Advisory

Data strategy
that holds up to scrutiny.

A data strategy is only worth something when it survives the day the auditors actually call. Not in the kickoff, not in the deck. So I build it against your live data estate, not against glossy slides.

Author: Andreas O. Schwan · Dipl.-Math. (FH) · Certified Banking Data Manager · see project history

Pillars

Three pillars, one outcome.

Strategy & governance

Target picture, data catalogue, lineage, clear accountabilities. At the level BaFin and the audit firms accept.

Data quality & migration

Attribute-level measurement. End-to-end test automation. Migrations the auditors do not pull apart.

AI integration & EU AI Act

Risk classification, LLM evaluation, governance. Drawn from real-world pilots, with a live BaFin dialogue running in the background.

Process

How I work

Take stock

Three days. Regulatory landscape, data estate, stakeholders. Output: a diagnosis that holds.

Plan with teeth

A real roadmap. Milestones, risks, escalation points. No slides, a plan.

Deliver in the field

Boots on the ground, with your team and my specialist network. We deliver, we do not just advise.

Hand over audit-ready

Documentation, training, escalation routines. You take over without losing sleep.

FAQ

Frequently asked questions

Common questions on data strategy for banks. Answered straight from 30 plus years of regulatory practice.

What is a data strategy for banks?

A data strategy for banks is a binding plan covering how data is captured, quality-assured, documented and used so that regulatory requirements (BaFin, MaRisk, Basel III, EU AI Act, DORA) are demonstrably met at any moment. It includes target picture, data catalogue, lineage, accountabilities and attribute-level data quality measurement.

How long does a defensible diagnosis take?

Three days. Enough time to get a fast read on the regulatory landscape, the data estate and the stakeholders. The output is a diagnosis that holds up and forms the foundation of the roadmap. No need for weeks of workshop loops.

What level of data quality is BaFin-ready?

BaFin and audit firms expect measurable data quality at attribute level with a documented measurement methodology. At Deutsche Bank, data quality was lifted from 78 to 96 percent during migration, based on automated, attribute-level measurement.

How do you make a data strategy EU AI Act compliant?

EU AI Act readiness needs AI risk classification, documented data lineage and quality, a governance framework, and LLM evaluation with reproducible metrics. We took those building blocks into production with SIMOSphere AI, in active dialogue with BaFin.

How is hands-on delivery different from PowerPoint advisory?

PowerPoint advisory ships concepts. Hands-on delivery ships systems in production: NICE Actimize modules SAM, WLF, CDD, KYC, STAR live; IRBA validation closed without findings; automated end-to-end data testing. SymBionTek operates inside your live data estate with your team and a specialist network.

Which languages and forums are covered?

Negotiations in German and English, at eye level with BaFin, EBA, US monitors and every major audit firm. Schranner-trained for the high-stakes moments.

Ready when you are.

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