Data providers are out; aggregators and end-to-end, AI-powered solutions are in.
The Era of Data Providers is Over
For years, financial services and payments companies have relied on a fragmented ecosystem of data providers to fuel their risk assessments, lending decisions, and onboarding processes. The belief was that more data meant better decisions. But reality has proven otherwise—more data sources do not mean better outcomes; they often create more complexity and slow down decision-making leaving onboarding teams with SLA’s they can’t meet.
The fintech industry is evolving rapidly, with trends like AI-driven automation, embedded finance, and real-time decisioning reshaping how businesses operate (Fintech Futures, 2025). Financial institutions, payment providers, and lenders no longer need just data; they need platforms that turn raw data into instant, intelligent decisions. And regulators know this.
This shift is already happening. Across key financial processes—merchant underwriting, POS finance, and beyond—companies are abandoning traditional data providers in favor of aggregators and end-to-end solutions that automate decision-making. The winners in fintech will be those who enable instant approvals and real-time risk assessments—not those who simply sell more data.
Merchant Underwriting: Automation, Not More Data Sources
The Problem: Fragmented Data Slows Down Approvals
Merchant underwriting has traditionally been a slow and inefficient process. PSPs, acquirers, and financial institutions pull reports from multiple data providers—business registries, credit bureaus, fraud databases, and other sources—to assess risk. The problem? Underwriters spend too much time manually analyzing disconnected information instead of making decisions.
The Era of Data Providers is Over
For years, financial services and payments companies have relied on a fragmented ecosystem of data providers to fuel their risk assessments, lending decisions, and onboarding processes. The belief was that more data meant better decisions. But reality has proven otherwise—more data sources do not mean better outcomes; they often create more complexity and slow down decision-making leaving onboarding teams with SLA’s they can’t meet.
The fintech industry is evolving rapidly, with trends like AI-driven automation, embedded finance, and real-time decisioning reshaping how businesses operate (Fintech Futures, 2025). Financial institutions, payment providers, and lenders no longer need just data; they need platforms that turn raw data into instant, intelligent decisions. And regulators know this.
This shift is already happening. Across key financial processes—merchant underwriting, POS finance, and beyond—companies are abandoning traditional data providers in favor of aggregators and end-to-end solutions that automate decision-making. The winners in fintech will be those who enable instant approvals and real-time risk assessments—not those who simply sell more data.
Merchant Underwriting: Automation, Not More Data Sources
The Problem: Fragmented Data Slows Down Approvals
Merchant underwriting has traditionally been a slow and inefficient process. PSPs, acquirers, and financial institutions pull reports from multiple data providers—business registries, credit bureaus, fraud databases, and other sources—to assess risk. The problem? Underwriters spend too much time manually analyzing disconnected information instead of making decisions.
As McKinsey notes, fintechs must now prioritize efficiency and automation over raw data aggregation to achieve sustainable growth (McKinsey, 2025). The fintechs that succeed will be those that automate underwriting with AI-driven decisioning instead of relying on traditional data workflows. To be clear: Data is no longer the new oil. It has to be refined.
The Solution: AI-Driven Merchant Underwriting
Instead of pulling endless reports, fintechs and PSPs should leverage aggregators that unify data, apply AI models, and deliver real-time risk scores.
At Gratify, we’ve seen firsthand how this shift accelerates merchant onboarding. Our platform integrates real-time identity verification, AI-powered risk scoring, and automated compliance checks, enabling PSPs to approve merchants in minutes—not days. Rather than forcing underwriters to sift through fragmented data, we deliver a single, AI-enhanced decision, reducing costs and onboarding friction.
This trend aligns with broader industry shifts toward collaborative AI and automation, where machines handle repetitive tasks while humans focus on strategic decision-making (Finextra, 2025).
POS Finance: Underwriting at the Speed of Retail
The Problem: Slow Credit Decisions Kill Sales
Point-of-sale (POS) financing has surged in popularity, yet many lenders still rely on outdated credit decisioning models that pull from multiple data providers instead of making real-time decisions. This fragmentation creates delays, increasing checkout abandonment rates and frustrating consumers.
Fintech experts predict that AI-powered decisioning will replace traditional credit assessment models in the next few yeexpect instant gratification, and lenders that can’t deliver approvals in real time will lose market share.
The Solution: Embedded, Real-Time Credit Decisioning
Lenders must shift from data fragmentation to embedded, AI-powered credit decisioning. Instead of relying on batch credit checks, manual fraud analysis, and slow approvals, modern platforms must aggregate multiple data sources into a single, instant risk model.
At Gratify, we’ve built our identity-based lending platform to do just that. By integrating:
✅ Real-time identity verification
✅ Behavioral analytics
✅ Proprietary AI risk scoring
We deliver instant credit approvals at the POS, reducing friction and increasing conversions. Instead of sending consumers through multiple steps and credit bureau checks, our AI evaluates risk in milliseconds, ensuring a seamless experience.
This approach aligns with predictions that "Agentic AI"—AI-driven automation that actively makes decisions—will dominate fintech by 2025 (Fintech Futures, 2025)
Why Aggregators and End-to-End Platforms Are Winning
The Problem: Fragmentation Is a Business Killer
The financial industry has spent decades piecing together solutions from multiple data providers—one for identity verification, another for credit scores, a third for fraud detection. This model creates unnecessary complexity and costs.
More importantly, it doesn’t solve business problems. Banks, PSPs, and fintechs don’t need more raw data—they need automated, AI-driven decisioning that turns disparate information into instant approvals.
The future of fintech is shifting away from data providers and toward end-to-end platforms. Instead of forcing businesses to integrate multiple APIs and vendors, these platforms:
At Gratify, we don’t just provide data—we provide decisions. Our real-time identity-driven decisioning platform enables PSPs and lenders to approve merchants and consumers in seconds, not days.
This shift is already transforming fintech, as embedded finance, automation, and AI-driven decisioning become the standard for financial services (CFC, 2025).
Conclusion: Decisioning is the New Data
The age of data providers is over. Banks, PSPs, and fintechs no longer need more fragmented data sources—they need automation, intelligence, and real-time decisioning.
The fintechs that will thrive in the next decade won’t be the ones with the most data—they’ll be the ones that make the fastest, smartest decisions. Whether it’s merchant underwriting or POS finance, the winners will be those who provide instant, seamless, and intelligent decisioning.
Fintech is undergoing a fundamental shift. Those clinging to traditional data provider models will fall behind. The future belongs to AI-driven automation, aggregators, and end-to-end solutions that power business decisions—not just data collection.
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