Data and AI Solutions for Banking and Financial Services

Yes. Every engagement starts by mapping the obligations that apply to the initiative, such as data residency, outsourcing and third-party risk rules, operational resilience requirements and model risk guidance. We then design access controls, encryption, logging and documentation to match. Our engineers can work inside your environments with your identity controls, so production customer data does not need to leave your infrastructure. We also provide the evidence your security, procurement and compliance teams typically request during onboarding.

We develop models with validation in mind from the first sprint. That means documented data sources and assumptions, reproducible training pipelines, benchmark comparisons against simpler models, stability and sensitivity testing, fairness analysis where relevant and reason codes for individual decisions. We produce a documentation pack structured around your model risk policy and set up post-deployment monitoring for drift and performance, so validators can review a complete, traceable package rather than reverse-engineering notebooks.

A first release usually focuses on one channel, such as card-not-present payments or instant transfers. We profile historical labeled data, engineer behavioral and network features, train and back-test models and integrate scoring with your payment flow or case management tool. A pilot running in shadow mode alongside existing rules can typically be ready in about three to four months, depending on data access and integration complexity. Shadow mode lets you compare results before switching decisions over.

Yes. The migration to ISO 20022 gives institutions structured, richer remittance and party information than legacy formats. We build parsers and data models that capture this structure, feed it into analytics and screening, and improve sanctions and fraud detection accuracy. We can also help reconcile legacy and ISO 20022 data during coexistence periods so reporting and analytics remain consistent while different payment systems migrate on different timelines.

We integrate with core, card, lending and payment platforms through their APIs, database replicas, event streams or file interfaces, depending on what the vendor and your architecture allow. We prefer change data capture or event streaming where possible to move from overnight batch to near real-time data. We do not replace your core system; instead we make its data accessible and trustworthy for analytics, AI and digital channels while respecting change-management controls.

You can engage us for a fixed-scope project, such as a reporting data mart or fraud model, a dedicated team that works as an extension of your data and engineering organization, or managed services where we operate pipelines and models in production. All models include weekly written progress updates and sprint demos. Many institutions start with a short discovery or proof of value and then scale to a dedicated team once the first use case is in production.