Big data and AI to streamline operations in automotive finance

Throughout all industries, the retail sector is pushing businesses to their operational limits. The automotive industry is no exception. If anything, it is under even more pressure, with the automotive finance market expected to grow to over 500 billion USD in 2033 at a CAGR of 6.5%. Such growth makes data management and processing even more complex.  

Where fleet operations typically involve a limited number of companies leasing many vehicles with minimal contract variations, the B2C and SME markets look entirely different. As OEM captives and leasing companies prepare to deal with end-customers through direct sales channels, their backend must be robust enough to handle thousands of customers with unique contracts and increasingly diverse expectations.  

Historically, OEM captives and lease companies have not been equipped to efficiently handle such data volumes. There are solutions, but the road isn’t clear of obstacles. When you don’t gather, use and monetize your data, you can’t personalize offers and create the smooth-flowing customer experience that vehicle buyers crave. 

On the other hand, when you gather all sorts of data without suitable systems and processes in place, you end up with scattered data sources and incomplete data integrations. This, in turn, leads to inconsistent tool performance and even inadequate personalization. In the end, customers still face a disconnected customer experience. 

How does this impact you? Studies like the McKinsey Automotive Retail Consumer Survey show that customers like to do their research online, test the vehicle in real life, and continue the buying journey online again. When a customer configures a car online, then goes to a local dealership showroom and talks to a representative, there shouldn’t be a need to configure the car again together. The customer doesn’t want this duplicate effort there, and they don’t want it again later when requesting a quote via digital sales channels. In other words, online business and showroom-based business need to be fully connected to provide an integrated buying experience. 

Currently, the only way to connect both experiences is by putting in a lot of manual work. Duplicating this information is time-consuming and error-prone as miscommunication between sales representatives and customers often leads to incorrect price offers and wrong configurations. This doesn’t only result in reduced profit margins, but it also becomes an unwanted bottleneck when dealing with the large sales volumes we find in direct-to-consumer operations.    

OEM captives and lease companies have a tremendous opportunity to revolutionize their operations through AI and data analytics. Accurate, accessible data enables personalization, efficient service delivery, and cost-effective opportunities to scale internal operations. 

Much of this data revolution is powered by connected vehicles or telematics. This technology combines GPS navigation and onboard diagnostics to monitor and track a vehicle’s location, movements, and performance in real time. As 96% of all new cars shipped worldwide are expected to be connected by 2030, almost every car will have the potential for automation, personalization, and upsells. The possibilities are wide-ranging: 

• Driving pattern analysis to enhance safety and efficiency 
• Onboard diagnostics enabling predictive maintenance  
• Trip registrations for tax purposes  
• Battery health updates for EVs.

All of the above lead to more data points, which could create more personalized customer experiences across all touchpoints and optimize second-cycle contracts to increase a vehicle’s lifetime value. 

AI and analytics also play a pivotal role in streamlining operations and reducing costs. Beyond automating well-defined processes, AI excels in processing and understanding large data volumes. The right AI tools can support your employees and help them make better decisions. Possible areas where you can leverage the power of AI are:  

• Automating administrative tasks such as contract verification to make the process faster, more consistent and more accurate
• Using AI for lease agreement reviews to significantly reduce approval times
• Automating risk assessment and credit decisions to ensure consistent, unbiased decisions
• Implementing AI-powered monitoring systems to enable live and accurate fraud detection
• Employing predictive analytics for inventory management to reduce holding costs and may improve delivery times.

In addition, big data and analytics broaden the scope for a range of additional services that may or may not be offered through partnerships. Some examples: 

• Usage-based insurance contracts
• Usage-based billing and Car-as-a-Service models. 

The rise of AI in the automotive finance industry has benefits for customers too. By analyzing behavioral data, spending patterns, and historical transactions, you can offer insightful recommendations tailored to individual preferences and financial situations. This enables you to provide genuinely personalized experiences and client-centric products across the full spectrum. Examples include better communication, flexible subscription models…

Also, your communication with dealerships will improve as data integration and analytics allow for seamless information exchanges and predictive models determining when to get the right vehicles to the right dealers. 

Whether you’re striving to streamline internal operations, improve dealership communications, or offer an integrated customer experience, data is at the center of it all. By embracing this revolution and building on a data-centric company, you may create a fully connected experience with benefits for everyone involved.