Navigating risk and opportunity with alternative credit data

Learn how financial institutions and fintechs can use alternative credit data, like verified employment and income, to make better lending decisions

Financial institutions and fintechs are working to strike the right balance between growth, customer experience, and risk mitigation amid a changing financial landscape. 

The gig economy now employs 42 million Americans, but traditional credit bureau data wasn't designed for workers with variable income streams or non-traditional employment. As consumer financial behavior evolves beyond conventional credit products, lenders face a critical question: How do you accurately assess creditworthiness when your primary data source only tells part of the story?

Forward-thinking institutions are finding answers in alternative data points that reveal how people actually manage their finances. These insights are reshaping how lenders evaluate risk, expand their markets, and serve customers who've been invisible to traditional credit models.

The limitations of relying on traditional credit data alone

Today’s financial organizations are tasked with figuring out how to enable growth and expand lending while maintaining responsible credit risk management.

This challenge is heightened by three key trends:

1. Continued economic and workforce shifts — The gig economy is booming, leading to less predictable consumer income and employment patterns.
2. Evolving consumer financial behaviors — The rise of digital banking, buy-now-pay-later services, and alternative financial products has changed how people manage and access credit.
3. Higher customer expectations — Customers expect lending decisions to happen in seconds and with fewer documentation requirements getting in the way.

Traditional credit assessment relies heavily on credit scores, often missing key financial health signals like cash flow and rent payment history. This narrow focus prevents lenders from making decisions that reflect the full complexity of modern financial relationships.

Dependence on credit bureau data alone makes it difficult to evaluate loan applications from potential borrowers who can be classified as:

• Freelance workers with variable income
• Young professionals early in their careers
• Recent immigrants without a U.S. credit history
• Small business owners with complex finances

As a result, organizations deny qualified borrowers who lack conventional credit histories. Good customers get turned away, and lenders lose out on profitable business.

Without comprehensive borrower data, financial institutions and fintechs default to burdensome documentation requirements or outright rejections. These rigid verification processes increase drop-off rates and push qualified applicants toward alternative lenders. Meanwhile, banks, credit unions, and fintechs whose underwriting processes are anchored to traditional credit reports struggle to adapt to economic shifts or emerging fraud patterns.

How alternative credit data fills the gaps

In lending, alternative data is any information beyond what traditional credit bureaus typically use to perform traditional credit scoring. While these bureaus focus primarily on credit product history (mortgages, credit cards, auto loans) and negative entries (bankruptcies, collections), alternative data paints a more holistic portrait of an applicant’s financial behavior.

The most valuable types of alternative data for lenders include:

• Cash flow data — Bank transaction history showing income patterns, spending habits, and financial responsibility
• Employment and income data — Verified current and historical employment information, including income stability and earning potential
• Bill payments — Consistent payment of monthly obligations that traditionally don't appear on credit reports, like rental payments and utility bills
• Business financial data — For small business lending, including revenue trends, accounts receivable, and accounting software integrations

Thanks to open banking, financial organizations can now access real-time bank account data when authorized by customers. This direct connection reveals how people actually manage their money (from cash flow patterns to bill payment consistency) without lengthy documentation processes.

While traditional credit scores can take years to reflect financial improvements, alternative data provides an immediate view of an applicant's financial health. Lenders can see current income patterns, spending habits, and payment reliability, leading to faster, more accurate lending decisions.

This comprehensive approach helps financial institutions serve previously overlooked customers while managing risk. Community banks and credit unions can confidently expand credit access to qualified borrowers who might not have conventional credit histories, creating new growth opportunities while maintaining strong underwriting standards.

Making alternative credit data work for your organization

The alternative data ecosystem includes hundreds of specialized providers, each offering unique insights into consumer behavior and creditworthiness. And it’s growing, with traditional credit data providers making intentional moves into this space. 

Equifax’s The Work Number®, for example, provides real-time access to verified income and employment history via payroll-sourced data from over 2.5 million employers. Using The Work Number®, financial organizations can:

• Strengthen identity verification — Cross-reference employment records to reduce synthetic identity fraud
• Streamline lending decisions — Automate credit origination by instantly verifying the ability to pay
• Optimize account management — Support both origination and ongoing monitoring by identifying credit line opportunities and payment arrangement needs
• Improve recovery outcomes — Use current employment status to inform collection strategies
• Expand market reach — Confidently serve credit invisibles with verified income and employment data

Watch our webinar: Onboarding strategies that fuel growth and reduce risk

Leveraging the power of data orchestration

Integrating traditional and non-traditional data sources into your risk assessment workflow is the first step towards smarter lending decisions. But once you've added multiple data providers to your tech stack, you face a new challenge: managing different APIs, data formats, and integration requirements across providers.

Data orchestration solves this by creating a unified layer that connects, standardizes, and manages data from multiple sources in real-time. Modern identity and fraud prevention platforms like Alloy act as this orchestration layer, centralizing access to diverse data sources through a single integration and allowing institutions to test and optimize multiple data streams without extensive engineering resources.

By seamlessly combining fraud, compliance, and credit signals into a single workflow, financial institutions and fintechs can gain the most comprehensive view of customer risk.

This unified approach enables:

• Fraud teams to detect emerging patterns with greater accuracy
• Compliance teams to maintain consistent, auditable processes
• Growth teams to confidently approve more qualified customers
• Product teams to identify and resolve onboarding friction points

Learn why data orchestration is essential for modern financial services

Partnering for success

As customer expectations increase and fraud threats evolve, financial organizations that rely on point solutions and legacy data are at a competitive disadvantage. 

Over 700 banks, fintechs, and credit unions — including 25% of the top 50 US banks — use Alloy’s identity and fraud prevention platform to achieve a safe balance of growth and fraud risk. Our platform connects 250+ pre-configured data integrations from leading global providers, so financial organizations can deploy new data sources quickly without extensive engineering resources.

Through our partner network, you gain access to best-in-class machine learning-powered scoring models from specialized providers, each trained to detect specific fraud patterns and inform credit decisions. Alloy's orchestration layer ensures these tools work together seamlessly.

Discover our data partners