Regulatory reporting
Automated assembly of returns with reconciliation to the ledger and full lineage on every figure.
Discuss thisFinance practice
Data work that holds up under examination
Financial services teams do not have a reporting problem; they have an evidence problem. Every number needs a lineage, every model needs an explanation, and every access needs a log. We build to that from the start.
MWRKJT
Delivery leads online — talk to a human, not a botFullColumn-level lineage
ExplainableModel outputs
AuditedEvery access
Risk and margin viewReconciled to ledger
100% delivery success — delivered worldwide across seven regions
AWS
Microsoft Azure
Google Cloud
Databricks
Snowflake
dbt
Power BI
Looker Studio
Azure Synapse
MongoDB
Python
LangChain
AWS
Microsoft Azure
Google Cloud
Databricks
Snowflake
dbt
Power BI
Looker Studio
Azure Synapse
MongoDB
Python
LangChain
The constraint
Speed is easy. Defensible speed is the product.
Anyone can build a fast dashboard. In a regulated environment the question is whether you can show where the number came from, who could see it, and why the model made that call — eighteen months later, to someone hostile.
- Column-level lineage from source file to regulatory return
- Immutable audit of who accessed which rows, and when
- Model cards and explanation for every score that affects a customer
- Segregated environments with reproducible infrastructure
- Retention and residency enforced in the platform, not in policy documents
Control architectureLineage · access · audit
Where we work
Finance engagements we take on
Banking, insurance, lending, payments and capital markets — mid-market institutions and the fintechs serving them.
Fraud and AML
Detection models with explainability and a case management path, tuned against your false-positive tolerance rather than a vendor default.
Discuss thisCredit and risk analytics
Scorecards and portfolio analytics with model documentation that survives model risk review.
Discuss thisFinance operations
Close automation, cash forecasting and unit economics reconciled to source rather than assembled in spreadsheets.
Discuss thisCustomer 360
A permissioned single customer view across products, built with consent and retention rules enforced in the platform.
Discuss thisDocument automation
Onboarding, KYC packs and claims: extraction, validation and routing with a human on anything the system cannot evidence.
Discuss thisBy the numbers
How we work in financial services
Grounded in MOD's financial-services work — wealth-management analytics and a GCC trade-finance platform. We will walk through the method under NDA.
0%Delivery success rate across every engagement
0Financial-services builds: wealth analytics & trade finance
0%Of figures traceable to source, by design
0Client PII exposed — security and integrity built in
Delivery model
How the work actually runs
One delivery model, whatever the engagement. You always know what is shipping this week and what it is worth.
01
Discovery
We map your sources, decisions and blockers, understand the business goal, and agree what success looks like before anything is built.
02
Solution design
We design the architecture, data models and use cases — right-sized to your team and your cloud — and cost the work before you commit.
03
Development
Weekly sprints against a visible backlog: pipelines, models, dashboards and applications, all in version control and yours from day one.
04
Testing & validation
Every pipeline and model is tested — with frameworks like PyTest and Great Expectations — so the numbers are trustworthy before they ship.
05
Deployment & training
We deploy into your cloud and train the people who will run it, so the capability lands with your team, not just our code.
06
Support & optimisation
Observability, alerting and continuous improvement keep the system fast, accurate and cost-efficient long after go-live.
Proof
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FAQ
Questions buyers actually ask
Straight answers. If yours is not here, ask us on a call — we will tell you if we are the wrong fit.
Ask a questionYes, and in regulated work that is usually the requirement. We deploy into your cloud accounts under your identity provider, with our access scoped, time-boxed and logged.
Every model ships with documentation covering data, assumptions, performance by segment, known weaknesses and monitoring. We have taken that pack through review with clients and will adapt to your template.
Residency is a design constraint from the first architecture session. Where a jurisdiction rules out a managed model endpoint, we deploy open-weight models in-region instead.
Rarely, and never without telling you before you sign. The people on the kickoff call are the people on the delivery.
Next step
Bring us the return that takes three weeks to assemble
Thirty minutes with a delivery lead, not a salesperson. You leave with a point of view on your highest-value use case and what it takes to ship it.