Artificial intelligence (AI) credit risk model provider Flowcast has unveiled the Tillful platform that provides quick, complimentary and transparent credit scores in addition to access to credit offers, according to a Wednesday (Oct. 14) announcement.
Tillful harnesses the firm’s unique, patent-pending machine learning (ML) offering that has been educated and validated with real-world information in conjunction with financial institutions (FIs).
The platform is safeguarded by “bank-level encryption,” according to the announcement, which noted that the offering is currently available to U.S. small- and medium-sized businesses (SMBs).
“In today’s rapidly changing environment, companies need a better way to know what lenders are looking for, monitor their financial health, and get the credit they need,” Flowcast CEO Ken So said in the announcement. “Tillful lets small businesses grow and thrive by leveling the playing field between business owners and lenders.”
Tillful provides complimentary credit analysis revised each day along with a single dashboard of all connected business accounts, which offers an evaluation of the financial wellness of a firm.
The platform also provides access to financing offers based on its credit analysis and actionable customized suggestions to bolster a firm’s credit profile.
According to the announcement, the pandemic has further undermined a SMB credit scoring procedure that depends on limited information and stationary models that don’t view quick changes in the business environment.
“Seeing the economic impact of COVID, we’ve become more committed than ever to democratizing financial data and technology,” So said in the announcement.
In separate news, CRIF Realtime was launching a bevy of offerings dubbed the COVID-19 Credit Passport to assist SMBs in Britain struggling due to the pandemic.
CRIF Realtime, which is focused on credit risks for businesses, indicated at the time that the offering would harness open banking technology and assist companies in better seeing their financial positions.
The data for companies was to be comprehensive, accounting for financial quality prior to, in the midst of, and following the pandemic.
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