Alternative Data for Credit Decisioning:
What Lenders Need To Know in 2025

The latest trends in alternative data for credit decisioning focus on expanding data sources beyond basic bank transactions. Lenders are increasingly (~50%-90% of applications) looking at utility and telecommunications bills, and open banking data to gain a more holistic view of applicants, particularly those with limited credit history. Additionally, lenders are using cash flow data and rental payment histories not just to reduce lending risk but also to get faster loan approvals and to create new loan products tailored to the financial realities of the gig economy.

Types of Alternative Data for Credit Decisioning

Alternative data for credit decisioning includes a range of non-traditional information sources that provide deeper insights into an individual’s financial behavior and reliability. This includes: utility and rent payment histories, which reflect consistent bill-paying habits; telecommunications and e-commerce data, which offers a view of spending patterns and financial stability; and social media activity, which can indicate lifestyle and behavioral traits. Additionally, bank transaction data, employment history, and educational background can be used to assess income stability and potential. The table below summarizes the types of alternative data lenders can use for credit decisioning.

Companies That Provide Alternative Data to Lenders

The use of each data type listed above is subject to strict Equal Credit Opportunity Act (ECOA) and Fair Credit Reporting Act (FCRA) regulations. For this reason, companies that provide alternative data to lenders are instrumental in modernizing credit decisioning by offering non-traditional data sources.

For instance, Experian RentBureau and CoreLogic supply rental payment histories, while Yodlee and Plaid aggregate bank transaction data to reveal financial behaviors. Equifax and TransUnion contribute utility and telecommunications payment data, enhancing traditional credit reports.

These companies and others enable lenders to make more informed, inclusive, and accurate credit decisions by leveraging various alternative data sources. Here is a list of many of those companies.

Benefits of an Alternative Credit Union 

The increased financial inclusion of alternative credit unions provides credit decisioning to individuals without traditional credit. In addition to greater accessibility, they provide applicants with several benefits such as:

More accurate risk assessment

Because they base their decision-making on an applicant's real-time financial activity, alternative credit unions can more accurately discern their eligibility.

Faster approval

AI-powered decision-making is often used by alternative credit unions, making them significantly more efficient than traditional lenders. Similarly, they allow for more widespread approval, as the data averages below depict.

*Data has been averaged from the sources below*

Personalized Lending

The use of alternative credit data allows unions to tailor their loans to the spending habits of the applicant, allowing customizable loan terms and flexible repayment options.

Greater Regulatory Compliance

The use of AI in decision-making allows alternative credit unions to stay on top of the shifting regulatory environment as well as reduce biases present in traditional lending institutions.

Why Lenders Need a Robust LOS to Leverage Alternative Data

Lenders need a robust loan origination system (LOS) to effectively incorporate alternative data in credit decisioning for several key reasons:

• Data Integration: A robust LOS can seamlessly integrate multiple sources of alternative data, such as utility payments, social media activity, and bank transaction data. This integration ensures that all relevant information is considered when evaluating a borrower’s creditworthiness.
• Data Analysis: Advanced data analytics capabilities are essential for processing and interpreting vast amounts of alternative data. A robust LOS can utilize machine learning algorithms and artificial intelligence to analyze these data points, identify patterns, and generate predictive insights that traditional credit scoring models might miss.
• Real-Time Processing: Alternative data often includes real-time information, such as recent bank transactions or mobile phone usage. A robust LOS can handle real-time data processing, allowing lenders to make more timely and accurate credit decisions.
• Enhanced Risk Assessment: By leveraging a modern LOS, lenders can better assess the risk associated with lending to individuals who may lack extensive traditional credit histories. This enhanced risk assessment can lead to more informed lending decisions, reducing the likelihood of defaults.
• Scalability: As the volume of alternative data grows, lenders need a scalable LOS that can handle increasing data loads without compromising performance. A robust system ensures scalability, allowing lenders to leverage alternative data effectively as their business expands.
• User Experience: A well-designed LOS can streamline the loan application process for borrowers by efficiently incorporating alternative data. This can result in a faster, more user-friendly experience, improving customer satisfaction and increasing the likelihood of loan approval.
• Competitive Advantage: Implementing a robust LOS that effectively utilizes alternative data can give lenders a competitive edge by enabling them to offer loans to a broader range of customers, including those who may be underserved by traditional credit models.
• Regulatory Compliance: Incorporating alternative data in credit decisioning must comply with regulatory requirements, including data privacy laws and fair lending practices. A sophisticated LOS ensures that the use of alternative data adheres to these regulations, mitigating the risk of legal issues.