Machine-learning is also good at automating financial decisions, whether assessing creditworthiness or eligibility for an insurance policy. Zest Finance has been in the business of automated credit-scoring since its founding in 2009. Earlier this year it rolled out a machine-learning underwriting tool to help lenders make credit decisions, even for people with little conventional credit-scoring information. It sifts through vast amounts of data, such as people’s payment history or how they interact with a lender’s website. Lemonade, a tech-savvy insurance startup, is using machine-learning both to sell insurance policies and to manage claims.
機器學習還擅長自動化金融決策，無論是評估信用還是保單的投保資格。Zest Finance自2009年成立後就從事自動化信用評分業務。今年早些時候，該公司推出了一款機器學習信貸審核工具，可幫助貸款方做出信貸決策，甚至可以決定是否貸款給那些幾乎沒有傳統信用評分信息的人。該工具篩查大量的數據，如這些人的付款歷史，或是他們與貸款方網站的互動。精通科技的保險創業公司Lemonade既利用機器學習來賣保險，也用它來管理索賠。
表達
1. automated credit-scoring：自動化信用評分
2. a tech-savvy insurance startup：精通科技的保險創業公司
3. insurance policies：保單
4. sift 篩選
Perhaps the newest frontier for machine-learning is in trading, where it is used both to crunch market data and to select and trade portfolios of securities. The quantitative-investment strategies division at Goldman Sachs uses language processing driven by machine-learning to go through thousands of analysts’ reports on companies. It compiles an aggregate “sentiment score” based on the balance of positive to negative words. This score is then used to help pick stocks. Goldman has also invested in Kensho, a startup that uses machine-learning to predict how events like natural disasters will affect market prices, based on data on similar events.
機器學習的最新應用領域可能是在交易上，人們用它來分析市場數據，以及選擇並交易證券投資組合。高盛的量化投資部門用機器學習驅動的語言處理技術來通讀分析師撰寫的成千上萬份公司研報。該技術根據積極言論和消極言論的數量對比，編制出一個綜合的“情緒評分”，然後用這一評分來幫助選擇股票。高盛還投資了Kensho，這家創業公司根據自然災害等事件的有關數據，用機器學習預測這些事件將如何影響市場價格。
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