In a time where wallets are filled with credit cards, buy now pay later options are available at the click of a button, and brick-and-mortar lenders are on every corner, yet a significant amount of the population is still considered credit invisible.
The credit invisible refers to those consumers that are invisible to lenders due to a thin credit file. In fact, according to the Consumer Financial Protection Bureau, nearly 26 million US adults are credit invisible, and another 19 million are considered unscorable. If we dig deeper into the 19 million adults that make up the unscorable population, 9.9 million receive this status due to insufficient credit history, and the remaining 9.6 million are due to a lack of recent credit history. As a result of being deemed credit invisible or thin file, millions of consumers struggle to obtain affordable credit and financing options, as traditional credit reports and decisioning services are unable to accurately assess the risk associated with them. However, being regarded as credit invisible does not necessarily mean a consumer is not actually creditworthy. With that being said, financial service providers have begun leveraging alternative data, not only to enhance their current underwriting strategies but to also gain deeper insight into the risk and creditworthiness of the invisible and thin file population.
Alternative Data Fills The Gap
Alternative Data is a term quite frequently used nowadays in the world of data, but we will be looking at it from a credit decisioning point of view. Alternative data used for credit decisioning purposes now includes banking and payment data, employment and income data, telecom and mobile phone data, utility data, and much more. The purpose of leveraging the various types of alternative data is to be able to fill the gaps left behind by the traditional tradeline-based products on the market today. This allows lenders and finance companies to determine credit risk, mitigate fraud, and grow their portfolio by identifying consumers who may have been deemed high-risk, invisible, or unscorable by the traditional bureaus, more accurately.
The Power of Unique Data
When it comes to credit decisions, it is crucial to understand how, when, and what consumers are spending their money, and when they do attempt these payments, what is the outcome? From a risk perspective, it is important to understand if consumers have payments that are unsuccessful due to insufficient funds, closed bank accounts, unauthorized payments, etc. ValidiFI, a Consumer Reporting Agency specializing in alternative data, has credit decisioning and fraud mitigation tools powered by bank and payment data. Bank and payment data is a subcategory within alternative data, consisting of information on consumers’ banking patterns, and reputation history, as well as detailed and aggregated information on their payment and spending patterns. One of the key differentiators between banking and payment data and traditional tradeline data is that it is not a limited view of just payments made to creditors, but instead, considers payments from all aspects of a consumer’s daily life.
ValidiFI takes raw unstructured data from hundreds of thousands of sources, normalizes it, and applies predictive analytics, creating actionable credit risk scores and solutions. One of ValidiFI’s credit risk solutions, the Payment Instrument Risk Score, allows lenders to leverage a modeled score and dozens of granular attributes to identify the riskiest of consumers, as well as identify low-risk applicants for swap-in strategies. Utilizing solutions like this, allows lenders to significantly reduce their fraud and risk as well as lower their cost per funded loan, allowing for significant portfolio growth.
To learn more about ValidiFI’s Credit Risk Solutions and the Payment Instrument Risk Score, visit Payment Instrument Risk Score | Solutions Powered By ValidiFI, email firstname.lastname@example.org or call us at (754)-209-2511.