— Industries · Financial services
Financial services data governance on one lakehouse regulators can follow.
Banks, lenders, insurers and advisers carry customer data across core systems, CRMs, loan platforms and spreadsheets. Our financial services data governance work brings it into one governed lakehouse, so a breach review, a model decision or an auditor’s question can be answered from records rather than reconstructed from memory.
30+ years inside IBM · EY · J&J · McKesson
Lean Six Sigma Master Black Belt
AIMContext from $3,500
60-Day Ship Guarantee
— The pattern · Where it breaks
The data exists. Nobody can find it in time.
Customer data in ten systems.
The same client appears in the core platform, the CRM, a loan system and a shared drive. After an incident, working out whose data was touched becomes a manual hunt across silos.
Symptom: incident reviews measured in weeks, not days.
Models without a paper trail.
Credit, fraud and pricing models make decisions, but the inputs, the model version and any human override are not stored where they can be retrieved later.
Symptom: an adverse-action question nobody can answer from data.
Logs nobody reviews.
Payment and security logs are kept because they must be, then reviewed by hand or not at all, which is exactly what the newer card-data rules no longer accept.
Symptom: a log review that happens once a quarter.
— The work · What we build
What financial services data governance looks like on the lakehouse.
Customer data inventory
Every system that holds customer information catalogued in Unity Catalog, with owners and sensitivity tags, so an incident review starts with a query, not a spreadsheet.
Lineage across systems
Table and column lineage from source systems to reports and models, so you can show where regulated data flows.
Decision records
Model inputs, versions, outcomes and human review captured as queryable data for credit and other automated decisions.
Automated log review
Payment and security logs landed in a security data lake, normalised, and reviewed automatically with evidence kept for assessors.
Access and masking
Group-based grants, masking of account and card fields, and a deliberate decision about what AI assistants may read.
Orchestrated pipelines
Ingestion and transformation jobs that carry these controls with them, with failure alerts and a named owner.
— The approach · One inventory
A breach clock is a data problem before it is a legal one.
SEC Regulation S-P now expects covered firms to run an incident response programme and notify affected customers within a fixed window. Meeting that depends on one thing: knowing, quickly, which systems held whose data and who accessed it.
That is an inventory, lineage and logging problem. We build those on one governed lakehouse so the answer comes from records, and counsel can make the notification call on facts.
— The method · AIM-IT
Five phases. Every build, every time.
Assess, Innovate, Model, Implement, Track. Each phase ends with something you can inspect and sign off, not a slide.
01 · ASSESS
Assess
Scope and inventory
Customer data sources, models and logs in scope, with owners.
02 · INNOVATE
Innovate
Control design
Access, masking, lineage, decision records and log review designed once.
03 · MODEL
Model
One flow end to end
One regulated flow, for example lending or payments, governed and evidenced.
04 · IMPLEMENT
Implement
Roll out
Remaining priority flows brought under the same controls with your team.
05 · TRACK
Track
Control plan
What is checked, how often and by whom, ready for the next exam or assessment.
— The deliverable · What you get
Financial services data governance with a fixed scope.
AIMContext
Governed customer data foundation, fixed scope.
Most engagements start with AIMContext, the fixed-scope build of a governed foundation:
- A customer data inventory with owners and sensitivity tags.
- Lineage from source systems to the reports and models that use them.
- Automated review of payment and security logs, with evidence kept.
- Decision records for automated credit or risk decisions where they apply.
- A control plan your team runs after we leave.
We build the evidence and controls; your counsel and assessors make the compliance call.
$3,500+
14 days
5 phases
60 days
60-Day
Ship Guarantee
On every Sprint engagement: if we do not deliver the agreed working artifact in 60 days, you do not pay the final invoice. That is what AIM-IT is for.
— The discipline · Process first
Fix the hand-offs, then automate them.
Most compliance gaps in financial services sit in the hand-offs: a file exported for a regulator, a model retrained on a copy, a spreadsheet that became a system. We map those with Lean Six Sigma discipline before we touch the platform.
The result is a lakehouse where the controlled path is also the easy path, which is the only kind of control that lasts.
— Related reading · From the blog
Go deeper on financial services data.
Logs
Retention rules side by side, and one design.
PCI DSS
Automated log review with evidence.
Silos
Why silos make every deadline harder.
Decisions
The data work behind automated-decision rules.
Security
One normalised home for security logs.
Lineage
What auditors ask for and where lineage breaks.
— Straight answers · FAQ
Questions we get asked first.
Are you a Databricks partner or certified?
No, and we will not imply otherwise. Certification is in preparation, and we are not in the Databricks partner programme. What we bring is thirty years of delivering the enterprise systems this data comes out of, inside IBM, Ernst & Young, Johnson & Johnson and McKesson, plus Lean Six Sigma at Master Black Belt level. Ask us for the work, not the badge.
Do you handle core banking or payment systems directly?
We work with the data those systems produce: extracts, change feeds and logs landed in your lakehouse. We do not replace core platforms, and we scope integration against what your vendors actually expose.
Will this make us compliant with Regulation S-P or PCI DSS?
It produces the evidence those rules ask for: inventory, lineage, access controls and reviewed logs. Your counsel and your assessor decide whether it meets the requirement for your firm.
Can AI assistants be used safely on customer data?
Yes, if they read governed data rather than every system their user can reach. We decide what an assistant may see, mask sensitive fields and log what it touches.
What does it cost?
AIMContext starts at $3,500 for a fixed-scope governed foundation, with a typical first build in 14 days. Larger programmes are quoted after scoping, and every engagement carries the 60-Day Ship Guarantee.
Start with one regulated flow, not the whole bank.
One call, your systems and your exam or assessment calendar on the table, and a straight read on where the evidence gaps are.