AI in Finance: Three Questions Investors need to answer now
AI has become a dominant theme in fintech, with most companies claiming to use it. For investors, the key question is whether it creates measurable value.
Artificial intelligence has become one of the dominant themes in financial technology. Nearly every fintech company now claims to integrate AI into its product, operations, or infrastructure. For investors, however, the question is no longer whether AI is used. The real question is: Does AI create measurable value in financial services, or is it simply part of the story?
Three structural questions increasingly define the real investment case for AI in finance.
1. Will AI adoption in finance catch up on AI Investments?
AI investment in fintech is growing rapidly, but adoption in financial organisations often moves much more slowly. Financial institutions operate in environments where trust, accountability, and regulatory compliance are critical. Even when AI solutions are technically capable, companies must ensure that automated decisions are transparent and controllable.
As a result, many finance teams still ask fundamental questions:
- Can AI systems be trusted in sensitive financial workflows?
- Who is responsible when automated decisions fail?
- How transparent must AI decision-making be?
This creates a growing gap between investor enthusiasm for AI and real-world adoption inside financial institutions. For investors, the key challenge is identifying companies that solve real adoption barriers, not just technical problems.
2. Does AI improve venture capital decisions or reinforce bias?
AI is increasingly used in venture capital to screen startup decks, analyse markets, and support investment decisions. The promise is clear: AI can process large datasets faster than any individual investor. However, faster analysis does not automatically lead to better decisions.
Venture capital has historically relied on pattern recognition, identifying founders and companies that resemble previous success stories. But this process can easily turn into confirmation bias, where investors favour information that supports existing assumptions.
AI introduces a new complication. Because AI models are trained on historical data, they may replicate the same patterns that shaped past funding decisions. Instead of eliminating bias, AI can unintentionally reinforce it at scale. For investors, the opportunity is not to delegate decisions to AI, but to use AI tools to challenge assumptions and surface overlooked signals.
3. Can AI help fintechs scale faster while staying compliant?
As fintech companies grow, they often face tension between rapid customer acquisition and regulatory precision. Scaling financial products requires strict identity verification, anti-money-laundering checks, and fraud detection systems. When compliance infrastructure cannot keep pace with growth, companies quickly face operational and regulatory risk. AI is increasingly used to close this gap.
Machine learning systems can analyse transaction behaviour, identify suspicious activity, and support compliance teams in monitoring financial crime risks. In this context, AI is becoming part of the core infrastructure that allows fintech companies to scale safely. For investors, this represents an important shift: long-term success will depend not only on growth but also on regulatory resilience.
Conclusion: What investors should evaluate in AI-driven fintech companies
As AI becomes standard across financial technology, investors need new criteria for evaluating companies. Three questions are becoming central:
1. Will users actually adopt AI-driven financial tools?
2. Does AI improve decision quality or simply accelerate existing biases?
3. Can companies scale while maintaining regulatory robustness?
These questions are already shaping conversations across the fintech ecosystem. At FIBE Berlin, investors, founders, and financial leaders will explore exactly these challenges: from AI adoption in financial institutions to the role of data-driven decision-making in venture capital and the growing importance of compliance infrastructure.
In discussions featuring voices such as Jessica Holzbach (0TO9), Romain Grimal (BlackFin Capital Partners) and other industry leaders, attendees will gain deeper insights into how AI is reshaping investment decisions, financial products, and regulatory frameworks. FIBE offers the opportunity not only to hear these perspectives but to actively engage in the debates defining the next phase of fintech innovation.