KYC document intelligence
Extract structured data from passports, incorporation documents, and proof-of-address files, cross-check against sanctions and PEP lists, and flag exceptions for human review instead of routing every file to an analyst.
Industries
AI systems for banking operations
We build production AI for retail and commercial banks: document intelligence, alert triage, and reporting automation that sits inside your existing core-banking and case-management systems, not a replacement for them.
Where this fits
Banks run on manual review: analysts reading loan files, compliance teams triaging alerts, operations staff reconciling reports against regulatory templates. Volume keeps growing, with more accounts, more transactions, and more jurisdictions, while headcount budgets stay flat. The result is a backlog that shows up as slower onboarding, alert queues nobody fully clears, and reporting cycles that eat the last week of every month.
We build AI systems that sit inside that workflow rather than replacing it: document intelligence that pulls structured data out of loan files and KYC packets, alert triage models that rank AML cases by actual risk instead of static rules, and reporting pipelines that assemble regulatory submissions from source data with a full audit trail. Every system runs on your infrastructure, whether on-premises or in your VPC, with logging that satisfies DORA operational-resilience requirements and BaFin/MaRisk model-governance expectations. We integrate with the core-banking, loan-origination, and case-management platforms you already run; nothing here asks you to rip out existing systems.
Named solutions
What we build for Banking
02
AML alert triage
Rank AML alerts by evidenced risk using transaction context and entity history, cutting the volume analysts work by routing low-risk alerts to fast-track disposition with a documented rationale attached.
03
Credit memo drafting
Draft first-pass credit memos from financial statements, covenant data, and prior exposure history, giving underwriters a structured starting point instead of a blank template.
04
Regulatory reporting automation
Assemble COREP/FINREP-style regulatory submissions directly from source ledgers and risk systems, with lineage tracked back to the originating record for audit.
05
Loan origination copilots
Support loan officers with automated document checklists, missing-item detection, and consistency checks across the application package before it reaches underwriting.
06
Treasury cash-flow forecasting
Build forecasting models on transaction and account data to give treasury teams a rolling liquidity view, refreshed daily rather than reconstructed manually each week.
07
Core-banking data integration
Connect core-banking, general ledger, and case-management systems into a single data layer, so AI systems and your own analysts work from one consistent source of truth.
08
Fraud pattern detection
Detect anomalous account and transaction patterns using models trained on your own historical fraud cases, tuned to minimise the false positives that burn analyst time.
09
Contact-centre deflection
Handle routine account and product questions through a policy-grounded assistant, escalating anything outside its confidence threshold to a human agent with full context attached.
How we work
Our delivery process
- 01
Discovery & data audit
We map your existing systems, data sources, and compliance obligations before writing any code, so the build plan reflects what you actually run.
- 02
Compliance-aware integration
We connect to core-banking, KYC, and case-management systems under your data-residency and access controls, with every extraction logged.
- 03
Model build & validation
We build and validate models against your historical data, with documented performance against a held-out set your risk team can review.
- 04
Regulated deployment
Systems ship on your infrastructure, on-prem or VPC, with the logging and explainability BaFin/MaRisk and DORA review expects.
- 05
Monitoring & retraining
We monitor live performance and drift, retraining on a defined schedule so accuracy holds as your book of business changes.
Compliance
Built for the banking compliance stack
Every system we deploy for banks is designed around EU AI Act obligations for high-risk financial use cases, DORA’s operational-resilience and third-party-risk requirements, BaFin/MaRisk model-governance expectations for German institutions, and GDPR data-handling rules. That means documented model risk assessments, audit trails on every automated decision, human-in-the-loop review for anything classified as high-risk, and deployment on infrastructure you control. We do not ship a model without the paperwork a supervisory review will ask for.
Frequently asked questions
Can this run on-premises, or does it require sending data to a third-party API?
Both are options. Most banking clients run on-prem or in their own VPC using open-weight or licensed models specifically to avoid sending KYC and transaction data to an external API. We size the model to what your infrastructure can serve.
How do you handle model risk governance for BaFin/MaRisk?
We document model design, training data, validation results, and known limitations in the format your model risk function already uses, and we build in the human-review checkpoints MaRisk expects for automated decisions above a risk threshold.
Does this replace our compliance analysts?
No. It triages and drafts; a human still disposes of AML alerts and approves credit memos. The goal is fewer low-value reviews per analyst, not fewer analysts making the final call.
How long does a first deployment take?
A scoped first system, such as KYC document intelligence or AML alert triage, typically reaches a production pilot in 8-12 weeks, including the compliance documentation.
What happens to accuracy as regulations or products change?
We set a retraining and revalidation schedule up front, and the monitoring system flags drift so retraining happens before accuracy degrades in production, not after.
Related services
Pair this with
Talk to us about Banking
A 30-minute call to scope what a first system would look like against your own data and systems.
Book a 30-min intro call