10+ years
with a top-tier investment bank
Engineering for investment banks
Built for complexity, speed and regulation. We help investment banks integrate complex ecosystems, modernize legacy architectures, and build AI-ready development environments by combining deep technical experience with fintech innovation.
Proven in banking. Shaped by fintech.
What sets us apart is our ability to operate at the intersection of large-scale banking systems and fintech innovation. With over a decade of experience working with a top-tier investment bank and multiple fintech platforms, we understand both sides of the ecosystem.
15+ projects
delivered for fintech innovators (trading, BNPL, wealth)
Niche expertise
in Java, Scala, Apache Kafka, and more
AI-ready
SDLC platform and tooling
The challenges shaping modern investment banking
Legacy architectures slowing down delivery
Many established banks still rely on monolithic "legacy" systems built decades ago. These architectures are often rigid, documented poorly, and interconnected in a "spaghetti" of dependencies. Because these systems weren't designed for the cloud or modular updates, deploying a simple feature can take months of regression testing. This technical debt creates a massive bottleneck, preventing banks from responding quickly to market shifts or client demands.
Growing ecosystem of fintech integrations
The rise of specialized fintechs has forced banks to shift from being closed shops to becoming "platform" players. While integrating with third-party tools for niche services (like specialized risk analytics or digital asset custody) offers a competitive edge, it creates a massive orchestration headache. Banks must now manage a complex web of APIs and external partnerships, ensuring that these third-party integrations don't compromise the bank's core security or operational stability.
Increasing pressure for real-time systems
The days of "T+2" settlement or end-of-day batch processing are rapidly fading. Modern clients and traders expect real-time visibility into liquidity, margins, and risk exposure. Transitioning to event-driven architectures that can process millions of transactions per second with microsecond latency is a monumental task. This shift requires a total overhaul of data pipelines to ensure that information is not just stored, but streamed and acted upon the moment it is generated.
Rising regulatory complexity (AI, data, compliance)
Regulators are moving faster than ever, specifically targeting how banks handle data and AI. From the EU AI Act to evolving Basel standards and strict data residency laws, compliance is no longer a "check-the-box" exercise; it's a massive data engineering challenge. Banks must now prove the explainability of their AI models and ensure "lineage" (knowing exactly where every piece of data came from), all while maintaining ironclad cybersecurity in a world of increasing sovereign data requirements.
We focus where it matters most
Modern architectures
- Migrating from legacy batch processing to low-latency, event-driven architectures.
- Mastering event streaming to handle millions of transactions.
- Modernizing system architecture while improving engineering standards and developer productivity.
- Redesigning monolithic structures into modular, high-throughput systems ready for global scale.
Integrations & Connectivity
- Designing scalable API platforms and robust partner connectivity for Open Banking.
- Managing third-party fintech ecosystems, including seamless integration of payments and KYC/AML providers.
- Resolving the "spaghetti" of external dependencies to ensure stable, secure data flow.
- Bridging the gap between established bank cores and the modern fintech landscape.
AI-Ready Software Development
- Implementing AI-supported development through specialized tools like VISDOM to ensure auditability.
- Leveraging TraceVault for immutable data lineage, meeting strict regulatory requirements.
- Boosting internal team output through Basel monorepo management and automated developer productivity loops.
- Applying rigorous technical standards to ensure AI models and data pipelines are production-grade and compliant.
Learn more how we enhance modern financial platforms:
Read more >How we work
We operate at the intersection of banking and fintech, strengthening internal teams with specialized engineering expertise.
Work alongside internal engineering teams
Focus on high-complexity, high-impact areas
Bring niche expertise and engineering excellence where it matters most
Deliver fast without compromising compliance
Recommend critical improvements
Take full ownership – we treat your product as ours
Why VirtusLab
Inside financial systems experience
10+ years working with a top-tier investment bank
Fintech ecosystem exposure
Trading, WealthTech, BNPL, and payments
Niche engineering expertise
Java, Scala, Kafka, real-time systems, AI-ready SDLC
Built for regulated environments
Compliance, traceability, and auditability by design
See how we help top-tier global investment bank
1
Migrated the client’s system to Azure and replaced semi-manual deployment scripts with a fully automated, parallelized deployment pipeline
2
Implemented auto-scaling and temporary cloud resources
3
Built an end-to-end automated testing framework integrated with the private cloud
Moving top-tier investment bank infrastructure to the next level with cloud deployment
1
Developed and deployed a managed IntelliJ IDEA tool that automated workspace setup
2
Optimized IDE and build performance by introducing partial monorepo imports, cached commits, and streamlined code verification processes
3
Doubled monthly merged pull requests and cut setup time by 90%
Reducing pull request merging times by 43% with a managed IDE tool
1
Optimized IntelliJ's native indexing performance
2
Developed an automated system to pre-build and distribute shared indexes
3
Integrated index generation directly into the CI pipeline to ensure seamless, hands-free index updates
