In financial services, risk management drives enterprise-level decision-making. When handled effectively, risk management not only prevents financial losses and ensures regulatory compliance but also unlocks growth opportunities. Today, with the emergence of advanced AI technologies and the proliferation of data, the stakes for getting the business approach to risk right are higher than ever. 

At my firm, Altari Ventures, I invest in enterprise fintech startups that are addressing the most pressing challenges in financial services. Risk management serves as my lens for evaluating opportunities because it cuts through competing business priorities and drives urgency in client adoption. 

This framework guided a panel I moderated at the Family Wealth Report Investment Summit, “Risk: The Common Language of Opportunity in Enterprise Fintech.”

For startup investors evaluating an early-stage venture, a critical question is: is the company solving a real problem? My approach delves deeper: What risk is the company mitigating, and what are the repercussions for the client organization of not addressing it? Risk management is a priority in all enterprises, but it is especially significant in financial services, where regulatory scrutiny creates long-lasting consequences for even unintended mistakes. 

Startups that connect their solutions to key risk concerns can materially accelerate sales into their target customers.

Risk comes in many flavors and represents an incredibly rich investment frontier. During the panel, we heard perspectives from founders working in different parts of the risk landscape, showcasing the breadth of the enterprise fintech opportunity. 

Alex at Tradewell focuses on ensuring best execution for institutional corporate bond investors across the rising number of electronic trading venues; Daniel at Auditive is building a two-sided risk management platform for enterprises and their third-party vendors; and Vanessa at Sugarwork is quantifying tacit corporate knowledge and enabling her clients to manage knowledge as an asset. Here are a few takeaways from the discussion and insights into how my portfolio companies are leveraging risk to create value.

Domain expertise is critical to product design and successful sales
Selling into financial services has become more challenging as the selection of software tools exploded and as innovation management shifted from centralized teams to individual business units. To succeed, startups need to clearly demonstrate the need for their solution and incentivize behavior change. 

This isn’t easy, when you’re talking about thousands of enterprise employees and a deeply ingrained self-preservation culture. Being able to show the detrimental impact of not adopting emerging technology – be it financial costs or being left behind by the rest of the market – is a powerful driver of change. Risk management, as a concern that resonates across all organizational levels, is an effective way to connect inaction to business consequences.

Domain expertise is critical to a productive risk management conversation. All three panelists had relevant experience that informed their product design and selling approach. Daniel spent time on Wall Street, in both trading and technology, and has lived the vendor risk management problem at a tech company; risk is a core notion he brought into Auditive’s third-party risk assessment because he saw that the inefficiencies in that process are risks, not just costs.

Vanessa started her career as a consultant at McKinsey where a big part of her work was organizing and templating clients’ corporate knowledge; this was directly relevant to Sugarwork’s knowledge data and AI value. Alex has a Wall Street trading background that informed the way Tradewell’s product and user experience are organized. Domain expertise gives these founders credibility in client conversations and enables them to deliver products that not only mitigate prevalent risks but also offer actionable insight into business upside.

Data is a product moat for technology startups as well as their clients The massive explosion of data is currently reshaping every industry, financial services included, creating both opportunities and challenges. Whether the organization is using technology to capture existing data more accurately, collect new data, or generating previously unavailable or proprietary data, it stands to benefit from more granular risk management and a unique moat that can offer a competitive advantage. 

Software startups that process enterprise clients’ data also strengthen their product moats: while each individual customer's data remains confidential, the startups observe anonymized market trends and usage patterns which enable them to deliver better, more relevant products in the future. 

For instance, Tradewell has visibility and insights into the broader corporate bond market flows and pricing; Auditive captures vendor and enterprise third-party risk management best practices across industries; Sugarwork sees the most effective ways to capture and transfer knowledge by market vertical and in aggregate.

Building the data moat can not only separate market leaders from followers but also help them build resilience against competitors.

However, as data proliferates, so does risk. While organizations face pressure to leverage their real-time data, they also need to safeguard privacy and security. 

Mismanagement can contribute to reputational damage, operational inefficiencies, and financial losses. The data explosion also means that risk management processes are never static. They need to be evaluated and upgraded continuously. The ability to transform data into a unique competitive advantage while keeping up with risk mitigation is essential for businesses that want to thrive – and a huge opportunity for the startups who can help them.

AI has a clear value proposition
AI’s value lies in its ability to deliver intelligent and actionable insights that would be nearly impossible to achieve through traditional methods. By enabling more immediate, precise identification of risks and real-time solutions, AI can empower organizations to stay ahead in an increasingly complex environment. 

This is particularly crucial in high-stakes scenarios where swift, informed decision-making with the help of the right tech tools is the difference between mitigating a risk or exacerbating it. Startups that win enterprise business tend to leverage best-in-class technology, most often AI, and are highly proficient in the language of risk. When selling to prospective customers, they lead with domain expertise and problem-solving rather than the cutting-edge quality of their technology alone.

What’s ahead
The role risk management plays in driving enterprise decision-making will only become more critical, as better data and AI enable faster risk detection and resolution while necessitating a dynamic approach to the tech stack supporting this process. Startups rising to address key risks are poised to create significant economic value and disproportionate investment upside, especially in the already massive financial services sector. As an early-stage venture investor, I’m excited to continue partnering with founders like Alex, Vanessa and Daniel who are building next generation tools and platforms in the multi-faceted enterprise fintech universe.