Can Code Generation Save Fintech Startups Time?

The pressure was mounting. Sarah, lead developer at a small Atlanta-based fintech startup, FinTech Frontier, stared at the lines of code sprawling across her screen. Their flagship app, poised to disrupt the local lending market, was riddled with bugs and deadlines were looming. Could code generation technology be the lifeline they desperately needed, or just another overhyped promise?

FinTech Frontier was burning through venture capital at an alarming rate. Every bug fix seemed to introduce two more. Sarah’s team, while talented, was stretched thin. They were spending more time debugging boilerplate code than building innovative features. I remember having a similar problem at my last company. We were constantly firefighting, and innovation took a back seat to simply keeping the lights on.

The problem wasn’t a lack of skill, but a lack of time. Manually writing every line of code for repetitive tasks – data validation, API integrations, UI components – was sucking the life out of the project. Sarah knew they needed a radical solution.

That’s when she started exploring code generation. The promise was enticing: automatically create code from models, templates, or specifications, freeing up developers to focus on higher-level logic and problem-solving. But could it actually deliver?

Early attempts were frustrating. The generated code was often clunky, inefficient, and difficult to integrate with their existing codebase. “It felt like we were trading one set of problems for another,” Sarah confessed during a late-night call. The initial tools they tried produced code that required almost as much debugging as writing it from scratch. Some of the generated code even introduced new security vulnerabilities, a major concern for a fintech company handling sensitive financial data.

A report by OWASP highlights that insecure coding practices are a leading cause of application vulnerabilities. So, any code generation tool needed to prioritize security.

Then, Sarah discovered Appian, a low-code platform that offered a more sophisticated approach. Instead of generating raw code, Appian allowed them to visually model their application logic and data flows. The platform then automatically generated the underlying code, handling many of the tedious and error-prone tasks. This was a significant improvement over their previous experiences.

The shift wasn’t immediate. The team had to learn the Appian platform and adapt their development processes. There was resistance at first. Some developers worried that code generation would make their skills obsolete. But Sarah emphasized that the goal wasn’t to replace developers, but to empower them. “We’re not becoming button-pushers,” she explained. “We’re becoming architects.”

The results were striking. FinTech Frontier was able to build and deploy new features in a fraction of the time. The development team could now focus on the unique aspects of their application, such as the complex algorithms for credit risk assessment. Boilerplate code, previously a major time sink, was handled automatically. According to Gartner, the low-code development technologies market is projected to reach nearly $29 billion in 2024, and that growth is only expected to continue.

Within three months, FinTech Frontier launched a new version of their app with several key features that would have taken six months to build using traditional methods. The time savings translated directly to cost savings, extending their runway and giving them more time to acquire customers. They even managed to integrate with the Georgia Department of Revenue’s online portal for automated tax reporting, a feature that gave them a significant competitive advantage.

The platform also improved the quality of their code. By using pre-built components and adhering to Appian’s best practices, they reduced the number of bugs and improved the overall stability of their application. The platform’s built-in security features also helped them to mitigate potential vulnerabilities. We’ve seen this pattern repeatedly – focusing on the core business logic and letting the platform handle the rest often leads to better, more secure code.

However, code generation isn’t a silver bullet. It’s crucial to choose the right tool for the job. Some tools are better suited for specific types of applications or programming languages. It’s also important to understand the limitations of the tool and to be prepared to write some code manually when necessary.

For example, FinTech Frontier still had to write custom code for certain complex financial calculations. Appian handled the basic data entry and workflow, but the core algorithms required the expertise of their senior developers. The key was to find the right balance between automated code generation and manual coding.
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Another challenge was maintaining the generated code. When the platform updated its code generation templates, Sarah’s team had to carefully review the changes to ensure that they didn’t introduce any new bugs or break existing functionality. Version control and thorough testing were essential.

We had a client last year who tried to implement a code generation tool without proper version control. The result was a disaster. They ended up with multiple versions of the same code, and it was impossible to track changes or identify the source of bugs. Here’s what nobody tells you: code generation doesn’t eliminate the need for good software engineering practices; it amplifies them.

Sarah’s team also learned the importance of continuous integration and continuous delivery (CI/CD). By automating the build, test, and deployment process, they were able to quickly identify and fix any issues that arose from the generated code. They used CircleCI to automate their CI/CD pipeline, ensuring that every code change was thoroughly tested before being deployed to production. Thinking about automating more? Customer service automation could be a cure for burnout.

The success of FinTech Frontier demonstrates the transformative potential of code generation technology. By automating repetitive tasks and freeing up developers to focus on higher-level logic, code generation can significantly accelerate the development process and improve the quality of code. A McKinsey report notes that low-code/no-code platforms are empowering “citizen developers” to build applications without extensive programming knowledge, further expanding the reach of code generation.

FinTech Frontier is now a thriving business, offering innovative lending solutions to underserved communities in Atlanta. They recently secured a second round of funding and are expanding their operations to other states. And it all started with a willingness to embrace new technologies and a commitment to continuous improvement.

What did Sarah and FinTech Frontier teach us? That code generation, when implemented strategically, can be a powerful tool for transforming the software development industry. The key is to choose the right tool, adapt your development processes, and never stop learning. To help, here’s tech help for small business.

Stop writing boilerplate. Start building. That’s the lesson FinTech Frontier learned, and it’s a lesson every software development team should take to heart. Explore code generation options that fit your needs and start thinking strategically about how to free up your team’s time for innovation, not repetition.