Ant Financial announces a developer initiative in 2016.

If you get into a car accident in China in the near future, you'll be able to pull out your smartphone, take a photo, and file an insurance claim with an AI system.

That system, from Ant Financial, will automatically decide how serious the ding was and process the claim accordingly with an insurer. It shows how the company—which already operates a hugely successful smartphone payments business in China—aims to upend many areas of personal finance using machine learning and AI.

The e-commerce giant Alibaba created Ant in 2014 to operate Alipay, a ubiquitous mobile payments service in China. If you have visited the country in recent years, then you have probably seen people paying for meals, taxi rides, and a whole lot more by scanning a code with the Alipay app. The system is far more popular than the wireless payments systems offered in the U.S. by Apple, Google, and others. The company boasts more than 450 million active users compared to about 12 million for Apple Pay.

Ant’s progress will be significant to the future of the financial industry beyond China, including in the U.S., where the company is expanding its interests. The company’s approach goes around existing institutions to target individuals and small businesses who lack access to conventional financial services. Ant said in April of this year that it is buying the U.S. money-transfer service MoneyGram for $880 million. The deal is subject to regulatory approval and should close in the second half of this year. The company could well apply the technologies it is developing to its overseas subsidiaries. A spokesperson for the company says it hasn’t brought Alipay to the U.S. because existing financial systems provide less of an opportunity.

Yuan (Alan) Qi, a vice president and chief data scientist at Ant, says the company’s AI research is shaping its growth. “AI is being used in almost every corner of Ant’s business,” he says. “We use it to optimize the business, and to generate new products.”

The accident-processing system is a good example of how advances in AI can flip an existing system on its head, Qi says. It has become possible to automate this kind of image processing in recent years using a machine-learning technology known as deep learning. By feeding thousands of example images into a very large neural network, it is possible to train it to recognize things that even a human may struggle to spot (see “10 Breakthrough Technologies 2013: Deep Learning”).