Data Analysis - 1.1 to 1.3 (Shyam) fully
solved
What is the objective of studying big data and technology in risk management and insurance? -
correct answer ✔✔To explain how they influence risk management and insurance strategy.
How does data allow insurers to provide coverage for a variety of risk exposures? - correct
answer ✔✔Through the law of large numbers and analyzing large numbers of claims.
Why do claims or underwriting professionals study data analytics? - correct answer ✔✔To use
the results of analytics in their decision making and effectively communicate with data
scientists.
Why would an insurance professional who is not an actuary or a data scientist want to learn
about data analytics? - correct answer ✔✔Because big data and technology are central to the
future of the insurance industry and have already disrupted traditional practices.
What are some strategic opportunities presented by big data and technology in the insurance
industry? - correct answer ✔✔Disruption of traditional marketing, underwriting, and product
analysis methods.
How does technology influence the insurance industry? - correct answer ✔✔It changes how
insurers communicate, learn, and do business.
What is the convergence of big data and technology transforming in the insurance industry? -
correct answer ✔✔The property-casualty insurance business.
,What is the role of data in predicting future claims? - correct answer ✔✔By analyzing large
numbers of claims, insurers can reasonably predict the probable cost of future claims.
What is the challenge for insurers as technology evolves? - correct answer ✔✔Developing new,
more efficient methods of processing and analyzing the increasing amount of data available.
What is the benefit of studying data analytics for insurance professionals? - correct answer
✔✔To stay updated with the evolving industry and effectively adapt to future technology
disruptions.
What is the impact of big data and technology on the insurance industry? - correct answer
✔✔It disrupts traditional ways of marketing, underwriting, and product analysis.
What is the significance of big data and technology in the insurance industry? - correct answer
✔✔They are central to the future of the industry and its evolution.
What is the future technology that will further disrupt the insurance industry? - correct answer
✔✔Autonomous vehicles.
What is the traditional source of data used by insurers? - correct answer ✔✔Loss histories.
What is the law of large numbers in relation to insurance? - correct answer ✔✔It allows insurers
to provide coverage for a variety of risk exposures.
What is the role of data scientists in insurance organizations? - correct answer ✔✔To effectively
communicate with insurance professionals and provide insights from data analytics.
What is the challenge for insurance professionals in using data analytics? - correct answer
✔✔To effectively communicate with data scientists and understand the results of analytics.
, What is the impact of big data and technology on decision making in insurance? - correct
answer ✔✔It increasingly influences decision making for claims and underwriting professionals.
What is the future outlook for the insurance industry with regards to big data and technology? -
correct answer ✔✔Continued disruption and adaptation to new technologies.
What is Big Data? - correct answer ✔✔Large and complex data sets that cannot be easily
managed or analyzed using traditional methods.
Why is communication and collaboration important between insurance professionals and data
scientists? - correct answer ✔✔To analyze new techniques and ensure success in applying data
analytics to insurance.
How can decision making driven by big data provide better results? - correct answer ✔✔By
using data analytics to identify profitable clients and develop effective strategies.
What is an example of using big data in the credit industry? - correct answer ✔✔Using loss
histories to select clients and determine credit lines.
What did Signet Bank do to obtain data for credit analysis? - correct answer ✔✔Provided credit
randomly to collect a base amount of data.
What were the results of Signet Bank's data acquisition strategy? - correct answer ✔✔Losses
increased significantly, but it led to the development of predictive models.
What did Signet Bank's data scientists do with the collected data? - correct answer ✔✔Created
predictive models to identify characteristics of profitable clients.