18-07-2025
Scaling Fintech Startups: Lessons From Hypergrowth Engineering
Madhuri Sesha Sarma is a VP of Engineering at Carta.
With over a decade working in the fintech ecosystem at companies like Visa, Clover, Fiserv, and now Carta, I've seen how fintechs face unique challenges when it comes to hypergrowth.
Few industries match fintech's growth, but rapid expansion in this sector often brings hurdles that hinder execution velocity and product quality. I recall at one company, for example, how we'd face outages every Friday due to peak dinner payment volume or the pressures of holiday seasonality.
Over the years, I've learned that scaling a fintech from 0 to 1 and then from 1 to N requires a focused platform engineering strategy. Let's explore some key factors for this strategy:
Build for modularity early.
A 0-to-1 product can work with a monolith, but a monolithic architecture can become a liability at scale. It can lead to all-or-nothing deployments, slow delivery, complicate debugging and often undermine reliability.
Building modularity early via microservices or well-defined domains within a monolith supports scalability. For fintechs processing high volumes of payments, isolating core payment logic into a highly available service ensures critical operations remain stable even if non-essential features experience issues.
For a deeper understanding of the challenges that companies face with monoliths while scaling, an excellent resource is an essay by Marco Palladino, co-founder and CTO of Kong, where he shared his challenges with monoliths and insights about his company's journey to modularity.
Prioritize execution velocity.
As usage scales, product development slows, bogged down by growing needs for quality assurance, incident response and compliance. Traditionally, this leads to heavy processes: manual regression testing, gated releases, and risk-averse cycles. While these methods help manage risk, they can strangle velocity over time.
Instead, teams should invest in automation and tooling that embeds quality and risk controls into development workflows. Examples include:
• LLM-powered integrated development environments (IDEs) like Cursor and Windsurf add tests to every pull request.
• Automated quality gates in CI/CD pipelines.
• Alert pruning, intelligent incident tracing.
• Canary deployments and automated rollbacks.
This approach helps to maintain speed while addressing complexity at scale.
Maintain a two-speed engineering model.
As a startup grows, chances are there is a critical legacy application that is moving at a much slower pace, as compared to newer products or applications that essentially need to move at a high velocity.
In this scenario, adopt a two-speed engineering model, where applications evolve and release at different rates aligned to risk tolerance, innovation needs and the desire for rapid feedback. Ensure quality assurance and deployment cycles are tailored to the specific needs of each stack.
Scale infrastructure with observability, not guesswork.
In fintech, reliability is non-negotiable given the financial impact of incidents. Yet, observability is often sidelined until after a critical incident forces urgent attention.
To avoid this reactive cycle, teams must treat observability as a core product requirement, not a bolt-on.
This requires a shift in mindset. At the outset, teams should define service-level indicators (SLIs) and error budgets that align with business priorities. Encouraging 'you build it, you own it' accountability ensures developers see value in adding telemetry early. Then, consider leveraging the LLM capabilities in observability tools such as Datadog Bits AI that integrate into CI/CD.
Investing in observability early pays long-term dividends, not only in uptime and user trust but in enabling confident, data-driven scaling as your fintech grows.
Treat compliance and security as first-class citizens.
Historically, prioritizing security and compliance almost always included a velocity tradeoff. A 2023 Palo Alto Networks report found that three-quarters of organizations publish new code to production weekly. Now, with the evolution of secure software development solutions in the market, the tradeoff is no longer relevant, and embedding security into software development should no longer be an afterthought.
Tools such as Veracode, Snyk, Wiz and others can detect and alert users about security vulnerabilities. AI-era security tools now offer AI copilots that can integrate with IDEs to automatically scan code for vulnerabilities and recommend remediation before the change gets committed into the source repository.
Design for data security and portability.
A 2025 Alloy report involving over 500 banks, credit unions and fintechs found that 60% of financial institutions reported an increase in fraud, and nearly a third incurred over $1 million in direct fraud losses. A data breach can be severely consequential to both the consumer and the fintech, especially when you consider that fintechs often deal with some of the most sensitive consumer data.
Data security investments such as investing in data encryption, data security posture management tools and ensuring access to data is granular, audited and only on an as-needed basis can protect the sensitive customer data from internal and external threats.
Additionally, as the data read and write load increases, strategies such as sharding can ensure the data source is reliable and can cater to increased usage.
Avoid the platform trap.
While a robust platform strategy is essential for long-term scalability, fintechs in hypergrowth must resist the temptation to over-engineer too early.
Premature investment in shared services can lead to wasted effort and unused systems. Instead, build for scale as needs emerge, when multiple teams experience repeatable friction or request common solutions. Ensure there's a clear pull before investing in platform features.
Overbuilding too soon slows agility and adds debt. Successful platforms are born from demand and prioritize validated needs over hypothetical scale.
Closing Thoughts
Investing in foundational architecture and organizational strategies early can help ensure that fintech startups can scale well beyond early success.
With these strategies in place, growth-stage fintechs can leverage their resources and expertise to build the next phase of high-scale products.
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