创业初始，Credit Karma为6000万人免费提供了信用评分，这种创举可谓颠覆了整个付费信用报告市场。而今年，Credit Karma又准备免费提供纳税申报服务，这着实也让89亿美元的报税行业吃了一惊。H&R Block和IBM之前曾大力宣传其人工智能报税服务。
用户提供个人信息（姓名、地址、电话、社保号码）以获得信用分。如果信用达标，用户将会得到获取最优惠信用卡、个人贷款和汽车贷款产品的机会。此外，用户还可以借助Credit Karma申报联邦税。而所有这些服务都是免费的。Credit Karma从信用卡和贷款提供商那收取佣金，并且承诺永远不会向消费者收钱。
然而，Credit Karma虽然看似只是为用户提供了免费的午餐，但其实得到的用户数据价值却远超服务费用本身。通过Credit Karma独特的窄域人工智能(ANI)分析模型，注意不是普通的人工智能技术，Credit Karma可以在20毫秒之内就为用户提供精确到分钟的金融决策建议。
Graciano表示，Credit Karma在生产、具体分析、数据科学和建模、在线预测等方方面面都需要用到数据。一个数据串大小是210TB，他们公司的数据每天增长大于1TB。 （每月用户数增加1-200万。）另外，每个月Graciano和他的团队会创建1000个新模型，这些模型考虑1.2亿个观察事项以进行预测，比如贷款通过率、使用者接受推荐产品的可能性和某服务对于使用者的价值。
By giving away free credit scores to more than 60 million people, Credit Karma upended the paid credit report market. And by offering free tax returns this year — at the same time H&R Block and IBM Watson were bragging about AI-powered tax filings — the company stormed the $8.9 billion tax preparation industry. Bold disruptions like this matter, but Credit Karma’s effort to quietly assemble the massive trove of information underpinning each of these moves may be even bolder.
Credit Karma works like this: Members supply personal information (name, address, phone, social security number) to receive credit scores and, if desired, to be matched with the best credit card, personal loan, and auto loan offers, and to file their federal income taxes — all for free. The company gets paid a commission by the credit card and loan issuers, and it vows it will never charge consumers. “We will always be free, that’s our core promise,” said chief technical officer Ryan Graciano, in a conversation with VentureBeat’s Blaise Zerega?at Collision 2017.
The resulting data itself is invaluable — imagine what insights into?one-fifth of America’s household debt might yield, but the tools and models Graciano and his team use to extract these insights are its magic glue. According to Graciano, the company is able to serve consumers up-to-the-minute recommendations for their financial decisions within 20 milliseconds. And to do this, the service relies not on general artificial intelligence (AI) but on artificial narrow intelligence (ANI).
Now that Credit Karma has both tax and credit data, it?can add more value to its?services. For instance, according to Graciano, “We can do things like notice you have a mortgage and point out that your forgot to deduct it on your tax returns.”
“AI is definitely over-hyped. The promise of AI is generalizable intelligence, the ability to not only learn but to reason, to pattern match, to interact, and I think what we have today is best described as artificial narrow intelligence. ANI is actually amazing and deserving of the hype,” Graciano said, adding that ANI is “very good at doing one very specific thing in a probabilistic fashion.” This means things like identifying a cat, but also instances where there is a big set of data coming in and one specific output coming out. “ANI is transformational to your business if you use it correctly,” Graciano said. “For us, I think it’s actually a key part of our secret sauce.”
Graciano explains the process as taking, say, 200 million data points, crunching them into 2,000 factors per member, and then putting all of it together into a binary “approved” or “not approved” outcome. “We have to use data in production, for ad hoc analysis, for data science and modeling, and for online prediction, across all of our products and platform,” Graciano said. He adds that a single data set is 210 TB, and that their data is growing at more than 1 TB per day. (The company is adding 1 to 2 million members each month.) Further, each month Graciano and his team create 1,000 new models, which consider 120 billion observations to predict everything from loan approval odds to the likelihood members will interact with offers to the value of particular services for members.
The 10-year old company claims to be profitable, having reportedly generated $350 million in revenue in 2015, and it may be worth as much as $3.5 billion. An obvious next step for Credit Karma would be home mortgages and international expansion. In terms of expansion, the company recently entered the Canadian market. Another opportunity could be to develop a?credit rating service, like TransUnion or Equifax. Graciano discounts this option. “Being a credit bureau comes with its own challenges,” he explained. “There’s a lot of regulatory stuff to worry about there.”
Graciano believes that his company’s competitive advantage isn’t big data and ANI per se, but rather the consumer trust they’ve helped earn. And he thinks companies that jump on the AI hype wagon are going to have a bumpy ride. “I think AI will have a tricky time,” Graciano said. “Businesses that don’t master the ANI space are really going to struggle. If you work in volume, with the consumer especially, then you have to master ANI. You have to get really good at predicting what’s best for your consumer and what maximizes your business outcome.”