In an industry that has embraced technological evolutions, subprime lenders and their dealers are turning to Artificial Intelligence (AI) to enhance operations. One critical area where AI is proving to be indispensable is in applicant verifications. As subprime lenders strive for greater efficiency, accuracy, and risk management, leveraging AI in the verification process has emerged as a strategic imperative.
Manual loan verification document processing is time-consuming. The verification process includes proof of residence, identity, insurance, and income. It can be prone to human error due to the repetitive tasks.
How does AI improve loan applicant verifications?
With machine learning (ML) and automation, today’s AI technologies provide a software solution that is available 24/7, including holidays and weekends. The solution works accurately without conscious or unconscious bias to calculate and clear stipulations in under 30 seconds with 99% accuracy, compared with an average of seven days for loan verifications.
Today’s subprime lenders are beginning to use AI and modeling technologies to perform complex calculations, ensuring accuracy, identifying omissions, reducing bias and combating fraud. With 99% accuracy and guaranteed service rates, lenders and dealers can focus less on legal and regulatory concerns and more on developing strong customer relationships. Advanced AI technology goes well beyond image recognition (OCR), detecting defects and omissions, and providing insights. And it enables automated loan processing capabilities so lenders can board more loans, reduce bias, comply with regulatory requirements and be audit ready.
Harnessing technology for data extraction
Leading AI verifications solutions automatically extract data and classify documents (such as driver’s license, paystub, W2 form, or bank statements), providing the required fields for the consumer verifications used to determine if the lender will grant the loan. Through accurate income calculations and validation of applicant data and loan documents, loans are processed faster and more accurately, with reduced human errors and fraud risk, and added operational efficiency. This helps create a better consumer, lender, and dealer experience.
In order to classify and extract information needed to validate information in accordance with a lender’s funding rules, today’s solutions use a series of proprietary rules and heuristics, text-based neural networks, image-based deep neural networks and other statistical models. Lenders then leverage those models before determining the decision.
With AI solutions, subprime lenders achieve automation at scale efficiently, while reducing costs. The solutions also reduce manual processes, support compliance and quality, mitigate risk, and deliver significant cost savings.
Today’s AI engines can perform complex calculations, ensuring accuracy, identifying omissions, and combating fraud. With them, lenders are more efficient, lowering loan processing costs and reducing time to process and fund. Dealers and lenders can now focus less on collecting and validating data and more on developing strong customer relationships.
Risk assessment modeling
AI enables lenders to tailor their risk assessment models based on specific parameters and criteria relevant to their customer base. This customization ensures that the evaluation process aligns with the unique risk landscape of each lender. Consequently, lenders can optimize their loan portfolios to achieve sustainable growth.
The integration of AI into applicant verifications represents a pivotal shift toward greater efficiency, accuracy, and risk management. By harnessing the power of machine learning, lenders can make more informed decisions, streamline operations, and stay ahead in an increasingly competitive market. As technology advances, the synergy between AI and financial services will redefine the future of auto lending, unlocking new possibilities for lenders, dealers, and applicants.
