Trends Impacting the Auto Finance Industry
There are considerable opportunities for improving efficiencies in the auto finance industry using newer technologies and data analytics. While several sectors are leveraging technologies such as artificial intelligence (AI), analytics, and mobility to impact their business models, the auto finance industry is still catching up.
There are multiple factors that will reshape auto financing in the coming few years. The inclination toward increased car sharing, Uber, and Lyft services has led to a growing proportion of leases and decreasing rate of car replacements. Such factors will ultimately give rise to severe competition across the auto finance industry.
However, car buyers are on forage for gaining more visibility in the car buying and financing processes. As a first step, the auto lenders need to realign their origination activities, which are related to the changing behavior of their target audience. The auto lenders must identify the challenges faced by the car dealers and their end customers, and then suitably take actions around that.
Many of the auto lenders still perform their business operations using legacy technologies, which stop them from implementing new processes. Therefore, there is a need to introduce organized layers or sophisticated workflows on top of the obsolete systems, which can help drive the advanced methodologies as well as awareness among dealers and end customers.
The organized layer becomes the fundamental framework upon which auto lenders could potentially add technologies such as AI, robotic process automation (RPA), and natural language processing and generation (NLP/G) for automating tedious manual processes. The NLP/G technology has the capability to extract information from contract documents, authenticate the data, recognize exceptions, and boost productivity by more than 50 percent, thereby significantly reducing the time-to-fund for auto lenders.
Besides, auto lenders also use different sources of data, especially in subprime lending for making credit-based decisions. While bureaus handle most of the change in the auto finance industry, the various data sources allow auto lenders to employ ML algorithms for improving their overall auto decision rates. In view of these advancements, well-established industries are successfully leveraging the latest technologies and analytics to focus on their customer needs. In the near future, digital technology and analytics are likely to transform the auto finance industry.