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A Car Insurance Claim Estimate Before the Tow Truck Is Called

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On a typical day, about 80,000 American drivers have accidents serious enough to warrant calling their insurers. After the initial shock comes a predictable sequence of worries: Was anyone hurt? Am I at fault? The driver’s first call is often to the insurance company, which leads to the next questions: How long will it take to get an estimate, get my car into the shop and then get it back on the road?

The time it takes to settle auto insurance claims is being shortened, and the accuracy of initial estimates is improving, because U.S. insurers now use artificial intelligence to generate repair estimates.

The latest technology powered by A.I. is much different from the “virtual claim” you might have filed after your last fender-bender. About five years ago, photo-based estimates became increasingly common. Insurance companies sometimes had customers download an app that helped them provide consistent photos, but some insurers just told customers to attach pictures to an email.

Insurance companies liked photo-based estimates because appraisers who could average only four in-person estimates a day could complete as many as 15 virtual ones by staying in the office and scrolling through customer-supplied photos on a computer monitor. However, once damaged cars got into body shops, those estimates proved far less accurate than those done in person. Insurance companies were bedeviled by costs that surpassed estimates — called claim supplements — sometimes running as much as 50 percent higher. Customers were frustrated by unexpected delays. And body shops hated being caught in the middle.

That was then. Now, customers can download phone apps through their insurers to guide them through the process of taking and uploading photos that can be evaluated by A.I., producing a near-instantaneous damage estimate. The apps are not yet in wide use in the United States, but their time is coming.

The algorithms are trained in image classification, and they identify damage and hand off the claims to companies like Mitchell International, based in San Diego, that price out parts and calculate labor costs. The best algorithms already provide estimates in a few seconds that are as accurate as those produced by experienced human estimators. The pandemic has made A.I.-powered estimating even more attractive because the technology reduces or even eliminates the need for face-to-face interaction between drivers and insurance adjusters.

Credit…Tractable

By eliminating the need to make appointments with appraisers or make a separate trip to the body shop for an initial estimate, these apps take days off the “cycle time” — how long it takes to get customers back into their cars.

Algorithms also learn and adapt more quickly than human experts. A simple bumper replacement is not necessarily simple anymore, because new bumpers often have expensive integrated sensors, like the ones that warn drivers if they’re backing up too close to another car when parallel parking. As a result, those claim supplements are increasing.

One of the leaders in this “insuretech” market is Tractable, a company based in London that was founded in 2014 by the entrepreneur Adrien Cohen and two computer vision experts, Alex Dalyac and Razvan Ranca. Since then, Tractable has received more than $50 million in venture capital funding and grown to over 100 employees in London, New York and Tokyo. Major insurers in Europe and Asia have used Tractable’s A.I. to settle more than $1 billion in claims.

Mr. Dalyac joined Tractable from Imperial College London, where he had led the computing department’s first industrial application of “deep learning.” That’s the approach the company used to train an algorithm to interpret auto damage — a task that had previously been performed only by skilled humans.

“These algorithms are very different to how people used to do computer vision, because you actually get the algorithm to figure out the right patterns in the object,” Mr. Dalyac said. “Instead of telling the A.I., ‘This is what a front bumper looks like; look for a corner like this and pixels like that,’ you feed the algorithm millions of images. Some contain a front bumper and some don’t. On a rainy day, a dark day, or a sunny one; an undamaged bumper; or one that needs three hours of repair. And the algorithm itself figures out the best combinations of pixel patterns that give it the most accuracy. It’s kind of magical, but it’s very data hungry.”

To date, Tractable has fed its algorithm about 10 million photos of damaged cars, most of which were taken in body shops and submitted to insurers along with repair estimates.

ImageApps like Tractable’s are not yet in wide use in the United States, but the company expects a big insurer to get on board soon.
Credit…Tractable

“Domestic carriers have historically been slow to adopt new technology,” said Jimmy Spears, an insurance industry veteran who is now Tractable’s head of North American automotive operations. One hurdle this technology faces in the United States, compared with other countries, is that every state regulates its own insurance sector.

“But Covid-19 has had a tremendous impact,” Mr. Spears said. “My days are filled with meetings and product demonstrations, and we have a number of proofs of concept in play with top-10 insurers.”

As insurance companies have pulled their employees out of the field, the use of virtual estimates has jumped. CCC Information Services, a Chicago company that markets its own A.I.-enhanced Quick Estimate app to insurers, recently reported a 125 percent increase in app use since March — even though traffic levels and accident numbers plunged when states locked down.

Even before the pandemic, major U.S. carriers were exploring the use of A.I. to speed claims settlement. Liberty Mutual’s in-house technology incubator, Solaria Labs, began work on an A.I. estimating algorithm in 2018. The company now uses it to give appraisers a head start on estimates.

USAA took a different approach. Rather than develop its own algorithm, it teamed with Google. Customers can upload photos of their damaged cars for analysis by Google Cloud’s Vision API. That damage assessment is then handed off to another partner, Mitchell International, which also uses A.I. to prepare a parts and labor estimate.

“Today, we send those estimates back to our appraisers because we’re still training the system,” said the company’s chief claims officer, Sean Burgess. “But in the near future, you won’t need that step. We’re going to take the process from days or weeks to minutes.”

That’s the approach Tractable has taken, too. “As comfort with the A.I.’s results is gained,” Mr. Dalyac said, “this human quality check is gradually reduced and removed, and so the proportion of A.I. touchless cases increases.”

Drivers insured by Admiral Seguro, a major Spanish auto insurer that uses Tractable’s tech, can already upload photos and completely resolve some claims — right down to receiving an offer of payment — in minutes on the first phone call.

How soon will American drivers have access to nearly instant claim settlement? Every insurer has to make its own decision about when it is ready to drop that last human quality check, but the day will come. Tractable is confident that it will soon be operating here. “We are getting pretty close,” Mr. Dalyac said. “In the next few quarters, there’s going to be an announcement of a very big American carrier — a household name — that’s going to be doing this.”

Although Mr. Burgess said USAA customers would always have the option of a human estimate, it recently filed a trademark on the phrase “Flash Estimate” and expects to bring its own A.I. claim settlement technology to market in 2021 or 2022.

The rise of A.I. could be bad news for thousands of people working at insurance companies, but Mr. Dalyac bristles at the suggestion that Tractable will necessarily put those people out of work. “The goal of our technology is to take care of the repetitive, straightforward cases so they can focus on the complex ones, or on providing better customer service,” he said. “Because sometimes when you’ve had an accident, you’re pretty shaken and want additional touch.”

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The Trump campaign celebrated a growth record that Democrats downplayed.

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The White House celebrated economic growth numbers for the third quarter released on Thursday, even as Joseph R. Biden Jr.’s presidential campaign sought to throw cold water on the report — the last major data release leading up to the Nov. 3 election — and warned that the economic recovery was losing steam.

The economy grew at a record pace last quarter, but the upswing was a partial bounce-back after an enormous decline and left the economy smaller than it was before the pandemic. The White House took no notice of those glum caveats.

“This record economic growth is absolute validation of President Trump’s policies, which create jobs and opportunities for Americans in every corner of the country,” Mr. Trump’s re-election campaign said in a statement, highlighting a rebound of 33.1 percent at an annualized rate. Mr. Trump heralded the data on Twitter, posting that he was “so glad” that the number had come out before Election Day.

The annualized rate that the White House emphasized extrapolates growth numbers as if the current pace held up for a year, and risks overstating big swings. Because the economy’s growth has been so volatile amid the pandemic, economists have urged focusing on quarterly numbers.

Those showed a 7.4 percent gain in the third quarter. That rebound, by far the biggest since reliable statistics began after World War II, still leaves the economy short of its pre-pandemic levels. The pace of recovery has also slowed, and now coronavirus cases are rising again across much of the United States, raising the prospect of further pullback.

“The recovery is stalling out, thanks to Trump’s refusal to have a serious plan to deal with Covid or to pass a new economic relief plan for workers, small businesses and communities,” Mr. Biden’s campaign said in a release ahead of Thursday’s report. The rebound was widely expected, and the campaign characterized it as “a partial return from a catastrophic hit.”

Economists have warned that the recovery could face serious roadblocks ahead. Temporary measures meant to shore up households and businesses — including unemployment insurance supplements and forgivable loans — have run dry. Swaths of the service sector remain shut down as the virus continues to spread, and job losses that were temporary are increasingly turning permanent.

“With coronavirus infections hitting a record high in recent days and any additional fiscal stimulus unlikely to arrive until, at the earliest, the start of next year, further progress will be much slower,” Paul Ashworth, chief United States economist at Capital Economics, wrote in a note following the report.

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Black and Hispanic workers, especially women, lag in the U.S. economic recovery.

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The surge in economic output in the third quarter set a record, but the recovery isn’t reaching everyone.

Economists have long warned that aggregate statistics like gross domestic product can obscure important differences beneath the surface. In the aftermath of the last recession, for example, G.D.P. returned to its previous level in early 2011, even as poverty rates remained high and the unemployment rate for Black Americans was above 15 percent.

Aggregate statistics could be even more misleading during the current crisis. The job losses in the initial months of the pandemic disproportionately struck low-wage service workers, many of them Black and Hispanic women. Service-sector jobs have been slow to return, while school closings are keeping many parents, especially mothers, from returning to work. Nearly half a million Hispanic women have left the labor force over the last three months.

“If we’re thinking that the economy is recovering completely and uniformly, that is simply not the case,” said Michelle Holder, an economist at John Jay College in New York. “This rebound is unevenly distributed along racial and gender lines.”

The G.D.P. report released Thursday doesn’t break down the data by race, sex or income. But other sources make the disparities clear. A pair of studies by researchers at the Urban Institute released this week found that Black and Hispanic adults were more likely to have lost jobs or income since March, and were twice as likely as white adults to experience food insecurity in September.

The financial impact of the pandemic hit many of the families that were least able to afford it, even as white-collar workers were largely spared, said Michael Karpman, an Urban Institute researcher and one of the studies’ authors.

“A lot of people who were already in a precarious position before the pandemic are now in worse shape, whereas people who were better off have generally been faring better financially,” he said.

Federal relief programs, such as expanded unemployment benefits, helped offset the damage for many families in the first months of the pandemic. But those programs have mostly ended, and talks to revive them have stalled in Washington. With virus cases surging in much of the country, Mr. Karpman warned, the economic toll could increase.

“There could be a lot more hardship coming up this winter if there’s not more relief from Congress, with the impact falling disproportionately on Black and Hispanic workers and their families,” he said.

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Ant Challenged Beijing and Prospered. Now It Toes the Line.

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As Jack Ma of Alibaba helped turn China into the world’s biggest e-commerce market over the past two decades, he was also vowing to pull off a more audacious transformation.

“If the banks don’t change, we’ll change the banks,” he said in 2008, decrying how hard it was for small businesses in China to borrow from government-run lenders.

“The financial industry needs disrupters,” he told People’s Daily, the official Communist Party newspaper, a few years later. His goal, he said, was to make banks and other state-owned enterprises “feel unwell.”

The scope of Mr. Ma’s success is becoming clearer. The vehicle for his financial-technology ambitions, an Alibaba spinoff called Ant Group, is preparing for the largest initial public offering on record. Ant is set to raise $34 billion by selling its shares to the public in Hong Kong and Shanghai, according to stock exchange documents released on Monday. After the listing, Ant would be worth around $310 billion, much more than many global banks.

The company is going public not as a scrappy upstart, but as a leviathan deeply dependent on the good will of the government Mr. Ma once relished prodding.

More than 730 million people use Ant’s Alipay app every month to pay for lunch, invest their savings and shop on credit. Yet Alipay’s size and importance have made it an inevitable target for China’s regulators, which have already brought its business to heel in certain areas.

These days, Ant talks mostly about creating partnerships with big banks, not disrupting or supplanting them. Several government-owned funds and institutions are Ant shareholders and stand to profit handsomely from the public offering.

The question now is how much higher Ant can fly without provoking the Chinese authorities into clipping its wings further.

Excitable investors see Ant as a buzzy internet innovator. The risk is that it becomes more like a heavily regulated “financial digital utility,” said Fraser Howie, the co-author of “Red Capitalism: The Fragile Financial Foundation of China’s Extraordinary Rise.”

“Utility stocks, as far as I remember, were not the ones to be seen as the most exciting,” Mr. Howie said.

Ant declined to comment, citing the quiet period demanded by regulators before its share sale.

The company has played give-and-take with Beijing for years. As smartphone payments became ubiquitous in China, Ant found itself managing huge piles of money in Alipay users’ virtual wallets. The central bank made it park those funds in special accounts where they would earn minimal interest.

After people piled into an easy-to-use investment fund inside Alipay, the government forced the fund to shed risk and lower returns. Regulators curbed a plan to use Alipay data as the basis for a credit-scoring system akin to Americans’ FICO scores.

China’s Supreme Court this summer capped interest rates for consumer loans, though it was unclear how the ceiling would apply to Ant. The central bank is preparing a new virtual currency that could compete against Alipay and another digital wallet, the messaging app WeChat, as an everyday payment tool.

Ant has learned ways of keeping the authorities on its side. Mr. Ma once boasted at the World Economic Forum in Davos, Switzerland, about never taking money from the Chinese government. Today, funds associated with China’s social security system, its sovereign wealth fund, a state-owned life insurance company and the national postal carrier hold stakes in Ant. The I.P.O. is likely to increase the value of their holdings considerably.

“That’s how the state gets its payoff,” Mr. Howie said. With Ant, he said, “the line between state-owned enterprise and private enterprise is highly, highly blurred.”

China, in less than two generations, went from having a state-planned financial system to being at the global vanguard of internet finance, with trillions of dollars in transactions being made on mobile devices each year. Alipay had a lot to do with it.

Alibaba created the service in the early 2000s to hold payments for online purchases in escrow. Its broader usefulness quickly became clear in a country that mostly missed out on the credit card era. Features were added and users piled in. It became impossible for regulators and banks not to see the app as a threat.

ImageAnt Group’s headquarters in Hangzhou, China.
Credit…Alex Plavevski/EPA, via Shutterstock

A big test came when Ant began making an offer to Alipay users: Park your money in a section of the app called Yu’ebao, which means “leftover treasure,” and we will pay you more than the low rates fixed by the government at banks.

People could invest as much or as little as they wanted, making them feel like they were putting their pocket change to use. Yu’ebao was a hit, becoming one of the world’s largest money market funds.

The banks were terrified. One commentator for a state broadcaster called the fund a “vampire” and a “parasite.”

Still, “all the main regulators remained unanimous in saying that this was a positive thing for the Chinese financial system,” said Martin Chorzempa, a research fellow at the Peterson Institute for International Economics in Washington.

“If you can’t actually reform the banks,” Mr. Chorzempa said, “you can inject more competition.”

But then came worries about shadowy, unregulated corners of finance and the dangers they posed to the wider economy. Today, Chinese regulators are tightening supervision of financial holding companies, Ant included. Beijing has kept close watch on the financial instruments that small lenders create out of their consumer loans and sell to investors. Such securities help Ant fund some of its lending. But they also amplify the blowup if too many of those loans aren’t repaid.

“Those kinds of derivative products are something the government is really concerned about,” said Tian X. Hou, founder of the research firm TH Data Capital. Given Ant’s size, she said, “the government should be concerned.”

The broader worry for China is about growing levels of household debt. Beijing wants to cultivate a consumer economy, but excessive borrowing could eventually weigh on people’s spending power. The names of two of Alipay’s popular credit functions, Huabei and Jiebei, are jaunty invitations to spend and borrow.

Huang Ling, 22, started using Huabei when she was in high school. At the time, she didn’t qualify for a credit card. With Huabei’s help, she bought a drone, a scooter, a laptop and more.

The credit line made her feel rich. It also made her realize that if she actually wanted to be rich, she had to get busy.

“Living beyond my means forced me to work harder,” Ms. Huang said.

First, she opened a clothing shop in her hometown, Nanchang, in southeastern China. Then she started an advertising company in the inland metropolis of Chongqing. When the business needed cash, she borrowed from Jiebei.

Online shopping became a way to soothe daily anxieties, and Ms. Huang sometimes racked up thousands of dollars in Huabei bills, which only made her even more anxious. When the pandemic slammed her business, she started falling behind on her payments. That cast her into a deep depression.

Finally, early this month, with her parents’ help, she paid off her debts and closed her Huabei and Jiebei accounts. She felt “elated,” she said.

China’s recent troubles with freewheeling online loan platforms have put the government under pressure to protect ordinary borrowers.

Ant is helped by the fact that its business lines up with many of the Chinese leadership’s priorities: encouraging entrepreneurship and financial inclusion, and expanding the middle class. This year, the company helped the eastern city of Hangzhou, where it is based, set up an early version of the government’s app-based system for dictating coronavirus quarantines.

Such coziness is bound to raise hackles overseas. In Washington, Chinese tech companies that are seen as close to the government are radioactive.

In January 2017, Eric Jing, then Ant’s chief executive, said the company aimed to be serving two billion users worldwide within a decade. Shortly after, Ant announced that it was acquiring the money transfer company MoneyGram to increase its U.S. footprint. By the following January, the deal was dead, thwarted by data security concerns.

More recently, top officials in the Trump administration have discussed whether to place Ant Group on the so-called entity list, which prohibits foreign companies from purchasing American products. Officials from the State Department have suggested that an interagency committee, which also includes officials from the departments of defense, commerce and energy, review Ant for the potential entity listing, according to three people familiar with the matter.

Ant does not talk much anymore about expanding in the United States.

Ana Swanson contributed reporting.

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