Driving innovation in auto finance with AI, transformer models, big data analytics

As the auto finance industry continues to evolve, so, too, must the underpinning technology solutions. Collaboration with fintechs helps auto finance companies stay ahead of the competition and drive innovation. This includes partnering in areas such as artificial intelligence (AI), blockchain and mobile payments. It’s becoming clear that AI will play a significant role in separating the winners from the losers.  

One expert in this field, Itamar Arel, chief executive of Tenyx, has developed a new voice agent for customer service that is “10 times better” than previous versions. But what makes it stand out is not just the AI, but also the AI’s ability to interact with legacy systems. 

Legacy systems are deeply entrenched in auto finance, and they are not going away anytime soon. This means that the companies that will ultimately succeed in deploying AI will be those that can integrate it seamlessly with these legacy systems. The key to success is finding companies that are agile enough to deploy AI rapidly, but also mature enough to have deep customer system integrations and the knowledge to quickly build out those capacities. 

Machine learning and AI already help auto finance companies automate manual processes, identify potential risks and improve decision making. This includes AI-powered chatbots for customer support and automated loan approval processes.  

One of the most exciting recent developments is the rise of transformer models in natural language processing. These models use a complex network of algorithms to interpret and process human language, allowing them to be fine-tuned to specific use cases such as verifying and onboarding auto loans. Leveraging masked language models to predict missing words in sentences, transformer models can be trained on ground truth annotated data to improve their accuracy and reliability over time. 

Informed, for one, leverages transformer models to create a cutting-edge solution for auto loan verification and onboarding. The technology is built on top of state-of-the-art models such as BERT and GPT-3, which allow for the processing and analysis of vast amounts of data in real time. By fine-tuning these transformer models to specific use cases, the results are highly accurate and reliable, helping auto finance companies streamline their loan application processes, reducing the risk of fraud. 

Big data analytics 

Big data analytics provide valuable insights into customer behavior, risk management and fraud detection. Auto finance companies can leverage data analytics to identify trends, predict customer needs, improve decision making, and reward dealers who consistently provide clean, compliant deals.  

Legacy systems cannot be the reason innovation stops, but ignoring this critical issue can be a barrier to entry. A key advantage to these new technologies is the ability to learn and adapt over time, ensuring big data analytics is constantly absorbing new data and updating models. Informed’s solution is built on a foundation of ground truth and annotated data in order to build trust.  

Ultimately, partnering with fintechs and leveraging advanced technologies such as AI, transformer models and big data analytics is crucial to keeping auto finance companies competitive and driving innovation and digital transformation in the industry. 

Jessica Gonzalez is the director of lending strategies at Informed.IQ and has more than 15 years’ experience in the financial services industry, including tenures at Santander Consumer USA and Visa.  

The Big Wheels Auto Finance Data 2023 report, the only tabulation of the top 200 auto lenders by outstandings, is available now.