Banking and financial services

Financial services technology is shaped by three forces at once. Customer expectations set by consumer fintech, the operating cost of running on core systems that were never designed for real time anything, and a regulatory environment that treats a software defect as a potential compliance finding. Programmes that succeed here account for all three from the outset rather than optimizing for one at the expense of the others.

We work across retail and commercial banking, mortgage and lending, and capital markets operations, on both the customer facing layer, such as digital banking, loan origination and trading tools, and the infrastructure behind it, including core banking connectivity, payments rails, data architecture and the compliance systems that monitor all of it.

A recurring theme across these engagements is consolidation. Banks and lenders that have grown by acquisition are often running three or four versions of the same system, and a meaningful share of our work is bringing that down to one without disrupting a business that cannot afford downtime.

Where we help

• Digital banking transformation, including online and mobile banking platforms and customer onboarding
• Core and platform consolidation, merging systems inherited through growth or acquisition into a single supportable stack
• KYC and AML automation, alerting and remediation, including workflow for suspicious activity reporting
• Mortgage and lending platform modernization, from origination through servicing
• Secure payment systems, including card, ACH and real time payment rail integration
• Trading and investment platform engineering, including market data handling and order management workflows
• Data architecture and reporting for regulatory submissions, risk management and internal audit
• Customer and agent facing portal design, development and deployment

The regulatory and compliance landscape

Depending on the client and the engagement, our work touches Bank Secrecy Act and USA PATRIOT Act obligations around KYC and AML, Regulation E and Regulation Z for consumer protection, GLBA driven data safeguarding requirements, and Dodd Frank reporting obligations for institutions above the applicable thresholds. We scope which of these actually apply at the start of an engagement rather than assuming a single answer fits everyone.

For institutions handling card payment data, we design and staff to PCI DSS requirements as a baseline architectural constraint, particularly around cardholder data environment scoping and tokenization, since retrofitting PCI compliance into a system not designed for it is one of the more expensive mistakes we see clients trying to unwind.

Audit readiness runs through everything. Change logs, access controls and a defensible record of who approved what and when, because in this sector the ability to show your work during an exam is nearly as important as the system working correctly in the first place.

Where AI and automation are changing the work

Fraud detection and transaction monitoring were early, legitimate use cases for machine learning in this sector, and that work has matured into a genuine engineering discipline. Model risk management, explainability requirements for adverse decisions, and ongoing model performance monitoring rather than a model shipped once and left alone.

Generative AI is now showing up in more customer facing places, including chat based support, document summarization for loan underwriting, and first pass KYC document review, but every engagement we run in this space keeps a human decision maker in the loop for anything that affects a customer credit access or account status, both because it is the right engineering choice and because regulators are actively watching this space.

On the operations side, AI assisted reconciliation and exception handling is quietly one of the highest value applications we see. Unglamorous, high volume, and well suited to a model that flags exceptions for a human rather than one that acts on its own.

Platforms and technology

We work across the core banking, payments and data platforms that make up a typical financial services technology stack.

• FIS, Fiserv and Jack Henry core platforms
• Temenos
• Salesforce Financial Services Cloud
• AWS and Azure with financial sector controls
• Plaid and open banking APIs
• Snowflake and enterprise data platforms
• ServiceNow

Where ServiceNow is part of the stack, our engineers handle ITOM and SecOps workflows on regulated infrastructure and ITSM configurations that keep incident and change history audit-ready. In financial services that is a design constraint from the start, not something added at the end. ServiceNow practice →

How we approach engagements in this space

We run a calibration session with engineering and compliance stakeholders together at the start of every engagement, so the requirement reflects the actual regulatory obligation driving it rather than a generic feature request written before anyone checked with the audit team.

When additional engineering capacity is needed, we prioritize people with prior exposure to the relevant domain, such as mortgage servicing, capital markets or core banking, before assessing general technical depth. In a regulated environment, the ramp up cost of a technically strong candidate with no domain context is usually the longer of the two problems to solve.

For delivery engagements, we favor consolidation and integration over a full rebuild wherever the existing system is fundamentally sound, because a complete core replacement is rarely the fastest or safest route to the outcome a client actually asked for.