RPA in the automotive industry: key use cases, examples & best practices

In the auto insurance industry, manual claim processing is a very labor-intensive and error-prone task. Traditionally, claims adjusters must check disparate sources to gather relevant data, such as vehicle accident reports, photos of car damage, and other relevant details. RPA can help collect this data automatically, format the documents, and create a digital record of an accident in the claims management system. 

Similarly, RPA tools can speed up the underwriting process by browsing public databases to check applicants’ criminal records. RPA can autonomously scan these records and create a report based on the findings for an authorized agent. 

AI-powered RPA software can also help auto insurance companies identify potential fraud. The solution can analyze claims, detect inconsistencies in the submitted documents (e.g., mismatched vehicle info or duplicate claims), and trigger a closer investigation if needed.

To meet the market demand, automotive companies need to interact with dozens of suppliers daily, relying on them to timely fulfill contractual obligations. That’s why they need to approach the vendor onboarding process—qualifying, approving, and signing a contract—with the utmost care and attention. This demanding task can be facilitated with RPA software performing background checks of potential vendors by scanning governmental and publicly available databases.

When the supplier is approved by the procurement manager, RPA bots can speed up contract signing. With built-in AI features like optical character recognition, RPA bots can automatically identify and transfer supplier information from document scans, emails, and public databases into corporate supply chain software. If there’s not enough information for supplier onboarding, the bot can send notifications to procurement managers about the missing data.

RPA can significantly enhance freight management, speeding up shipment delivery. For example, a bot can extract relevant shipment details, such as the destination and number of SKUs from a purchase order, and enter this data into the transportation management system to define the optimal route and delivery option. After that, the bot can automatically generate quotes and plan shipments, freeing employees from these mundane tasks.

Сar manufacturers usually have an extensive geographically distributed dealership network. Smooth management of its operations involves multiple administrative tasks, such as reporting sales figures, payment processing, and maintaining compliance documentation. Robotic process automation can facilitate dealer network management by automating data collection, verification, and reporting. RPA bots can also help onboard new car dealers, process sales orders from the dealerships, and generate accurate outgoing invoices.