention window (typically 7 years for financial records) and document the cutover point precisely in the reconciliation evidence. The cutover document includes row-count parity, schema parity checksums, and the timestamp of last synchronized record per transaction table. That document is co-signed and archived as part of the engagement evidence package.
We have data residency requirements — our EU customer data cannot land in US infrastructure. How is that handled? ▾
Data residency constraints are first-class inputs to the migration architecture, not guardrails added at the end. Discovery maps every dataset to its residency classification (EU, US, APAC, or unrestricted) and produces an architecture where data never transits a non-compliant region. This often means a multi-region target topology — separate dataset instances per region with cross-region replication restricted to anonymized or aggregated data. The migration execution plan reflects that topology from wave 1.
Our ledger tables are append-only by design. Does that change how migration works? ▾
Append-only ledger tables are the most tractable to migrate because the source is stable once written. Migration proceeds by time-range batch: migrate all records up to a cutover timestamp, verify row count and checksum, then migrate the tail during the cutover window. The narrow migration window for recent records is where the risk concentrates. Discovery identifies every table with append-only semantics and plans the cutover window accordingly. The reconciliation evidence includes a per-table record that the append invariant is preserved on the target.
How do you handle KYC/AML data lineage across a platform migration? ▾
KYC and AML data lineage needs to survive the migration intact — the regulatory requirement is that you can trace a given screening decision back to the data inputs that produced it. The migration plan preserves lineage by keeping the source-system record identifiers stable through the move, tagging migrated lineage records with a migration-event marker, and verifying that downstream AML reporting queries produce consistent results against both the source and target in parallel run. The parallel-run window for AML workloads is typically 4 weeks before cutover is authorized.
What does fraud detection signal lake migration look like? ▾
Fraud signal lakes have two migration challenges: the historical signal data and the real-time ingestion path. Historical data migrates by time partition with checksum verification. The real-time ingestion path requires a dual-write window during execution — signals write to both source and target simultaneously so the fraud model continues training on current data while the migration is in flight. The dual-write window ends only after the target pipeline has passed a defined drift check: model inference outputs from source-trained and target-trained models must stay within a defined threshold for a minimum period.
How long does the Discovery Sprint take for a FinTech company? ▾
The Discovery Sprint is 10 business days fixed. For FinTech, the Sprint output includes a compliance control mapping (current state vs target state), a data residency classification for every dataset, an audit-trail continuity plan, an append-only table inventory with cutover window design, and the execution scope and fixed-fee quote. The additional compliance documentation does not extend the Sprint window.