China’s Biggest Private Sector Company Is Betting Its Future on Data
Fender benders, even minor ones, used to mean interminable hassle for Chinese drivers. One could wait hours by the roadside for an insurance inspector—then lose hours more filling out forms. Reimbursement took days, and often weeks.
In 2017, Ping An, China’s second-largest insurer and its biggest non-state-owned company by revenue, rolled out a “Superfast Onsite Investigation” system—enabling policyholders to submit claims by simply opening a smartphone app and answering a few questions. But the app’s niftiest feature offers the option to not even wait for an inspector. Instead, customers can snap photos of a damaged vehicle and send them to a Ping An computer, which can respond with a repair estimate in three minutes or less. If the customer accepts the estimate, then wancheng! (“Done!”) Ping An can transfer funds immediately.
Last year, Ping An’s customers used this feature to settle 7.3 million claims, or 62% of the total. The service saves the company more than $750 million each year by reducing bogus claims and human error. But its simplicity belies the extraordinary sophistication of the artificial intelligence and data-processing operations that make it possible.
To generate accurate estimates, Ping An matches photos of vehicle damage against a database of 25 million parts used in the 60,000 different auto makes and models sold in China. The system assesses whether those parts can be repaired or must be replaced, then calculates the cost of parts and labor in more than 140,000 garages. Ping An integrates all that information with face-, voice- and image-recognition tech and a complex matrix of anti-fraud rules. Ping An chief scientist Xiao Jing says it took a team of A.I. experts, data scientists, and insurance managers three years to design, develop, and integrate the new service. It is, he exults, “the only one of its kind in the world.”
But automated auto inspection is only one of myriad marvels that illustrate how Ping An is using A.I. and big data to transform everyday life in China. There’s also the facial-recognition technology the Shenzhen-based conglomerate uses in its consumer lending business; Ping An claims its A.I. can read 54 distinct “micro-expressions” to determine whether loan applicants are lying. Or take Ping An Healthcare and Technology, better known as Good Doctor, which offers consultations to 265 million patients registered via a mobile app—and aids physicians in diagnosing thousands of ailments. Over the past five years, Ping An has also built its own cloud and designed a suite of A.I.-driven software services to go with it—not just to support its own work but also to market services to thousands of smaller financial institutions, hospitals, and medical clients.
These products and services have a vital feature in common: They match online data, generated by China’s digitally native consumer masses, with a vast storehouse of “offline” data and insight amassed over three decades in the insurance business. Ping An believes that this offline information—which encompasses elements as disparate as business-loan default rates, symptoms of skin cancer, and the resale value of a car with sprung shocks—means that its data services are based on better data. “That’s where our advantage comes in,” says Jessica Tan, the deputy CEO who oversees Ping An’s technology companies. “We’re able to connect to the full picture.”
Such connection is central to the vision of Ping An’s hard-charging founder and CEO, Peter Ma. Ma built a massive business around an array of life, health, and property and casualty insurance. Ping An’s insurance arm now reaches 184 million customers and accounted for the bulk of the company’s $164 billion in revenue in 2018. Growth in those relatively staid industries is slowing as China’s economy matures. But they are generating the massive flows of cash and data Ping An needs to build its tech arsenal. Ping An’s leadership foresees the day when the company’s technology businesses contribute as much as half of its earnings, up from only 6% today, and compete head-to-head with pure technology plays like Alibaba Group and Tencent Holdings.
Giant financial services companies rarely double as disruptive innovators. Ping An’s very name, which means “peace and safety,” evokes warm milk and an early bedtime. Yet Ping An has already spawned a menagerie of proprietary technologies that support the group’s five key “ecosystems”: finance, health care, autos, real estate, and smart cities. Meanwhile, its online financial and health care services, some sold under its own brand and some licensed to others, now boast more than 565 million registered users.
Ping An earmarks 1% of revenue for investments in innovation. Over the past 10 years, the group has plowed more than $7 billion into research and development, and Ma has vowed to invest $15 billion more in the decade to come. That endowment has nurtured 11 technology affiliates, of which two—Good Doctor and Autohome, a platform for car buyers—are publicly traded and three are privately held “unicorns” with multibillion-dollar valuations For now, only two of those five are profitable. Even so, the combined value of the group’s tech ventures tops $70 billion. (See the “Star Pupils” sidebar.)
Paul Schulte, CEO of Hong Kong–based Schulte Research and an expert on how financial companies use technology, says that Ping An grasped the importance of A.I. and data analysis “from the beginning.” While other big Chinese companies seemed to sleepwalk past the new tools, he says, Ping An was “hyper-awake and constantly pushing.” These days, that push is only growing more forceful.
Ping An tower, the second-tallest skyscraper in China, dominates Shenzhen’s skyline, looming 118 stories over the Futian financial district. From its upper floors, executives can gaze over lesser buildings to a hill upon which stands a statue of Deng Xiaoping, the leader who steered China out of isolation and rigid centralized economic control after the death of Mao Zedong. Lee Yuansiong, the deputy CEO who heads Ping An’s insurance group, jokes that he bows to the statue every day—thanking Deng for setting China’s economy, and his employer, on the path to rapid growth.
Ping An got its start in 1988 when Ma, then a junior official at state-owned shipping company China Merchants Group, persuaded superiors to let him set up a property and casualty insurance unit. The concept of an insurance company was unfamiliar in China, but China Merchants was headquartered in Shenzhen, a special economic zone, where economic experimentation was not only tolerated but encouraged. Ping An later branched into life and health insurance, enjoying “first mover” status in those markets just as millions of Chinese people attained middle-class prosperity for the first time, driving demand; it eventually rolled out a profitable retail bank.
Beginning in the 1990s, Ping An took advantage of widening reforms to become the first Chinese financial institution in which foreign firms could own equity: Goldman Sachs and Morgan Stanley were early backers. The company eventually went public in 2004, listing in Hong Kong. (Current shareholders include three companies controlled by Thailand’s CP Group, which together held a stake of 9.19% at the end of last year. Chatchaval Jiaravanon, son of the executive chairman of CP Group, has owned Fortune since December 2018.)
Even as its customer base and revenue soared, Ping An made missteps. Efforts to expand through acquisition were particularly ill-fated. In 2008, Ping An bought a 50% stake in Brussels-based financial conglomerate Fortis, just before that company collapsed. The 2010 acquisition of Shenzhen Development Bank, a troubled commercial lender, has been slow to bear fruit.
As he grappled with those challenges, Ma marveled at the rise of Tencent and Alibaba. The rapidity with which those companies parlayed data on e-commerce and mobile payments into successful products hinted at the power inherent in Ping An’s own deep data pool. (Peter Ma shares the same surname as Alibaba cofounder Jack Ma and Tencent founder Huateng “Pony” Ma, but the three are not related.) Ma’s vision, says Jonathan Larsen, the company’s chief innovation officer, was that Ping An could combine the best of a stable finance company and a nimble tech firm—innovating and experimenting to help keep a big company growing at a steady pace.
To implement that vision, Ma has reached outside the company’s ranks and outside China itself. Jessica Tan, who joined in 2013, grew up in Singapore and earned degrees in electrical engineering and computer science from MIT. She spent 13 years at consultancy McKinsey & Co., where Ping An was a client. Her first project for Ping An also marked her first trip to mainland China. “I remember arguing with my office manager,” she says, laughing. “I really didn’t want to go.” That assignment turned into an 18-month odyssey in which Tan helped develop a major administrative campus. Her current role puts her in constant orbit between headquarters in Shenzhen, Ping An’s 32-acre tech center outside Shanghai, and Singapore to see her family.
Lee, the insurance group head, also hails from Singapore. Larsen, an Australian, held a variety of top roles at Citibank, including head of global retail banking, before joining Ping An in 2017. And Xiao, the chief scientist, is a Chinese native who joined in 2013 after stints in Silicon Valley at Seiko Epson and Microsoft. Starting at a company with a data trove the size of Ping An’s, Xiao says, was like discovering “Treasure Island.”
Comparing Ping An’s data capabilities with those of Alibaba and Tencent is a tricky proposition, given the radically different scales at which they operate. Taobao, Alibaba’s main retail marketplace, has 666 million monthly active users, while Alipay, its mobile payments platform, boasts more than a billion. Tencent’s WeChat platform draws more than a billion active users who generate an average of 45 billion messages—every day. Schulte estimates that the BAT (China’s troika of Baidu, Alibaba, and Tencent) processes at least 10 times as much data every day as Ping An has acquired in its entire existence.
But Ping An executives argue that quality matters more than quantity. The data its businesses collect is richer than that gleaned by the BAT, they claim, because it involves big-ticket transactions relating to health, wealth, and property—among the most meaningful decisions in customers’ lives.
As a case in point, Jessica Tan cites Autohome. When Ping An acquired a controlling stake in the New York–listed company from Telstra, the Australian telecom giant, in 2016, Autohome was seen as promising but unproven. Under Ping An, it has consolidated its position as China’s largest online auto-sales platform while swinging to profitability. Tan attributes the turnaround to the firm’s ability to tap into decades of Ping An data unrelated to e-commerce—millions of records about auto loans and car-insurance claims, for example. Just as important, Ping An persuaded some 14,000 auto dealers to use Autohome for sales management—generating real-time intelligence about consumer tastes. All of this information enables Autohome to target customers more precisely and offer them services like financing—and it wouldn’t have been possible, Tan says, “if I were just a pure insurer who sticks to my stuff.”
Those dealer partnerships point to one key to Ping An’s data expansion. By licensing big-data tech to other companies, the insurance giant creates a virtuous circle in which Ping An collects still more data through the relationships, enabling it to improve its models and thereby attract more clients. There are now 22 auto insurers using the “Superfast” accident-claim platform. Some 460 Chinese banks and over 1,800 other small- and medium-size financial services firms use Ping An’s OneConnect financial platform. And Ping An’s proprietary cloud lets the company scale up these offerings at relatively little expense, helping the circle grow bigger, faster.
In the same vein, Ping An has built a popular A.I.-driven model for assessing consumer credit risk. Alibaba, Tencent, and Ping An have all been granted provisional licenses to offer credit-bureau services, but Ping An’s is the favorite of financial institutions; it’s being used by about 200 banks. While Alibaba’s and Tencent’s models rely on analysis of e-commerce data to underwrite small loans for purchases by their own customers, the value of such loans rarely exceeds a few thousand yuan—a few hundred dollars. Ping An’s model “can give a small-business owner a loan for a few hundred thousand completely unsecured, no problem,” says Tan, “because we have been doing this for years.”
To support his high-flying high-tech strategy, Ma has assembled a formidable talent pool. Ping An employs more than 24,000 software engineers, 800 data scientists, and 180 A.I. specialists. The company says it has filed more than 15,000 technology patent applications. Ping An also controls a gaggle of venture and private equity funds, including the Global Voyager Fund, a $1 billion war chest launched in 2017. Larsen, who helms Voyager, says the fund focuses on early-stage ventures in fintech and health care—securing stakes in platforms or technologies Ping An has yet to develop itself.
That the stock is undervalued is a constant lament of executives, who argue that viewing Ping An solely as an insurer misses the potential of its tech ventures. Ping An shares trade at a price-to-earnings ratio of about 12—on par with mature insurers such as AXA or Allianz but a far cry from Alibaba and Tencent, which trade at 35 and 38 times earnings, respectively.
Still, some metrics are trending in the right direction. Over the past two years, a third of new customers for Ping An’s financial services have already been registered users of its Internet businesses, the company says. That suggests the tech ventures are helping agents “cross-sell” more lucrative products—for example, when people who use Autohome to buy a car wind up getting insurance from Ping An.
The company also counts its technology portfolio as a hedge against a graying workforce and a slower economy. Larsen sees a huge opportunity in health care as China’s population ages. “You’ve got higher expectation of service standards from an increasingly affluent and educated population,” he says. “You have the onset of chronic diseases—54% of males smoke, 9% of long-term smokers get lung cancer—and a host of other conditions [related to] heart disease, lack of exercise, obesity.” Ping An’s HealthKonnect platform aims to help the Chinese government, which covers about 55% of the country’s health care costs, contain this looming wave. The company is working on features to help digitize medical records, analyze health data, pay bills, and spot fraud.
Ping An’s burgeoning capacity to collect and analyze such intimate data raises complicated privacy issues. Facial recognition and “micro-expression” analysis are now standard features for companies using Ping An’s cloud. Should customers be pleased that a company that sells health insurance can calculate their body fat percentage with a face scan? Does it bother consumers that the Good Driver app—which constantly relays where they go, how fast they drive, and how smoothly they change lanes—is increasingly a mandatory download for someone buying auto insurance? And what if the company selling them that policy also knows their occupation, net worth, and health history?
Tan says Ping An has developed elaborate systems to safeguard the privacy of client data, and that data is fully anonymized before being used in modeling. But decisions about insurance and loans for individuals, of course, are anything but anonymous. Chinese culture generally doesn’t place the same value on privacy that Western culture does; in practice, that makes it likely that Ping An’s biggest innovations will remain concentrated in China for now. “We don’t have aspirations to make acquisitions overseas,” Ma recently told the Financial Times. “The Chinese market has the best growth prospects.”
Ping An is having little trouble persuading Chinese consumers to sign on. It’s doing so with the help of an old-school sales force—the 1.1 million independent agents who sell its policies and other products. Automation has affected this army too. “They basically never touch a piece of paper,” Larsen says. “Client relationship management, social network management—it’s all automated.” Still, they drive billions of dollars in sales, year after year: In emerging economies like China’s, it turns out, the killer app for wooing customers remains an actual human.
A version of this article appears in the August 2019 issue of Fortune with the headline “Ping An’s Castle Made of Data.”
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