The startup has developed a behavioral lending platform that utilizes machine learning to analyze diverse behavioral data for assessing creditworthiness. By categorizing borrowers based on personality traits, the platform enables financial institutions to identify high-quality applicants and tailor competitive financial products.
Funding
$3.7M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Traditional credit scoring models often exclude or misclassify individuals with limited credit history, leading to a high rejection rate for potentially creditworthy borrowers. Financial institutions struggle to accurately assess risk and offer appropriate financial products to this underserved population.
Solution
QUASH provides a behavioral lending platform that leverages machine learning to analyze a wide range of alternative data points, including personality traits, to assess creditworthiness. The platform categorizes applicants based on their unique profiles, enabling lenders to identify reliable borrowers who may be overlooked by conventional scoring methods. By enriching applicant profiles with over 700 new variables, QUASH allows financial institutions to make more informed decisions, customize credit rules, and offer more competitive financial products tailored to individual risk appetites. The platform also provides real-time insights into credit portfolio performance, enabling lenders to optimize their strategies and anticipate borrower behavior.
Target Audience
The primary target audience includes banks, credit unions, microfinance institutions, and other lenders seeking to expand their reach to underserved populations and improve the accuracy of their credit risk assessments.
Features
- Machine learning algorithms that analyze diverse behavioral data to predict creditworthiness.
- Alternative Data Catalog with 700+ variables to enrich applicant profiles.
- Customizable credit rule engine for creating and testing new lending criteria.
- Real-time performance dashboards for monitoring portfolio performance and borrower behavior.
- Personality-based borrower categorization for identifying reliable applicants.
- Integration with existing lending systems via API.