Of China’s 1.4 billion people, the central bank database covers 800 million, of which roughly 300 million people had credit records. That leaves about 500 million people who can’t borrow money from traditional financial organizations.
China Rapid Finance is aiming to address the issue.
The Company aims to bring consumer credit to the nation’s emerging middle class and is defining a new category of customers.
Many of these underserved consumers have stable incomes, are connected to the internet and love to shop online. The Company defines this group as China’s Emerging Middle-class Mobile Active consumers, or EMMA. This group, which is typically urban, well-educated, and hooked on smartphones, is projected to become the consumer mainstream in China, providing a huge market potential for CRF in coming years.
These hundreds of millions of consumers in China have generated a tremendous amount of data, even if they lack a proper credit history. Being heavy Web users means EMMAs have a large data footprint from Web search, social networks, payments and online shopping.
CRF partners with some of China’s major Internet platforms to build multiple channels of data that may capture nearly all of the nation’s Web users. By building a multi-channel, multi-platform product chain, the Company can provide EMMAs with consumption loans in fast, affordable, and convenient ways.
The products launched by CRF and its Big Data cooperative partners are targeting the huge consumption loan market in China.
According to an iResearch study, China’s consumption loan market will grow at an annual rate of 19.5% from 2014 to 2019, when it will reach 37.4 trillion yuan. As of December 31, 2014, the consumption credit penetration as a percentage of GDP in China was 5%, while the ratio was near 20% in the U.S., reflecting huge market potential in China.
CRF is seeking cooperation with more partners to develop additional channels to reach the entire EMMA population. How to leverage such data for credit decisions is a huge challenge.
CRF has applied its unique technology to solve the problem. The company uses Big Data algorithms to analyze the unstructured data it acquires through its multichannel strategy. CRF’s predictive selection technology and automated decisioning technology are able to identify a pre-selected list of qualified consumers.
China Rapid Finance had provided more than 4.7 million loans to Chinese consumers from inception to the end of 2015, making it the industry leader as measured by the total number of loans.
With a Big Data lab in Silicon Valley, China Rapid Finance refines and develops its core technologies such as predictive selection and automated decisioning, which are based on artificial intelligence and machine learning algorithms. These advanced technologies allow China Rapid Finance to accomplish large-scale, low-cost acquisition of quality borrowers.
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