Bain Capital Ventures’ Kevin Zhang: The ‘Unlockable Potential’ in Lending, Investing, and Insurance
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ABSTRACT
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The ‘opportunity engine’ businesses of lending, investing, and insurance have always had to apply the latest technology to accurately quantify risk, understand human behavior, assess geopolitical and financial data, and achieve state-of-the-art marketing and operational excellence. Kevin Zhang, Partner at Bain Capital Ventures, assesses technological tailwinds for emerging players in this category, as well as areas for innovation that extend beyond vertical tech for financial services.
KEY POINTS FROM KEVIN ZHANG'S POV
Why are opportunity engine businesses such an important category moving forward?
Numerous big picture changes, including embedded financial services and blockchain tech, are affecting the nature of new opportunities in the lending, investment, and insurance industries. “Financial services origination is moving into the software layer, becoming embedded naturally into the tools you already use—and which already have access to your latest financial data,” says Zhang. “Technologists are examining how blockchain technology can bring us back to a more decentralized, and perhaps more efficient model of mutual insurance and lending.”
Market players in these spaces must continually improve productivity to stay competitive, creating industry-wide demand for innovative software providers. “Many lenders, investment platforms, and insurers are simply scale B2C and B2B businesses that need to stay on the cutting edge in order to compete,” he says. These companies maintain strong demand for enterprise and productivity software. “For example, our portfolio company Magical, a tool for repetitive text expansion and autofill, is used by many loan processors.”
Generative AI is increasingly being piloted and put into production across these opportunity engine industries. “Financial services companies are aggressively exploring applications of generative intelligence across various aspects of their business, from compliance to client service and financial analysis work,” says Zhang. “In insurance and lending, AI tools are helping underwriters to more efficiently collect and evaluate data.”
The higher interest rate environment presents both challenges and opportunities in the financial services sector. “Non-zero interest rates make many financial services businesses more viable and fiscally healthy. Companies which hold deposits or client dollars for enough time to generate “float” benefit from a higher risk-free rate.” This gives financial services companies more options for fiscal sustainability, and more dollars to invest in technology and services.
What are the business models, use cases, or applications that might be attached to this category?
Generative AI applications and co-pilots will support workflow automation and augmentation. An example in this space, Norm AI, provides a regulatory compliance platform that enhances how businesses manage their compliance processes through the use of AI-powered agents that automate tasks and ensure actions taken by the business align with relevant legal and regulatory requirements.
Financial services technology vendors still have lots of room to optimize processes across the ecosystem. “While it’d be simplistic to assume that the opportunity in these industries is limited to vertical-specific processes, there is a lot of opportunity to further streamline financial services,” says Zhang. Successful upstarts include debt management facilities like Finley, origination software like Vesta, income verification services like Argyle, and tax calculation and filing products like Column Tax.
Within financial services, some startups are shifting to capitalize on float-based models in response to the higher interest rate environment. Several neobanks, for example, are shifting to focus on competitive offerings for securing customer deposits, such as tiered interest rates that increase with higher savings balances, early direct deposit services, or fee-free overdraft facilities. In turn, these startups are utilizing the generated float as a significant source of revenue and operational liquidity to fund lending and other financial services.
Tech-enabled financial service providers are uniquely positioned to spearhead the adoption and deployment of emerging technologies to innovate on traditional service models. “We are particularly excited about this space as a driver of innovation in the industry. Tech-enabled service companies are positioned to be early adopters of new technology to automate their own workflows,” adds Zhang.
B2B software vendors invariably find that financial services is an early adopter, even if the industry is one vertical among many eligible. “If you are selling software that makes people more productive, analyses more accurate, salespeople more effective, support more efficient–you will find a willing audience in this industry, which has had to thrive on lower margins than, say, consumer Internet companies,” says Zhang. The industry has quickly adopted data infrastructure like Hightouch or Lightning AI, as well as productivity tools including Magical.
Technologists are pursuing ambitious experiments in decentralized markets and contract enforcement. “In its early days, many financial services were the result of everyday individuals coming together–for example, in mutuals that protected their members who suffered from unlikely, but devastating, events. It’s not clear yet whether decentralized networks can cut out the ‘middlemen’ that have emerged, but it seems an exciting vision,” says Zhang. Relevant projects touch on insurance such as Subsea, and money markets like Compound.
"It’s not clear yet whether decentralized networks can cut out the ‘middlemen’ that have emerged, but its an exciting vision."
Kevin Zhang~quoteblock
What are some of the potential roadblocks?
The category is inherently vulnerable to monetary policy and cyclical hurdles. “Lending and investing are by definition cyclical—in fact, they are the industries that the Federal Reserve aims to directly affect through interest rate policy. We’re now in a phase where policymakers are looking to contract access to credit in order to slow the economy and defeat inflation. On one hand that shows how the opportunity engine powers everything else, but also in the short run that might mean these industries are looking to cut costs, and will be more discerning around new expenses,” says Zhang.
Many startups are likely to find signing long-term customers far more challenging than securing pilots, given the volume of enterprise budgets dedicated to exploring new technologies. “While many startups are in pilots with enterprises and large institutions, converting these pilots to paying clients is another story,” says Zhang. “There are a lot of enterprises with exploratory budgets for technology right now, and founders should be wary that it will be far more challenging to actually convert these contracts.”
IN THE INVESTOR’S OWN WORDS
Kevin Zhang
Both by background and investment experience, I spend a lot of my time on the opportunity engine businesses of lending, investing, and insurance—all of which serve to channel resources towards unlockable potential.
These are competitive, complex, and critical industries that have always had to apply the latest technology to accurately quantify risk, understand human behavior, assess geopolitical and ecological data, and provide state of the art marketing, distribution and operational excellence.
Moreover, there are many emerging opportunities for business model innovation in the current interest rate environment, which we believe is far more indicative of the future than the past several years of low interest rates.
MORE Q&A
Q: What do other market participants often misunderstand about this category?
A: “Many investors look to invest in the full-stack players, ‘technology-enabled’ lenders and insurers, for example. While it is possible to outperform by building the whole operation from scratch, mixing the pressures of venture investment, and the need to hit a certain growth trajectory, with the reality of risk management often leads to adverse outcomes. It’s easy to believe you’ve built a better risk algorithm, and it’ll take time before you realize you’re actually growing through adverse customer selection.
Another misunderstood element of this category is the presumption that long-run interest rates will be near 0%. This is ahistorical. The reality is that a significant component of many long-standing financial services businesses, especially banking, is borrowing at a lower rate, such as through low-yield deposits, and lending at a higher rate, perhaps near “risk free” to the government; This business model can’t be valued like a software company, but it is often high-margin with sticky customers and recurring revenue."
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