Financial institutions looking for artificial intelligence applications beyond employee productivity tools may have a new option. Financial intelligence startup geniosAI has emerged from stealth with $19.1 million in combined seed and Series A funding, according to an announcement Monday (Nov. 9), betting that banks and investment firms will pay for AI that not only produces answers but also shows how it reached them.
The funding comes from FactSet, Zoom and General Catalyst, with FactSet leading the Series A and serving as geniosAI’s strategic partner. The company is developing AI products for corporate finance teams, investment professionals and the office of the CFO.
Its central proposition is that financial institutions need a way to preserve the assumptions, calculations and review decisions behind their analyses so employees can verify results, challenge conclusions and build on previous work.
Through its partnership with FactSet, geniosAI will bring FactSet’s financial data into its platform. Zoom, meanwhile, will support the conversations where financial decisions take place, including internal finance reviews and earnings calls.
The company said its technology is already being used by finance and investment teams at Fortune 500 banks and technology companies to prepare for earnings, compare results with analyst expectations and identify questions investors may raise.
“The value of data is defined by how decisively you can act on it,” FactSet CEO Sanoke Viswanathan said. He added that combining FactSet’s data with geniosAI’s traceable analysis could help financial teams make decisions with greater confidence and speed.
The timing reflects a broader shift in enterprise finance. As companies add more technology to their operations, the challenge is how to connect systems, preserve controls and decide which capabilities they actually need to own. For CFOs, the cost of a modern finance stack is often less about individual software licenses than the work required to keep applications, data and processes connected.
AI adoption is growing, particularly in financial services back offices. A PYMNTS Intelligence study found that at least half of surveyed financial services firms were using AI in 27 of 75 business tasks examined. Revenue recognition led adoption at 65%, followed by credit risk assessment and sales forecasting at 60% each. Yet fragmented or poor-quality data remained the biggest obstacle to wider deployment for 30% of financial services leaders.
Banks are also finding ways to introduce AI without replacing the technology they already have. Sutherland and FlowX.AI, for example, are putting more than 220 AI agents to work on top of existing banking systems, targeting processes such as lending, onboarding and anti-money laundering reviews. One European lender reportedly reduced manual credit-workflow handoffs by 80%.
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