How april engineers the synergy between tax and tech to offer e-filing solutions

Fintechs have leveraged the boom in embedded finance to offer a range of banking and payment solutions, but the tax industry has experienced relatively slow progress. This reluctance could be due to the tax industry’s complex ecosystem and web of regulations, where discrepancies between laws at multiple levels compel tax software providers to walk on eggshells.

Companies like Credit Karma and Intuit provide bundled tax services, but other fintechs are pursuing alternative strategies — such as partnerships or developing proprietary technology — to establish their presence.

Lili, for instance, has found success by merging banking, payments, invoicing, and tax management into a single app for SMBs. 

Another player in the wider market is april, a fintech startup that collaborates with banks, fintech firms, and payroll providers like Gusto to deliver them embedded tax solutions. april’s tools help users file, estimate, and optimize their taxes directly within the financial apps they already use. Instead of going the partnership route for tax tech, april decided to create its in-house infrastructure from the ground up.

We unpack the inner workings of how april built its platform and handles its infrastructure to offer e-filing capabilities in today’s market, the challenges involved, and whether the market today considers standalone embedded tax offerings viable.

Platform building: The alchemy of tax and technology

april, which debuted in 2021, centers its services around its AI-driven tax software.

Turning its vision of integrating tax and technology into reality required april to build and invest in a skilled team and a solid infrastructure.

Building the team

To develop the platform, april recruited engineers and teamed them with tax experts and a personalized tax coding virtual assistant.

Building a tax-targeted team has been key because tax is integral to april’s operations, giving it a wider scope of influence across the organization. “Everything that we want to do is going to be, at its core, tax-weighted,” said Christina Taylor, VP of Tax Development and Delivery at april.

To integrate tax expertise into all aspects of their operations, support, and development, Taylor draws on her nearly twenty years of experience in tax, accounting, and business operations to mentor her tax analyst team for improved outcomes. Her previous roles include leading teams at Credit Karma Tax and Cash App Taxes.

“I make sure that they have the direction and tools they need to do so and oversee processes to make sure we’re all aligned across tax analysts and engineering,” she said. “When I joined april a year back, I brought over top-notch analysts and veterans from the tax industry because I wanted to build a team with the skills needed to get april to national coverage.”

Building the in-house tech infrastructure

The US tax code presents a maze-like challenge, making it difficult to develop effective digital and mobile solutions. april’s strategy to address this challenge involves a two-pronged approach, addressing both technology and tax individually before combining them into a unified product. This hybrid model brings together tech and tax expertise, mixing digital advancements with human insights.

To align tax experts with engineers and stay current with evolving Federal and State tax policies, april relies on its proprietary AI system, Tax-to-Code. This system employs specially trained large language models (LLMs) to analyze tax documentation (Technical Product Requirements Documents) and generates code suggestions for defining data entries, logic, and relationships, for precise tax calculations. These suggestions are then reviewed by april’s Tax Engineers, who focus on refining the LLMs’ accuracy with each technical PRD they process.

However, it’s easier said than done. 

“One of the challenges of building a tax product is that the law is constantly changing and you have to be not just on top of, but ahead of the changes,” noted Taylor.

This means constantly fine-tuning algorithms to match precise requirements.

The race to beat the clock with coding: A tax product may involve millions of lines of code to achieve nationwide coverage. The federal tax code alone has grown to over 70,000 pages and more than 10 million words, with annual changes at both state and federal levels.

Taylor notes that creating a single tax filing product is akin to developing 43 separate products to handle both federal and state taxes. “I like to say all states are like their own sovereign entities when it comes to tax – they all have different ideas, techniques, tax laws, platforms, and technology,” she said.

The task of analyzing each state’s tax code is a massive endeavor in itself, and coding it into a functional e-file product adds another layer of complexity. The necessity for thorough testing and timely updates compounds the challenge. 

Although navigating the changing tax code is a complex task, this method provides april with a competitive edge over traditional players.

“The major difference between the way we build our tax products and the legacy incumbents is that our engineers are primarily building internal tooling, not the actual logic of our product,” Taylor added.

By sticking with this approach, april has achieved nearly 85% coverage of US tax scenarios within three years and has set up nationwide e-filing coverage for both state and federal taxes, according to Taylor.

The right dose of AI: AI is widely implemented in april’s backend operations, featuring systems like the Tax-to-Code generative AI process and aprilOS, which alleviates repetitive tasks.

“AI allows us to basically 10 times the rate at which we code tax law,” Taylor explained.

On the front end, too, an AI-backed chatbot uses a combination of AI models and input from april’s support team to provide users with algorithmically generated answers.

Even with its heavy reliance on AI, the company doesn’t place blind trust in the technology. The fintech recognizes the limitations of AI models and exercises caution by having all AI-generated outputs examined by its engineers.

“Tax is complex, sensitive, and highly regulated, so we don’t see a benefit to AI-washing here,” asserted Taylor. “We’ve taken a measured approach to how we’ve integrated AI into our processes.”

Bundled vs. standalone embedded tax products – the better approach today? 

Taylor notes that the tax industry has come a long way with the emergence of fintech, a far cry from 10-15 years ago when professionals like her had to labor to highlight the value of tax services.

Today clients have the option to offer the tax service free of charge, for a fee, or as part of a bundle, however, there is a growing trend toward bundling tax services among fintechs. 

Taylor views standalone embedded tax products as a promising opportunity, too. “That’s why I came over to april – that, and to use AI to do things better and smarter,” she added.

However, she argues that taxes shouldn’t be isolated as a single-service offering.

“Taxes shouldn’t be a standalone product – they’re interconnected to so many parts of our financial lives – income, investments, expenses,” she said. “I believe that having tax data operability will allow for more Americans to make more informed financial decisions and come tax time, file quicker than ever before.”

Tax data can also be a resource for fintechs to offer personalized products and services. When a consumer’s tax return is e-filed and accepted, the verified tax data can enable fintech apps to offer tailored services such as mortgage loans or auto financing rates to their users.

“We think that tax is that broader means to an end – a more intelligent financial technology ecosystem for consumers,” noted Taylor.