China

Chinese microlending is getting weird and dangerous

Every app now wants to lend you money. It's driving some users into debt and foreshadows a broader crackdown.

Chinese microlending is getting weird and dangerous

Close-up of Mao Zedong's portrait on 5 Yuan RMB,10 Yuan RMB,100 Yuan RMB (China Currency).

Image: hudiemm/Getty Images

Xu Hai got the promotional ad in a text message just when he was desperate for cash. It was summer 2020, and the 37-year-old Foxconn worker from the inland Chinese province of Hunan had been unemployed for months. Xu was no stranger to microloans: he had been taking them out since 2018, first from a few national banks and then from fintech platforms like Alipay and WeChat. The pandemic had made his financial situation even worse. He needed to borrow more.

The text urged Xu to borrow directly from Meituan, a tech company that has developed from a Yelp-like app to a mammoth corporation offering food delivery, bike-sharing, ride-hauling and more.

Xu accepted the offer because he needed to pay back the other loans he'd taken on. And Meituan was not the only place he turned. Now, Xu owes money to eight microlenders, five of which are household names in Chinese tech: Alipay, WeChat, Meituan, 360 and Xiaomi. These days, seemingly every Chinese app, whatever its original purpose, also pushes to lend users money. "Weibo tells me it can lend me money; the delivery app tells me it can lend me money; and now even the photo editing app tells me it can lend me money," wrote one Weibo user last month. "I have 32 apps on my phone. Probably 30 of them have turned into microlending apps."

Xu is now unable to climb out of debt and is battling depression.

Over the past year, non-fintech-turned-fintech apps have come under intense scrutiny by the Chinese public and the state. There's a growing concern they have tricked young people into overspending and pushed the overall amount of consumer debt to a dangerous level. The Chinese government proposed new rules in November to ramp up regulation over online microloans. Even though the rules are not official yet, their forecasted effects have already caused the suspension of Ant Group's blockbuster IPO. When they become official, they're almost certain to put a brake on tech companies' lending binge.

"China is the first large country where technology companies have turned into large financial intermediaries," Sampath Sharma Nariyanuri, a fintech analyst at S&P Global Market Intelligence, told Protocol.

A brief history of microlending

China's major tech players have been operating microlending services for years; it's one direct way to monetize a massive user base. For payment apps like Alipay and WeChat, it's a natural fit. In late 2014, Alibaba affiliate Alipay released Huabei, an online credit card-like service that allowed users to buy items on Alibaba's ecommerce platforms using credit. Ten months later, the company released another service, Jiebei, which offered unsecured microloans that could be used anywhere. The two products became popular almost instantly.

But it's gotten bewildering as other apps, many totally unrelated to fintech, have joined the game. Of the 20 most commonly used apps in China — ranging from photo editing to file sharing, from maps to streaming platforms — all have some kind of in-app loan services, according to Chinese tech site iFanr.

The growth of Chinese fintech platforms really turbocharged around 2015, said David Yin, vice president and senior analyst at Moody's financial institutions group. "Financial innovation was encouraged at that time, with very loose regulatory requirements," he told Protocol.

Things quickly got weird as a jumble of tech companies that didn't work in finance joined the party. Tencent and Baidu launched their microlending service in 2015; JD, the ecommerce platform, in 2016. In the years since, hardware manufacturers like Xiaomi and (non-fintech) software companies like Weibo, Meituan and ByteDance all rolled out their own microlending products. They had good commercial reasons for doing so: Offering microloans can attract new users, create a new stream of revenue and reduce fees to credit card issuers for transactions on the platform.

But it was the lack of traditional banking services that made it possible in the first place.

"The low penetration of traditional banking services provided an opportunity for the tech companies to step up and meet customers' credit needs," Sharma Nariyanuri said. For the generation that grew up with smartphones, going to an online credit service like Jiebei is more natural than applying for a credit card.

Caveat emptor

It's now easier to count the major tech players that don't offer microloans than to count those that do.

With so many options on the market, they have to compete for attention, with predictably annoying and dangerous effects.

Weibo users complain the app is constantly promoting its microlending service through mobile ads with only a tiny tag signifying they're advertisements. "Even if you are in urgent need of money, you shouldn't go to illegal lenders! Come to Sina's official lending services," reads one of the posts. That ad also boasts that the maximum loan is about $30,000, with daily interest rates as low as 0.03% — that sounds low, but isn't when compounded over the course of months or years. Many lenders, including Weibo and Meituan, have been accused of false advertising: Users complain they were tricked into starting a service with no knowledge of processing fees. After all fees, the real annual interest rate is often around or even higher than 36%, the maximum rate allowed by Chinese law. There are countless complaints on social media about debtors being bombarded with calls, texts and WeChat messages, some even sent to their colleagues and friends, pressing them to pay loans back.

Financial regulators have been slow to address these issues, partly because the Chinese state was previously preoccupied with systemic risk from (unregulated) peer-to-peer lending services.

But now microlending from big tech has their full attention. During a December press conference, the China Banking and Insurance Regulatory Commission laid out the risks posed by fintech platforms. "There exist problems like unsound corporate management, profiteering off data monopoly, encouraging over-borrowing and overleveraging," a spokesperson said. The regulator also said it would conduct more inspections of individual platforms.

It is not clear when new rules aimed at cutting microlending down to size will take effect, or how tech companies will respond. There could be workarounds, particularly for companies that can obtain licenses to operate "consumer finance" businesses, an area the new rules don't touch.

But it's clear the era of loose fintech regulations is over. Online lending "will be subject to a similar regulatory framework as that for traditional financial institutions," Yin said. When that day comes, some beloved Chinese apps may have to turn their attention away from pushing loans, and go back to whatever they do best.

Fintech

Judge Zia Faruqui is trying to teach you crypto, one ‘SNL’ reference at a time

His decisions on major cryptocurrency cases have quoted "The Big Lebowski," "SNL," and "Dr. Strangelove." That’s because he wants you — yes, you — to read them.

The ways Zia Faruqui (right) has weighed on cases that have come before him can give lawyers clues as to what legal frameworks will pass muster.

Photo: Carolyn Van Houten/The Washington Post via Getty Images

“Cryptocurrency and related software analytics tools are ‘The wave of the future, Dude. One hundred percent electronic.’”

That’s not a quote from "The Big Lebowski" — at least, not directly. It’s a quote from a Washington, D.C., district court memorandum opinion on the role cryptocurrency analytics tools can play in government investigations. The author is Magistrate Judge Zia Faruqui.

Keep Reading Show less
Veronica Irwin

Veronica Irwin (@vronirwin) is a San Francisco-based reporter at Protocol covering fintech. Previously she was at the San Francisco Examiner, covering tech from a hyper-local angle. Before that, her byline was featured in SF Weekly, The Nation, Techworker, Ms. Magazine and The Frisc.

The financial technology transformation is driving competition, creating consumer choice, and shaping the future of finance. Hear from seven fintech leaders who are reshaping the future of finance, and join the inaugural Financial Technology Association Fintech Summit to learn more.

Keep Reading Show less
FTA
The Financial Technology Association (FTA) represents industry leaders shaping the future of finance. We champion the power of technology-centered financial services and advocate for the modernization of financial regulation to support inclusion and responsible innovation.
Enterprise

AWS CEO: The cloud isn’t just about technology

As AWS preps for its annual re:Invent conference, Adam Selipsky talks product strategy, support for hybrid environments, and the value of the cloud in uncertain economic times.

Photo: Noah Berger/Getty Images for Amazon Web Services

AWS is gearing up for re:Invent, its annual cloud computing conference where announcements this year are expected to focus on its end-to-end data strategy and delivering new industry-specific services.

It will be the second re:Invent with CEO Adam Selipsky as leader of the industry’s largest cloud provider after his return last year to AWS from data visualization company Tableau Software.

Keep Reading Show less
Donna Goodison

Donna Goodison (@dgoodison) is Protocol's senior reporter focusing on enterprise infrastructure technology, from the 'Big 3' cloud computing providers to data centers. She previously covered the public cloud at CRN after 15 years as a business reporter for the Boston Herald. Based in Massachusetts, she also has worked as a Boston Globe freelancer, business reporter at the Boston Business Journal and real estate reporter at Banker & Tradesman after toiling at weekly newspapers.

Image: Protocol

We launched Protocol in February 2020 to cover the evolving power center of tech. It is with deep sadness that just under three years later, we are winding down the publication.

As of today, we will not publish any more stories. All of our newsletters, apart from our flagship, Source Code, will no longer be sent. Source Code will be published and sent for the next few weeks, but it will also close down in December.

Keep Reading Show less
Bennett Richardson

Bennett Richardson ( @bennettrich) is the president of Protocol. Prior to joining Protocol in 2019, Bennett was executive director of global strategic partnerships at POLITICO, where he led strategic growth efforts including POLITICO's European expansion in Brussels and POLITICO's creative agency POLITICO Focus during his six years with the company. Prior to POLITICO, Bennett was co-founder and CMO of Hinge, the mobile dating company recently acquired by Match Group. Bennett began his career in digital and social brand marketing working with major brands across tech, energy, and health care at leading marketing and communications agencies including Edelman and GMMB. Bennett is originally from Portland, Maine, and received his bachelor's degree from Colgate University.

Enterprise

Why large enterprises struggle to find suitable platforms for MLops

As companies expand their use of AI beyond running just a few machine learning models, and as larger enterprises go from deploying hundreds of models to thousands and even millions of models, ML practitioners say that they have yet to find what they need from prepackaged MLops systems.

As companies expand their use of AI beyond running just a few machine learning models, ML practitioners say that they have yet to find what they need from prepackaged MLops systems.

Photo: artpartner-images via Getty Images

On any given day, Lily AI runs hundreds of machine learning models using computer vision and natural language processing that are customized for its retail and ecommerce clients to make website product recommendations, forecast demand, and plan merchandising. But this spring when the company was in the market for a machine learning operations platform to manage its expanding model roster, it wasn’t easy to find a suitable off-the-shelf system that could handle such a large number of models in deployment while also meeting other criteria.

Some MLops platforms are not well-suited for maintaining even more than 10 machine learning models when it comes to keeping track of data, navigating their user interfaces, or reporting capabilities, Matthew Nokleby, machine learning manager for Lily AI’s product intelligence team, told Protocol earlier this year. “The duct tape starts to show,” he said.

Keep Reading Show less
Kate Kaye

Kate Kaye is an award-winning multimedia reporter digging deep and telling print, digital and audio stories. She covers AI and data for Protocol. Her reporting on AI and tech ethics issues has been published in OneZero, Fast Company, MIT Technology Review, CityLab, Ad Age and Digiday and heard on NPR. Kate is the creator of RedTailMedia.org and is the author of "Campaign '08: A Turning Point for Digital Media," a book about how the 2008 presidential campaigns used digital media and data.

Latest Stories
Bulletins