The Chinese fintech ecosystem is the largest and most diversified in the emerging markets world. In this series of reports, we map the progress of China’s fintechs and examine their strategies and plans. As one of the more mature markets, the country’s fintechs can also provide a blueprint for where other EMs may follow.
Our database of over 650 Chinese fintechs within 3,400 emerging market firms helps us position China in a broader EM context. The main factors Chinese fintechs credit for their success to date include innovative service offerings, extensive distribution networks, and user-friendly platforms. They plan to introduce new products/services, increase operational efficiency, and enter new customer segments. Planned innovations focus on artificial intelligence, easier customer onboarding, and machine learning.
Our Ultimate Guide to China fintech gives a more comprehensive overview of the sector and can be accessed here.
Key success factors for Chinese fintechs: innovation, distribution network, user-friendliness
The factors China fintechs credit most for their success include innovative service offerings, extensive distribution networks, and user-friendly platforms. In contrast to fintechs in other emerging markets, those in China are more likely to cite distribution networks and strong shareholders as success factors, and less likely to mention seamless execution, funding access, and operational efficiency.
In our previous survey, Chinese fintechs cited innovative service offerings, funding access, and competitive product prices as their top success factors. While the importance attached to funding access has declined significantly, extensive distribution networks, strong management, and well-connected/financially strong shareholders have gained in relevance.
Innovative service offerings
Innovation is a key pillar for fintech success. It can, for example, allow fintechs to improve their service offerings and, hence, enhance the consumer experience. Chinese firms that are striving to innovate include Leapstack (insurtech) and Kingstar (investech).
Extensive distribution network
Fintechs benefit from an extensive distribution network if they have developed significant partnerships across different markets and have built a broad agent network. Chinese firms that attribute an extensive distribution network as a success factor include ZhongAn Insurance (insurtech) and WeBank (digital banking).
Firms need to create an easy-to-use, seamless interface. Chinese fintechs citing this as a success factor include Alipay (payments) and Clustar AI (fintech software solutions).
Future plans: New products and customer segments, operational efficiency
Chinese fintechs’ top strategic priorities are introducing new products/services, increasing operational efficiency and entering new customer segments. Relative to other emerging markets, Chinese fintechs are less focused on exploring new markets, which may reflect the large size of the domestic revenue pool. However, they are more likely to leverage strategic partnerships than fintechs in other emerging markets.
In contrast to our previous survey, the strategic priorities of Chinese fintechs have shifted from enhancing management expertise and increasing technological investment to introducing new products/services and entering new customer segments. In addition, Chinese fintechs no longer prioritise moving to new markets.
Introducing new products and services
Fintechs tend to expand their service offerings to new products when they achieve a certain scale in their primary offering. For example, payments fintechs often look to expand into lending or investments; this can help to lift their share of wallet and boost financial returns. Chinese fintechs that plan to launch new products include Suning Finance (lending) and Bitmain (blockchain).
Boosting operational efficiency
Operational efficiency allows companies to boost their bottom lines and also facilitates competitive pricing, thereby growing the addressable market. Chinese fintechs targeting better operating efficiency include Lufax (lending) and Du Xiaoman Financial (lending).
Entering new customer segments
China’s large population is extremely diverse in terms of geography, age and income. Therefore, it makes sense for fintechs to modify their existing offerings to appeal to a broader range of customer segments. Firms planning to enter new customer segments include Tigerobo (fintech software solutions) and G-banker (investech).
Targeted fintech innovations: AI, easier customer onboarding, machine learning
The top three areas where Chinese fintechs are targeting innovation efforts include artificial intelligence, customer onboarding and machine learning. In contrast to other emerging markets, Chinese fintechs are less keen on developing chatbots/virtual assistants, using technology to reduce defaults and cloud technology. However, they are more focused on machine learning and augmented reality than other EM fintechs.
In our previous survey, chatbots/virtual assistants, blockchain technology, and easier customer onboarding topped the targeted innovation areas for Chinese fintechs. Cloud technology is also now less of a focus than in the previous survey. These changes may help investors in other, less mature EM fintech markets track where future development efforts could be directed.
Artificial intelligence for predictive analysis
Artificial intelligence can be utilised by fintechs in many ways, for example, predictive analysis to assess future outcomes and boost risk management. Other potential uses include improving operating efficiency or enhancing customer engagement levels. Chinese fintechs targeting greater use of AI include WeShare (lending) and Ways (fintech software solutions).
Using technology to ease customer onboarding
Partly for regulatory reasons, customer onboarding has traditionally tended to be a lengthy process. Any complexities or difficulties in customer onboarding can lead to bad first impressions, resulting in lower business volume and less customer loyalty. For these reasons, Chinese fintechs such as Ontology (blockchain) and Yeahka (payments) are working to improve the process.
Machine learning, a subfield of AI, enables firms to learn from and improve data analysis. For example, through access to traditional and non-traditional datasets, machine learning can enable lending firms to better evaluate the creditworthiness of financially-excluded individuals. ML can help to prevent fraudulent activities or to enrich the user experience via virtual assistants that become smarter over time.
ML models can also help in wealth management, through real-time data monitoring to predict movements in equity prices. Chinese fintechs wishing to innovate in this area include Xtransfer (lending) and BitOcean (blockchain).
The author thanks Rohit Kumar, Rabail Adwani and Gaurav Kumar for their assistance with this report.