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Paying for high-ticket car essentials is difficult for many people, especially those with short credit histories. What can they do when they need new tires, wheels, or repairs to keep their cars running? Lease-to-own options offer a lifeline for people with limited financial history, giving them the power to get back on the road and take control of their transportation needs.
This US-based company makes the process easy and affordable, providing straightforward lease-to-own options for essential car needs. They promise a hassle-free application process with instant approval, opening doors for those who might otherwise struggle to get financing.
But making smart leasing decisions is a complex balancing act. Approving too many high-risk applicants can lead to defaults and lost revenue while being too strict can mean missed opportunities and frustrated customers. Finding that sweet spot where business goals and customer needs align is a constant challenge.
Data Orchestration: The vast and diverse applicant pool has a limited financial history, so the risk data had to be orchestrated from many different legacy data systems—APIs, databases, spreadsheets, etc. This posed significant hurdles for a human-only team.
Real-Time Decision Making: The need for instant approvals with limited data required a highly efficient and accurate decision-making process.
Dynamic Applicant Pool: The evolving applicant pool demanded a shift from static rules to a dynamic AI-based decision engine. Models that worked a year ago may no longer deliver the same accuracy today.
Modernized Business View: The company sought to scale and modernize its customer and business insights using modern BI applications. They needed ways to access and process insights from the decisioning system.
To address the leasing company's challenges, RapidCanvas implemented a multi-faceted solution that combined data orchestration, AI-powered risk assessment, and explainable AI to provide a comprehensive and transparent decision-making platform. The project began with an expert-led assessment of existing systems and challenges. Rapid Canvas dedicated a team of outstanding data scientists to ensure we architected a bespoke solution tailored to company needs.
First, we tackled the challenge of data orchestration. Internal and external data from various sources, including user-provided information and third-party databases, were seamlessly integrated and analyzed. This provided a holistic view of each applicant, revealing patterns and anomalies that informed risk evaluation.
Next, we focused on creating a robust risk assessment model. We engineered additional features, such as financial ratios and email trust scores, using the orchestrated data to improve the model's accuracy and predictive power. The RapidCanvas platform's AutoAI capabilities seamlessly facilitated this feature engineering.
The core of our solution was an AI-powered risk prediction model. Using AutoAI, this model automatically identified the best algorithm to assess the risk of each lease application in real time. Importantly, we prioritized explainable AI, ensuring the model's decision-making process was transparent and understandable. This explainability is crucial for maintaining accountability, fairness, and trust in automated decisions.
To further enhance the platform, we incorporated:
This comprehensive, expert-led approach not only streamlined the leasing company's operations but also enhanced the accuracy and transparency of their risk assessment process, ultimately leading to better business outcomes and improved customer experiences.
The AI-powered leasing platform developed by RapidCanvas delivered outstanding results, exceeding the company's expectations and transforming its business operations. By starting with an expert-led process and then applying the most advanced AI technology to address challenges, we crafted a future-proof solution that improved operations quickly.
Growth and Brand Promise: By leveraging AI and machine learning, the company successfully scaled its customer base while maintaining its brand promise of an easy application process with instant approvals, even for applicants with limited financial history. The system can now accurately process 20X more applications. This ensured continued customer satisfaction and reinforced the company's commitment to providing accessible financing options.
Improved Leasing Risk Management: The dynamic, real-time machine learning models provided valuable insights into applicant risk profiles, enabling the leasing company to make more informed decisions throughout the application and payback periods. This proactive approach to risk management reduced financial exposure and improved business stability.
Increased Revenue: The platform's ability to accurately predict leasing risk powered 10% revenue growth. The company minimized losses and improved overall profitability by identifying potentially high-risk applications.
Deeper Customer Insights: Interactive data apps provide a 360-degree view of each customer, enabling deeper analysis and understanding. Segmenting and clustering users based on patterns and behaviors enabled more targeted and effective marketing and CRM strategies.
These results highlight the transformative impact of RapidCanvas's AI-powered solution on the leasing company's business. Operations are vastly more scalable, accurate, and run more smoothly. It's a win-win for everyone, showing how powerful Agentic AI, administered by a dedicated Rapid Canvas expert, empowers people and businesses.
To learn more about how RapidCanvas can help your business with your challenges, contact us today for a free consultation.
