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Cheers Financial Launches AI-Powered Credit-Building Tool, Averages 21-Point Score Increase

Cheers Financial leverages AI to boost credit scores by an average of 21 points, enabling immigrants to build financial independence in the U.S.

Cheers Financial, a startup founded by fintech entrepreneur Ken Lian, has recently integrated artificial intelligence into its credit-building platform, designed to assist individuals, particularly immigrants, in establishing financial independence in the United States.

Launched from Pasadena-based Idealab Inc., Cheers Financial, co-founded by Zhen Wang and Qingyi Li, offers a streamlined onboarding process aimed at making credit access fairer for those who often struggle to meet traditional banking criteria. “Our mission is really to try to make credit fair to individuals who want to have financial freedom in the U.S.,” Lian stated.

Having arrived in the U.S. as an international student from China in 2008, Lian encountered significant challenges in securing a credit card, taking four years to obtain bank approval. Since 2021, he has focused his fintech initiatives on dismantling barriers that immigrants face in credit access and development.

Since its inception in November, Cheers Financial has experienced “healthy growth,” attracting thousands of users to its secured personal loan product which permits credit building through automated monthly payments. Users receive their principal back at the end of a 24-month loan term, with interest rates averaging around 12.2%.

“The product is designed to automate the entire flow, so users basically can set and forget it,” Lian explained. Partnering with Minnesota-based Sunrise Banks, Cheers has observed an average 21-point increase in credit scores within a few months for users entering with “fair” scores, ranging from the high 500s to mid-600s.

The company’s use of AI for data summarization and matching enables it to report to the three major credit bureaus every 15 days, effectively doubling the frequency of updates compared to popular credit-building app Kikoff. Lian aspires to reduce this reporting interval further to seven days.

Cheers Financial is not the first venture for Lian, Wang, and Li in the realm of alternative financial tools. Their prior initiative, Cheese Inc., launched in 2021, also aimed at providing credit-building loans alongside services such as a no-fee debit card with cashback options. However, Cheese faced challenges when its operational partner, Synapse Financial Technologies, collapsed in April 2024, leaving numerous users unable to access their savings.

The fall of Synapse served as a critical lesson for Lian and other fintech founders about the vulnerabilities within the digital banking ecosystem. As he prepared to launch Cheers, Lian prioritized establishing in-house models and a direct relationship with banking partners. “That allows us to build a very secure and stable platform for our users,” he noted.

Despite a decline in fintech investment, Cheers Financial secured funding from Better Tomorrow Ventures, which is backed by a $140 million fintech fund. The implementation of AI to automate foundational processes has allowed the startup to maintain lower operational costs. “You don’t need to build everything from the ground up,” Lian remarked. “You can let AI build the basic part, and then you optimize from that.”

The startup’s success is also attributed to strong demand from quality users, many of whom have begun opening Cheers accounts before arriving in the U.S., effectively setting the groundwork for credit building from abroad.

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Marcus Chen
Written By

At AIPressa, my work focuses on analyzing how artificial intelligence is redefining business strategies and traditional business models. I've covered everything from AI adoption in Fortune 500 companies to disruptive startups that are changing the rules of the game. My approach: understanding the real impact of AI on profitability, operational efficiency, and competitive advantage, beyond corporate hype. When I'm not writing about digital transformation, I'm probably analyzing financial reports or studying AI implementation cases that truly moved the needle in business.

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