Against a backdrop of high interest rates, supply chain issues, changes in the mix between new and used vehicles, increasing regulatory pressures, and general economic uncertainty, there is no question that the auto financing landscape is more competitive than ever.
Additionally, the prized cohort of younger buyers, who have “grown up digital,” leads the way when it comes to the desire for a seamless and transparent car purchase and finance experience. Data from the Deloitte 2021 Global Automotive Consumer Study found that while older consumers still value (or will at least tolerate) an in-person shopping experience, a growing number of younger consumers want a totally virtual buying experience.
The old ways of doing business no longer meet the needs of lenders or their customers, driving the need to evaluate and adopt new approaches to price loans and manage risk, and the technologies that support them.
Many auto finance companies may have attempted to implement risk-based pricing in the past, only to be disappointed in the poor results. These poor outcomes include:
High up-front development costs
Large ongoing expenses for model refreshes
Continuous, costly, and disruptive software updates and maintenance
Unpredictable issues when integrating with existing systems
Today, more agile, composable, and intelligent solutions are helping auto lending companies reimagine internal pricing operations.
Modern pricing solutions, such as those offered by Earnix, eliminate these issues. These proven technologies help lenders evolve their best practices and innovate their operations to better serve demanding modern customers.
As the foundation for these solutions, machine learning (ML) and artificial intelligence (AI) can provide much deeper insights into consumer, market, and competitive data, and significantly improve pricing models and outcomes.
Greater personalization and quicker turnaround time
