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VRSK

NASDAQ Industrials

Verisk Analytics, Inc. - Common Stock

Consulting Services

Verisk Analytics, Inc. engages in the provision of data analytics and technology solutions to the insurance industry in the United States and internationally. The company offers underwriting solutions, including forms, rules, and loss costs services that provides policy language, prospective loss costs, policy writing and rating rules, and underwriting solutions for risk selection and segmentation, pricing, and workflow optimization; underwriting data and analytics solutions, which provides property and auto specific rating, and underwriting information solutions; catastrophe modelling and risk solutions; life insurance solutions for transforming current workflows in life insurance underwriting, claim insights, policy administration, unclaimed property/equity, compliance and fraud detection, and actuarial and portfolio modelling; specialty business solutions, which provides full end-to-end management of insurance and reinsurance business; and international underwriting solutions. It also provides claims insurance solutions, including property estimating solutions, provide data, analytics, and networking solutions for professionals involved in estimating all phases of building repair and reconstruction; anti-fraud solutions that provide fraud-detection tools for the property and casualty insurance industry; casualty solutions, which focus on compliance, casualty claims decision, and workflow automation; and international claims solutions, which focus on personal injury and motor franchises with complementary offerings to the property claims solutions. The company was founded in 1971 and is headquartered in Jersey City, New Jersey.

🎯 投资策略评分

VRSK 在各投资策略中的评分。分数越高,越符合该策略目标。

高股息率 + 低波动性
高增长潜力(高贝塔 + 超卖)
逆向投资(超卖 + 低于移动均线)
超买股票(潜在做空标的)
大盘、机构级别股票
🔍 策略解读

最佳匹配: 🔪 Falling Knife (94/100) — 此策略 逆向投资(超卖 + 低于移动均线).

评分最低的策略: 🎈 Over-Hyped (8/100). 单一评分不构成买入或卖出信号 — 请结合多种视角综合判断。 了解如何解读这些评分 →

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免责声明:本数据仅供教育和娱乐用途,不构成金融建议。市场数据可能存在延迟。在做出投资决策之前,请始终进行自己的研究。
数据最后更新: 2026-04-17.