How AI & Alternate data help Lenders in Credit decisioning

The fact is, as many of 30% of adults in today’s credit market are virtually invisible to traditional screening methods. The growing population of digital natives, students, and recent immigrants do not fit neatly into the spending and borrowing habits of previous generations. Most lending tools do not recognize this massive opportunity. It is not fair for either borrower or lender. The introduction of advanced AI & alternative data makes the process of consumer lending fast, more accurate and efficient. It uncovers the full potential of customer data and delivers better financial return, while cutting down expenses.

So, let us see how Artificial Intelligence and Alternative Data help lenders grow in today’s changing market.

AI and Alternative data, the game changers

AI-powered analytics and alternative data provide the predictive analytics that lenders need in a world of tightening credit, digital innovation, and increased competition. These new tools help lenders see more, accept more, and grow more.

By leveraging on alternative data, it will not only allow you to have a holistic customer view and identify the trends and patterns, but also include external factors like market trends, political issue, economic changes, social factors to accelerate timely and precise credit assessment that provides you 360-degree view on customers’ credit behaviour and potential risk. Initiating your first step correctly and effectively is extremely important to ensure accurate predictions and help you to make better decisions towards your desired outcome.

Using AI and unique, uncorrelated, alternative data, lenders can identify the millions of creditworthy customers that traditional screening miss, even from thin- file and no-file households. A generation of digital natives qualifies for the credit they deserve, while lenders gain fast, fair, and frictionless access to the consumers they need to grow business, reduce risk, and maximize profits.

Here are different ways AI & Alternative data positively influence the changing credit market.

Improved assessment of creditworthiness using alternative data: Effective credit risk management begins with finding the right data for today’s growing market segments. The Consumer Financial Protection Bureau (CFPB) estimates that 26 million Americans are credit invisible or “no file”—they have no credit history with nationwide consumer reporting agency. Traditional account screening services deliver little or no predictive insights to several consumers. By combining uncorrelated alternative data with traditional credit scores, lenders can maximize the data coverage for their markets—an absolute requirement for optimizing revenue growth.

Predictive Analytics to make profitable decisions: When it comes to AI powered analytics, one size does not fit all. Lenders have various business goals and tolerance for risks. Markets vary by industry and patterns of risk. The most effective use of AI tailors AI-powered analysis for specific lenders, and then refines that analytical model over time, giving lenders an increasingly predictive and accurate score for credit risk assessments.

By customizing analytics and refining those analytics over time, lenders can optimize their loan-decision processes for growth. By applying customized AI-powered analytics to alternative data, lenders can discover predictive signals that other screening services miss, leading to 20-30% more profitable accounts.

Using AI to bring transparency to compliance: By using sophisticated AI techniques to analyze disparate types of traditional and non-traditional data, it is possible to separate the signal from the noise and deliver insights that are both predictive and interpretable. Explainable AI enables lenders to apply AI techniques at the top of a data waterfall, accepting more profitable accounts before additional data costs are incurred. When lenders use Explainable AI to gain predictive insights, they can grow profits while helping ensure compliance.

Optimize Waterfall: The ability to bring custom analytics to your data waterfall offers a powerful advantage for lenders looking to add customers and reduce risk. Lenders should look for credit risk scores with easily integrated APIs and insights that can be applied to any point in data waterfalls, giving lenders the freedom and flexibility to tune loan-decisions for the best possible results.