Small and medium-sized business (SMB) lenders often struggle with outdated technology and business models, leading to inefficient lending processes and a disregard for valuable data. This results in limited and unsatisfactory funding options for business owners, contributing to a significant funding gap.

Charm Solutions offers an AI/ML-powered software platform designed to transform financial data into actionable insights for SMB lenders. The platform employs continuous self-learning analytic models to optimize underwriting accuracy and portfolio monitoring. By integrating seamlessly with existing workflows and applications through a robust API service, Charm Solutions enables lenders to identify promising SMB leads, manage portfolios effectively, and detect trends in customer behavior. The platform's AI-powered widgets embed directly into current financial applications, providing access to key features and insights into a customer's financial health.

Customizable real-time scoring models that integrate seamlessly with existing workflows and applications

Web application ready with a robust API service for direct integration

Widget-based technology for embedding AI-powered widgets into existing financial applications

SMBScoreTM, built from decades of SMB accounting data from over six countries, utilizing proprietary ML technology

AI-driven underwriting process optimization to improve accuracy from three intelligence pillars of data sets

Continuous tracking and monitoring of default probability utilizing a borrowers' account behavior and patterns

Opportunity insights to analyze deposit portfolios for qualifying SMBs for new financial product offers

Large-scale data sets to provide valuable insights for determining financial health, optimizing operations, and making strategic decisions

Charm Solutions primarily targets small and medium-sized business lenders, including banks and credit unions, seeking to enhance their underwriting processes, optimize portfolio monitoring, and identify new lending opportunities.