AI predicts lease renewal with 85% accuracy

Predicting end-of-lease activity enables businesses to track cash flow, understand what keeps customers around, and market more effectively.

Businesses can now use Artificial Intelligence (AI) and Machine Learning (ML) to better predict the likelihood that their customers will renew their contracts. According to Odessa, provider of technology solutions for asset finance, the new approach proved to be accurate 85% of the time — enabling Odessa clients to track future cash flow, understand what keeps customers around, help with new and used stock management, and target their marketing more effectively.

Accurately predicting end-of-lease customer actions has long been a goal of the equipment finance industry. Knowing which customers are likely to renew — and which are not — enables companies to allocate both the attention of their workers and the inventory of their products. Machine Learning enables computers to infer patterns from data. In many cases, the model portrays important data to the prediction that is unbeknownst to the human mind.

“AI’s ability to predict agreement renewal enhances customer retention, optimizes customer lifetime value and helps cash flow,” said Odessa EVP Jeff Lezinski.

“The key was to combine business expertise with tech experts who live and breathe the asset finance and leasing industry.”

Developing and honing Odessa’s lease-agreement renewal AI model required multiple sources of data. Lezinski suggested that businesses should ensure that their systems are capturing the right data to maximize future analysis. “Even though there is a significant amount of data for the AI to process, embarking on this type of project is very manageable for asset finance and equipment leasing companies,” said Lezinski. “It’s a relatively simple use case that can produce significant results.”

“Odessa has long hired industry experts who have experienced the same challenges our customers face,” said Odessa CEO Eric Bernstein. “That expertise enabled us to instruct the AI properly to get the most accurate results. We will continue to use AI and every tool that helps us help our clients understand their customers and address their needs. We’re excited to see what else AI will do for equipment finance.”