Lendtable, a fintech startup, is revolutionizing the way employees access their company benefits by offering cash advances based on their benefits package. This innovative approach empowers individuals to maximize their financial potential by leveraging their employer's 401K plan or ESPP.
To streamline the application process, applicants only need to upload their paystub. Information from these documents is then used to determine whether an advance should be approved or not, a task that demands efficiency and accuracy.
In this case study, we will explore how Butler's cutting-edge document extraction solution has transformed Lendtable's workflow, resulting in significant time savings and improved customer experience.
Lendtable faced several challenges when processing applications that relied on extracting information from unstructured documents, such as paystubs and 401K statements.
Their existing process relied on humans and was slow. It would take up to 24 hours for customers to be notified of a term sheet to review.
This delay negatively impacted the customer experience and led to a loss of revenue as some potential clients abandoned the process.
Lendtable’s existing document extraction provider was not a good candidate for reviewing paystub applications due to the following reasons:
To overcome the challenges faced in their customer application process, Lendtable turned to Butler's managed large language models to create a tailored solution. They worked with the Butler team to fine-tune large language models specifically for paystub extraction, enabling them to address the unique requirements of their use case.
These models offered several key benefits:
Yuri, a lead product manager on the Lendtable team, shared about their experience with Butler:
"Butler's fine-tuned large language models have been a game changer for our customer application process. The real-time extraction, high accuracy, and seamless integration into our existing workflow have led to faster application times, increased revenue, and reduced manual review. We couldn't be happier with the results."
After implementing Butler's custom document extraction solution, Lendtable experienced impressive results that positively impacted their business:
The combination of these results greatly enhanced Lendtable's onboarding application process, customer experience, and overall business performance.
In conclusion, Butler's cutting-edge document extraction solution played a pivotal role in transforming Lendtable's customer application process. By fine-tuning large language models for their specific document extraction use case, Lendtable significantly reduced application times, increased revenue, and improved operational efficiency with minimal engineering effort. The successful partnership between Lendtable and Butler showcases the power of AI-driven solutions in revolutionizing the fintech industry and enhancing customer experiences.
As Lendtable continues to innovate and expand its offerings, the company looks forward to exploring new opportunities with Butler, including the use of their advanced AI technology for 401K and ESPP plan analysis and other potential applications. This ongoing collaboration is a testament to the value that Butler's solutions bring to the rapidly evolving fintech landscape.