CFO tech stack (2024)

1. Layering over legacy systems

   CFOs have to deal with a myriad of different systems to have visibility on their organisation’s finances. For example, there are different tools for tracking functions such as treasury management, procurement and cash collection. This means that finance teams are often forced to work in silos, creating a large amount of manual work in the process.

   Startups such as the Balderton-backed Payflows are building platforms deployed on top of companies’ existing accounting systems known as enterprise resource planning systems.

2. Procurement and treasury management

   Along with companies focusing on increasing visibility to all the systems used by finance teams, there are also a set of startups working on specific parts of the CFO tech stack. Pivot, a French startup set up by former product chiefs from Swile and Qonto, raised €20m at the tail end of last year to focus on procurement (business spend on goods and services).

   In February, Madrid-based Embat raised a $16m Series A led by Creandum to automate treasury management, the process of managing a company’s liquidity to identify and eliminate any operational risks.

3. Will finance teams embrace AI?

   One of the areas where AI continues to encroach upon fintech is the CFO tech stack vertical. According to a September survey conducted by consulting firm Gartner, 58% of finance functions in companies are currently using AI — a 21% increase year-on-year.

   Startups are also getting in on the game. Embat, for instance, uses Google Cloud’s generative AI to automate accounting and bank reconciliation. By doing this, the company says it’s able to automate more than 90% of accounting entries, saving up to 10 hours per week for finance teams in the process.

   Pigment has added AI features to its products — users can now ask natural language questions like “show me revenue for the past year” and get results. DataSnipper, meanwhile, this month bought a company called UpLink and will use its expertise to enable users to mine, analyse, and verify large volumes of documents in Excel.

Who early stage startups are up against