When Fundipedia applied to join the IA Engine Innovator Programme in 2020, our software was flying under the radar. We were solving a real problem in asset management and had a few clients but I was still figuring out how to explain our solution clearly.

It’s fair to say that many early stage firms find themselves in a position of less than 100% clarity – and that’s okay. This is part of the journey.

Now as the chair of the IA Engine I’ve read dozens of fintech applications to the cohort, and there are common mistakes made that are easily avoided – even if your message is not 100% refined to your liking.

This post sets out key mistakes to avoid so you can avoid them when you apply.

1. It’s all about the problem, and really not about the technology.

Don’t talk about your product, your stack or AI. Start with the problem you’re solving.

In our case, asset managers were wasting time and money ineffectively managing their growing pool of fund data across spreadsheets and silos. Fundipedia created one accurate and trustworthy source of funds and associated data so they could improve accuracy, governance and downstream dissemination.

You should refine your message until you can describe what your solution does in a single statement.  In other words, could you explain what your solution does to your parents or people outside of the industry?

Many applications are full of jargon. Keep yours clean and simple.

Focus on what you actually deliver and how it links back to the core problem statement you solve:

For us, this included tangible features and benefits such as

• Customisable data model and workflows to store and process any data
• A customisable rules engine for data validation – with 1000+ rules out of the box
• Full audit trail for all data changes
• One-click reporting for a range of downstream dissemination points, also out of the boxThese are short and clear benefits that tie back to the problem statement.

3. Don’t overstate AI

It is of course sensible to mention that you use AI, but the technology isn’t the story. The problem you’re fixing is.

The reality is that buyers care about outcomes, not algorithms. If you can’t explain the practical impact without saying “AI”, you haven’t nailed your pitch yet.

4. Quantify the impact

Everyone says they “create efficiencies”. Show it.

We shared numbers that proved our value:

• 14 days of manual effort saved each month across impacted teams
• Faster product launches because distributors got data in real time
• Improved data accuracy on platforms like Morningstar and FE FundInfoNumbers get attention. They make your benefits tangible.

5. Show that you understand the industry

The IA Engine wants FinTechs that understand how the asset management industry works.

We called out the job titles we wanted to speak to and referenced the clients we’d already worked with such as Barclays and M&G. This evidenced that we knew our target market and where we fit within it.

This was key – our application didn’t just focus on what we wanted to gain. We also talked about what we wanted to give back.

We said we wanted to help shape an industry data standard and share knowledge through our user community. That mindset matters. IA Engine is a community, not a sales channel.

I do wish all of the FinTechs applying the best of luck.  Please drop me a line on LinkedIn should you have any specific questions: https://www.linkedin.com/in/simonswords/