How Data Gaps Are Creating New Fintech Markets

Financial data today is often scattered across many silos, legacy systems, bank databases, accounting ledgers, and third-party platforms, making it hard to get a unified picture. This fragmentation or “data gap” is now widely recognized as a serious problem.

For example, a recent analysis notes that when critical financial or identity information “is stored across multiple, disconnected systems,” it becomes nearly impossible to access “a single, reliable source of truth”. In practice this means fragmented data leads to inaccurate underwriting, delayed transactions, and higher fraud and compliance risk.

The effect is tangible: one report warns that data fragmentation in financial services could cost the global economy up to $6.5 trillion in lost GDP by 2030. As regulators, banks, and fintech firms grapple with this “hidden data crisis,” nimble startups are seizing the opportunity to build new B2B fintech markets that bridge data gaps and modernize the financial stack.

5 Key Data Gaps in Finance

Several specific data gaps now have an outsized impact across business banking and finance:

1. Small-Business Credit Data

Unlike consumer credit, there is no unified SMB credit bureau. Small businesses’ loan and payment records are dispersed across private co-ops and commercial credit bureaus (Dun & Bradstreet, Equifax, Experian, SBFE, etc.), each with different formats and incomplete coverage.

As a result, lenders “can’t see which lender reported the tradeline,” and many lenders don’t report to any bureau at all. This “scattered, delayed” data makes it hard to assess a small business’s creditworthiness. In other words, a business with solid revenues may still be denied credit simply because its recent payment history is missing in any one system.

2. Treasury and Payments Data

Large corporations and SMBs alike use multiple bank accounts, currencies and payment platforms. Treasury and finance teams often face inconsistent or outdated data. One industry observer notes that “inconsistent data, fragmented financial ecosystems and lack of real-time visibility” are common in multi-entity firms.

This lack of consolidated cash and liquidity data can force slow, manual reconciliations and blind borrowing decisions. Similarly, fragmented payment data, for example, from disparate processors or non-integrated merchant accounts, creates blind spots in cash flow and reconciliation.

3. Account and Accounting Data

Small businesses and startups increasingly use cloud accounting (QuickBooks, Xero) and sales platforms (Shopify, Stripe), but their data often lives behind separate APIs. Finance teams must stitch together accounting records, bank statements, and invoicing data to understand a customer’s health.

As one blog explains, “the ability to access and consolidate data from various sources is crucial for [SMBs] to make informed decisions”, yet aggregating that data is “complex and time-consuming”. This gap has spawned a new category of APIs that connect accounting, banking, commerce and payroll data for B2B applications.

4. Customer Identity and KYC Data

Verifying a business’s identity and structure is harder than verifying a person. Companies can change names, owners or locations frequently, and multiple firms may share an address. Fragmented business registries and KYB (Know-Your-Business) data means banks and payment platforms often rely on manual checks.

As one analysis notes, fragmented data “makes it difficult to confirm a business’s operational status, ownership, and financial history,” raising fraud and compliance costs.

5. Compliance and Reporting Data

Even within banks, data is siloed across departments. Compliance teams may have fraud alerts in one system, while the front office has customer KYC info in another. For example, data collected at customer onboarding is often not integrated with transaction monitoring, creating “significant gaps in compliance oversight”. This fragmentation slows fraud detection and slows regulators’ reporting requirements.

In short, most parts of the business-to-business (B2B) financial value chain lack seamless data flows. Any gap, whether in loan underwriting data, cash positions, vendor invoices, or risk profiles, represents both a headache for incumbents and an opportunity for innovators.

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Origins of the Data Gaps

These gaps have deep roots. Decades of fragmented technology adoption in finance mean many incumbent institutions still run on legacy systems and custom data stores. Regulators and analysts point out that “outdated infrastructure and inconsistent data standards may hinder scalability and interoperability”.

Over time, banks have rolled out new channels, branches, call centers, online banking, mobile apps, each built on different platforms, creating silos between customer interactions. Larger banks also acquire fintechs and merge with other banks, tacking on more disconnected systems.

Organizational silos compound the problem: marketing, lending, payments, and compliance teams often maintain separate databases with little shared access. One analysis compares banks to microscopes: they have “extensive infrastructure built over decades… with long value chains and constraints,” and tend to use data in “a single decision point, within a single team”. By contrast, nimble fintechs build cloud-native platforms from scratch, designed to ingest diverse data from day one.

Geography and regulation also play roles. In the U.S., there is no federal mandate for open banking, so banks have little external pressure to expose data via APIs. (By contrast, Europe’s PSD2 rules forced banks to open account data.) Without a clear mandate, many large institutions have simply deprioritized data modernization and B2B api Integration.

Meanwhile, strict privacy and compliance rules make banks risk-averse about data sharing. The net effect is that “data is used narrowly and in a centralized manner” in banks, leaving many gaps open.

Where the Gaps Are Most Painful?

These data disconnects most impact areas where B2B processes rely on up-to-date financial intelligence:

• Lending to SMBs and Unbanked Segments: As noted, small-business lending is severely hampered by missing credit and cash-flow data. Many community banks and fintech lenders still must manually piece together scattered accounts and payment records to underwrite loans, which raises costs and excludes applicants. Even in consumer finance, credit-invisible or underserved groups face similar fragmentation of alternative data.

• Embedded and Vertical Finance: Vertical SaaS platforms (e.g., restaurant POS systems, health services software, etc.) that want to offer payments or lending must integrate with disparate bank and payment systems. Without unified data connectivity, embedding finance into software is cumbersome and expensive. Industry experts note that embedding finance into SaaS is a major B2B trend , but is slowed by disjointed data sources.

• Treasury and Cash Management: Multi-entity companies struggle to see all cash positions in real time. Fragmented data across subsidiaries and banks means treasury teams can’t easily optimize liquidity or investment. A report on data-driven treasury notes that “fragmented financial ecosystems and lack of real-time visibility are common” for organizations with many entities.

• B2B Payments: Traditional B2B payments (wire transfers, checks, ACH) often lack instant data flows. Collections, invoicing, and reconciliation processes suffer when payment status and remittance info do not flow directly into accounting systems. This motivated fintechs to develop virtual cards and payment orchestration: digital-payment rails that automatically feed transaction data back to b2b company ERP and TMS platforms, eliminating manual reconciliation. Indeed, one analysis predicts virtual cards will process 4% of all B2B payment value by 2025, surpassing cash and checks, in part because they solve data and control gaps in payables.

• Risk, Compliance, and Fraud Detection: In AML/KYC compliance, fragmented customer data creates blind spots. For instance, if customer risk profiles and transaction monitoring reside in separate silos, suspicious patterns can go unnoticed. Fragmented data also amplifies false positives and slows investigations. Industry articles warn that compliance data fragmentation forces extra manual work to consolidate alerts and reports.

In short, any B2B process that relies on up-to-date, integrated financial data is hurt by these gaps. At the same time, each pain point is spawning a new fintech niche to solve it.

Emerging B2B Fintech Markets

The chart below highlights some of the new fintech categories and services arising to fill these data voids. In each case, startups or SaaS companies are building data-centric solutions for businesses and financial institutions:

• Data Aggregation APIs and Integration Platforms: A whole class of fintechs now provides “API engines” or connectors that pull together disparate accounting, bank, and SaaS data. These platforms act as “data supermarkets,” aggregating multiple sources under one roof. For example, firms like Plaid, Yodlee (Envestnet), Salt Edge, MX and TrueLayer focus on banking data, while others like Codat (UK) and Finsheet connect accounting systems (QuickBooks, Xero, etc.) to lenders and platforms. These tools save banks and fintechs from building dozens of one-off integrations. As one fintech blog notes, API aggregators “enable seamless connectivity between different systems,” serving as the backbone for data integration.

• Embedded Finance / Banking-as-a-Service (BaaS): Several fintech firms let software platforms embed financial services by plugging into a unified backend. These B2B platforms (Unit, Synctera, Railsr, Treasury Prime, Stripe Treasury, etc.) handle underlying bank accounts, card issuance, and payments via APIs. By standardizing these financial primitives, they effectively bridge fragmented banking infrastructure. As industry analysts observe, businesses still have pain points in “payments, accounting, and treasury management” that fintechs can automate, and embedded finance is a key route to do so. For example, Unit and Synctera have emerged as fast-growing providers of turnkey banking features for software companies.

• B2B Payments and Expense Management: The rise of virtual cards and expense-management platforms addresses data holes in corporate payables. Companies like Brex, Ramp, Divvy and Tipalti offer cards that integrate directly with corporate ERPs, instantly syncing payment data into finance systems. This eliminates manual invoice matching and gives real-time visibility on spend. One fintech review calls virtual cards a “silent B2B revolution,” noting they feed transaction data into accounting systems and give greater payment control. In addition, payment orchestration services (e.g. Unit, Fingerprint, Bamboo) connect multiple payment gateways so businesses can route and reconcile cross-border payments more easily.

• Lending and Credit Tech for Businesses: Fintech lenders (e.g. Fundbox, BlueVine, Lendio) and data providers (e.g. CreditSafe, DataMerch) are targeting the SMB credit gap. They often use non-traditional data (bank transaction history, receivables, e-commerce sales) to underwrite loans. For instance, a Fundbox executive notes that underwriting now requires “smarter ways to combine [signals] across messy, fragmented sources”. New credit-score platforms for businesses (TrueAccord, Cignifi, Zest AI for biz) also tap alternative data via APIs to build models, effectively creating a parallel credit bureau for SMEs.

• Risk, Compliance and KYC Platforms: Data fragmentation has fueled growth in compliance-related fintechs. Companies like ComplyAdvantage, Trulioo, and Alloy link multiple data sources (watchlists, identity registries, transaction feeds) to give firms a unified compliance view. They break down silos by aggregating risk data, for example, screening customers across 100+ databases and sanction lists. Flagright and other regtechs similarly centralize fragmented compliance data so banks can monitor across systems in real time.

• Treasury Management and Analytics Tools: Addressing fragmented treasury data, a new generation of SaaS tools connects to multiple banks to give CFOs a single dashboard. Platforms like Kyriba, Trovata, and Cashforce use APIs to consolidate balances, FX rates and KPIs across subsidiaries. This tackles the “fragmented financial ecosystem” of multi-entity firms. They also embed intelligence, e.g. AI forecasts and cash pooling, to make use of data that was previously too siloed to analyze.

• Data Intelligence & Decisioning Services: On the analytics side, startups are layering AI and analytics on top of integrated data. Companies like Snowflake (data cloud) and Databricks (AI for finance) enable large-scale blending of financial datasets. Some fintechs, like Bud Financial and DirectID, offer data-enrichment layers that turn raw transaction feeds into insights or credit scores. Others use AI to flag anomalies or predict risk once data is unified. In short, any data gap in the stack is an opening for a data-intelligence provider to step in.

Collectively, these categories represent new B2B fintech markets driven directly by data gaps. For example, Salt Edge (an open banking API company) explicitly identifies five key B2B use cases, SME lending and credit decisioning, digital accounting, treasury management, business finance management/automation, and business banking, that are being unlocked by fintech data connectivity. In each case, fintech solutions use APIs to ingest and harmonize fragmented data, then deliver it as a service to banks or businesses.

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Why Incumbents Have Lagged?

Given the clear need, why haven’t traditional banks and financial platforms already solved these data gaps? The reasons are structural:

• Legacy Technology Debt: Many banks run core systems built decades ago, which makes new integrations costly and risky. As one expert bluntly notes, institutions “simply cannot afford” to keep key operations on 30-year-old systems. Data silos persist because wrangling old mainframes and paper processes is hard. Even updating a single data feed can require months of IT work.

• Organizational Inertia: Within large banks, each department often “keeps its own tools and data”. There is no single owner responsible for enterprise data. This makes cross-silo projects difficult to execute. A decentralized bank might have a great new idea for analytics, but it still needs to negotiate data access across teams.

• Risk and Compliance Caution: Banks’ compliance and legal teams are extremely cautious about data sharing. Introducing new data sources or exposing internal data via APIs can trigger lengthy audits. Many incumbent firms prefer incremental improvements in known systems rather than wholesale data overhauls. For example, regulators sometimes urge banks to improve KYC by using new data sources, but compliance groups can be reluctant to approve unproven integrations.

• Misaligned Incentives: In some cases, the data silos benefit the incumbent’s business model. A proprietary credit scoring system, for instance, is a revenue source. Opening it up may undermine that business. Also, without clear customer demand (especially in B2B web design service, where integration projects are complex), banks lack pressure to fix data fragmentation, especially given the required investment.

In short, legacy and risk aversion have slowed traditional players. This opens the door for agile fintech firms that are built around modern APIs and cloud data stacks. As one industry report puts it, fintech startups “efficiently focus on solving specific niche problems, unburdened by existing infrastructure,” whereas banks’ narrow, centralized data management approach “often falls short”.

Implications and Opportunities

For business leaders and investors, these data-driven gaps signal major opportunities. The next wave of fintech innovation is squarely aimed at the B2B and infrastructure layers of finance. Startups that can aggregate data, marketing automation tools, reconciliation, or enrich decision-making processes stand to capture large markets.

Consider that global fintech revenue pools remain vastly under-penetrated, hundreds of billions yet to be won, and much of the prize lies in smoothing B2B frictions.

Practically speaking, executives looking to invest in or build new fintech infrastructure should:

• Partner or Invest in Data Platforms: Collaborations with API and aggregation providers (e.g., Plaid, BossInsights, Yodlee/Envestnet) can jump-start access to fragmented data. Investing in such platforms or embedding them in your product stack can immediately improve data coverage.

• Build Open APIs and Orchestration: Fintechs should architect for open data from the start. That means designing applications with APIs, microservices, and cloud data warehouses to easily connect new sources. Orchestration layers, platforms that sit between fragmented systems and unify data, are becoming the invisible backbone of modern finance.

• Leverage AI on Integrated Data: Once data silos are bridged, advanced analytics and AI can transform it into actionable intelligence. Tools that apply machine learning to consolidated financial datasets (for cash-flow forecasting, fraud detection, etc.) will yield a strong competitive advantage. Indeed, many B2B finance pain points (like credit underwriting or compliance) are prime for AI enhancement once the raw data is available.

• Address Compliance by Design: In all cases, fintech builders must ensure compliance and security are baked in. Ironically, part of solving data fragmentation is unifying compliance data itself, offering a more auditable and secure data environment than multiple ad-hoc systems.

• Capitalize on Emerging Use-Cases: The categories highlighted above, embedded lending, real-time treasury, expense automation, etc., are ripe for growth. For example, BCG and QED Investors forecast that “fintech growth will be centered around B2B(2X), financial infrastructure, and lending”. Leaders should map which data gaps most affect their market verticals and invest accordingly.

As one strategic report notes, the credit and risk models that serve small businesses or other niche segments are now being “commercialized” via new data services. This means incumbents who ignore the trend risk being outflanked by specialized fintechs. By contrast, executives who recognize that data fragmentation is itself a market inefficiency can reap outsized returns. In effect, fixing data gaps is a growth strategy.

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Conclusion

The fragmentation of financial data has created fertile ground for fintech innovation. For growth-minded leaders, the message is clear: invest in systems and partnerships that break down silos. Centric is at the forefront of helping companies master data orchestration and intelligent analytics The companies that master data orchestration and intelligent analytics will define the next generation of B2B financial services and capture the value left on the table by traditional players.