The asset finance sector is embracing the benefits of artificial intelligence (AI), machine learning (ML), and real-time data, enabling it to optimize performance and position operations for sustained growth in an increasingly competitive market.
However, implementing these innovative technologies like AI in asset finance can be daunting. Asset finance companies must navigate the complexities of shifting customer expectations, a rise in sophisticated fraud cases, and an evolving regulatory landscape. This means that striking the right balance between the best technologies is key to successful integration and sustained growth.
Here, we explore three key areas in which asset finance organizations can use AI, ML, and real-time data to automate tasks, enhance customer experiences, streamline onboarding processes, and boost their auditing procedures.
Customer onboarding
One fundamental area for enhancement in asset finance is the onboarding process. By streamlining business processes, asset finance organizations can effectively assess the creditworthiness of clients during onboarding. This not only minimizes the chance of defaults but also accelerates verification times by utilizing third-party services for credit checks and identity verification.
Over half of asset finance and lending organizations have already recognized the benefits of this. According to the 2023 World Leasing Yearbook, 55% of leasing companies worldwide have adopted digital onboarding solutions, leading to a 35% drop in onboarding times and a 20% increase in acquisition rates. AI can boost customer experience and service processes, which is another aspect of operations.
Customers increasingly prefer to manage their accounts independently and interact with service providers at times that align with their schedules, which often extend beyond the traditional 9-to-5 working day.
On the flip side, they also expect more personalization in their interactions with businesses, which can be achieved through AI chatbots. Many organizations have introduced AI capabilities to handle this shifting mindset, implementing solutions that allow customers to address frequently asked questions at any time of the day or night. This approach not only empowers customers but also frees up staff to focus on other areas of a business, such as assisting vulnerable clients or advancing projects to achieve business goals. Other use cases include biometric verification and digital identity systems to boost customer acquisition and retention rates, as well as Know Your Customer processes to reduce the time and costs associated with customer verification.
Real-time data
Real-time data is proving to be a game-changer for the industry, providing transparency across operations, helping detect fraud earlier, and reducing human error through automated insights. According to IBM’s Cost of a Data Breach Report 2023, organizations that used AI and automation achieved a 34% time-saving in cyber-risk identification and isolation. The report noted that organizations with extensive use of security AI and automation showed the highest cost savings, representing a 39.3% difference.
However, ensuring that all data sources are aligned across an organization is essential. Organizations that are equipped with accurate real-time data are more likely to make informed decisions and detect potential fraud and other risks sooner than those that rely solely on employees to spot issues. Without automated insights, businesses have to depend on human intervention, which can be time-consuming and prone to errors and misinterpretation. A Cox Automotive study found that dealerships expect real-time data to help them increase revenue and profitability, improve customer experience, and boost internal operations. Automating reports and workflows can also streamline internal operations and help identify areas for improvement, such as opportunities to reduce overheads and other spending.
Digital auditing
One notable application of real-time data is in digital auditing, which streamlines the audit process for car dealerships by eliminating the need for staff to travel for physical audits. Research suggests that a hybrid auditing model—where dealerships conduct self-audits alongside less frequent in-person audits by experts—offers a balanced approach. This model enhances risk identification and helps organizations understand dealership and customer trends more effectively. Moreover, it allows for better budgeting for auditing operations by minimizing travel expenses and scheduling disruptions.
While adoption rates may vary across regions due to regulatory and technological differences, the benefits observed by early adopters signal a clear shift toward integrating digital auditing solutions. As a result, digital auditing is expected to become a standard practice in the asset finance industry. In January, SBS will release its latest asset finance study, Asset Finance Trends for 2025. In this study, we will explore the latest AI technologies and real-time data capabilities in greater detail, as well as other trends such as onboarding, decision-making, client experience, digital auditing, compliance, and risk.
How SBS can help
For more than four decades, the SBS Financing Platform (SFP) has helped asset finance organizations worldwide to optimize their floorplan and wholesale business operations by transitioning to a modern, cloud-based solution that enhances agility, scalability, and flexibility. This gives them the advantage of actionable insights to help make informed decisions. You can learn more about the SBS Financing Platform by clicking here.
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