Cracking the Code of the Financial Information Gap

This article was co-authored by my co-founder Julia Yao.

In the first article in our series "Transforming Finance with AI - The Dawn of a New Era", we explored how AI is poised to transform financial services by addressing inefficiencies and unlocking new opportunities. Today, we tackle a different but deeply related issue: the information gap. This imbalance in data access doesn’t merely slow things down—it fundamentally shapes the power dynamics of finance.???

Why Unequal Access to Information Is Finance’s Biggest Challenge—and Opportunity?

Imagine you’re preparing to invest in a mid-market manufacturing company. The preliminary financial reports show consistent year-over-year revenue growth, stable EBITDA margins, and a robust pipeline of new customers. On the surface, the deal looks promising—until you dig deeper. Behind these numbers, hidden risks lurk: unresolved lawsuits in key jurisdictions, a shrinking customer base in one of the company’s most profitable regions, and a reliance on a critical supplier whose financial health is questionable.?

Now imagine your competitor knows all of this—not because they worked harder, but because they had access to better information. That edge can spell the difference between a profitable investment and a costly misstep.??

This scenario highlights one of finance’s greatest inefficiencies: Information Asymmetry. It occurs when one party in a transaction has more or better information than the other, leading to imbalanced decisions, misaligned valuations, and missed opportunities. In finance, where success often hinges on who knows what, information asymmetry isn’t just a challenge—it’s a defining characteristic.?

From our vantage point of implementing AI solutions for clients, we see that these imbalances often arise not from a shortage of data, but from an overwhelming surplus of it—scattered, unstructured, and locked away in spreadsheets or siloed systems. This data overload makes it difficult to sift out the insights that truly matter. LLMs (Large Language Models) and AI agents can parse this data at scale, surfacing critical information that might otherwise remain hidden. We’ll explore how these tools can transform due diligence, deal sourcing, and other high-impact areas in the sections ahead.?

Understanding Information Asymmetry?

In finance, Information Asymmetry is a systemic issue. One party—whether an investor, a fund manager, or a company—holds more data or insights than others involved in the same transaction, often causing inefficiencies, delays, and even mistrust. Historically, this disparity stemmed from a lack of information. However, in the era of big data, modern information asymmetry increasingly arises from data overload—an excess of information so vast that stakeholders struggle to isolate the critical insights from the noise.?

Here’s how it shows up across the industry:?

• In Venture Capital: Startups often present glowing projections—double-digit month-over-month growth, ambitious customer-acquisition metrics, and impressively low churn rates. Yet, the raw data behind these claims can be scattered across CRM systems, user analytics platforms, and finance software. Parsing it all manually can take weeks of due diligence. Smaller VC firms or those without advanced analytics tools may struggle to validate the numbers hidden in thousands of rows of usage logs and transactional data. Consequently, they either miss red flags—like short-term promotional signups that inflate growth—or spend so long analyzing the details that they risk losing out on competitive deals.? ?

• In Private Equity:? During M&A processes, brokers create massive virtual data rooms filled with financial statements, operational reports, supply chain records, and legal documents—sometimes totaling tens of thousands of pages. Selective disclosure also comes into play: certain bidders may be granted deeper access to detailed cost-breakdown reports or segmented revenue data, creating an uneven playing field. Even if a bidder gains access to all the documents, the sheer volume can obscure crucial insights—like hidden dependency on a single supplier or an underperforming product line. Firms with AI-powered due diligence platforms that can rapidly filter and analyze this flood of data often gain a decisive advantage.? ?

• In Wealth Management: Limited Partners (LPs) must trust General Partners (GPs) with their capital, but they seldom receive real-time information. GPs themselves might collect performance data from multiple portfolio companies—each using different accounting systems, CRMs, and dashboards—leading to a mountain of unstructured and siloed data. By the time GPs compile quarterly or annual reports, the results are heavily summarized. LPs are left with broad overviews and minimal insight into day-to-day fund activity. This gap can delay critical decisions—such as rebalancing allocations or divesting from underperforming assets—because LPs simply don’t have the tools or data to act quickly.? ?

?

These imbalances aren’t just inconvenient—they’re costly. Capital is misallocated, deals are delayed, and opportunities are lost. But of course, information asymmetry is a double-edged sword. On one other side, it fuels capital efficiency by giving savvy investors the insights they need to back promising ventures, and it hands a big advantage to whoever holds the exclusive data. Indeed, information asymmetry can tilt the playing field and spark debates about how widely industry-defining insights should be shared.?

How AI Can Be The Solution?

Artificial intelligence offers a solution to information asymmetry by leveling the playing field. It does this not by eliminating the human element in decision-making, but by empowering professionals with data-driven insights and tools. ?

Drawing on our experience helping companies implement AI in their workflows, we’ve seen firsthand how bridging information gaps can supercharge productivity and decision-making—particularly in data-intensive fields like finance. Here’s how AI addresses the issue:?

1. Making Due Diligence Faster and Smarter?

In private equity, reviewing a Virtual Data Room (VDR) often takes weeks, as firms sift through thousands of documents. AI tools can change that. By synthesizing legal, financial, and operational data, AI surfaces critical insights—like customer churn trends or recurring legal risks—within hours.?

For example, Kira Systems uses machine learning to identify and extract key clauses from contracts, helping firms cut through the noise and focus on what matters.?

2. Enabling Real-Time Transparency?

Wealth management has long struggled with information gaps. Limited Partners (LPs) often rely on periodic reports from fund managers, leaving them in the dark between reporting cycles.? AI-powered dashboards such as Tetrix offer real-time views of fund performance, data analysis, portfolio health, providing actionable insights.?

This instant access doesn’t just keep investors in the loop; it fosters trust and collaboration between partners, speeding up decision-making and strengthening relationships.?

3. Accelerating Deal-Sourcing?

Identifying investment opportunities, particularly in the Small and Medium Business (SMB) space, requires sifting through fragmented data. AI can predict which companies are likely to seek investment by analyzing patterns like hiring trends, customer growth, and market positioning. Tools such as Grata and Sourcescrub use AI to surface opportunities in the middle market that are otherwise obscure to investors.?

We have recognized that layering LLMs or AI Agents with dedicated tool access on top of these predictive models can help interpret unstructured data—such as social media sentiment or press releases—further refining deal-sourcing strategies.?

Emerging New Opportunity: The Investment Tech Segment?

The emergence of Investment Tech—a new market segment focused on leveraging AI to solve finance’s biggest inefficiencies—marks a turning point. Unlike fintech, which serves consumers, Investment Tech empowers financial professionals by tackling problems like data fragmentation and inefficient workflows.?

There are many companies active in this sector. Here are a few standout innovations:?

• Hebbia : Supercharges research workflows, designed to help teams analyze vast amounts of data, and gain actionable insights?

• Synaptic : enables Private Equity and Venture Capital investors to use alternative data for sourcing, tracking and due diligence. ?

• Dealroom.co : provides a global data platform offering intelligence on startups, innovation, high-growth companies, ecosystems, and investment strategies.?

• Boosted.ai : enhances portfolio management productivity via AI-powered software that assists investment managers?

These tools don’t just close the information gap—they democratize access to insights. Smaller firms can access the same data-driven insights as their larger counterparts, leveling the competitive landscape.?

The Opportunity Beyond the Gap?

For decades, information asymmetry has been an accepted reality in finance. But today, AI is shifting the paradigm. By providing real-time insights, automating tedious processes, and surfacing hidden opportunities, AI transforms asymmetry from a challenge into a competitive advantage.?

The financial services firms that embrace these tools will not only work more efficiently—they’ll also gain the trust and confidence of their stakeholders. In an industry where information is power, AI ensures that power is shared, not concentrated.?

Next in the Series?

In our next article, we’ll dive into AI tools reshaping finance, from accelerating diligence to predictive analytics for spotting that elusive “next big thing.”?Stay tuned!