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SmartData Collective > Analytics > Web Analytics > How Data Analytics Is Changing The Insurance Industry
AnalyticsBig DataExclusiveWeb Analytics

How Data Analytics Is Changing The Insurance Industry

Steve Jones
Last updated: 2020/11/22 at 4:18 PM
Steve Jones
5 Min Read
data analytics insurance
Shutterstock Licensed Photo - By metamorworks
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The insurance industry is based on the idea of managing risk. To determine this risk, the industry must consult data and see what trends are evident to draft their risk profiles. The journal Risk Management and Insurance Review mentions that historically, in the latter half of the twentieth century, the analysis of trends was the primary driver in determining risk in the insurance business. While it might not take a mountain of data to spot a pattern, the more data that is available, the better the chances that the trend is not an anomaly, but an established event. The twenty-first century offers a lot of exciting innovations when it comes to data processing and analytics. Towards Data Science has already stated that Big Data is already influencing a handful of industries and while the insurance industry isn’t on the list, it stands to benefit a lot from utilizing Big Data to spot trends.

Contents
Advanced Analytical Processes in InsuranceSeeing Into the FutureInsuring for the Twenty-First CenturyDealing with New Technology Appropriately

Advanced Analytical Processes in Insurance

Big Data, when combined with new technology such as artificial intelligence and machine learning, can be used to help determine trends much quicker than if humans had to pore over all the data. Industrial-sized big data pools are far too extensive for humans to ever have a chance of processing and as such, AI fueled by machine learning provides the best alternative. Information Age notes that AI is already being used in the insurance industry to improve customer experiences. By teaching AI to come to conclusions using available data faster, insurance companies can capitalize on fast response rates, despite the massive amount of data they have to handle.

Seeing Into the Future

The in-depth analysis of historical data gives insurers a platform to base their determination of risk. However, modern technology offers insurance companies the option to look forward into the future and predict potential outcomes. IBM provides a predictive analytics suite for insurers that it claims can help them deal with issues like fraudulent claims while at the same time allowing them to deal with the real-time demands of their customers. The usefulness of software like this isn’t only from the financial savings that it can offer. Analytical engines can provide deep insight into customers? behavior to predict what they are about to do. For this system to have the proper impact, it should also incorporate another emerging technology, that of IoT devices. Continual incoming data increases the data pool and allows for a more substantial amount of potential points for analysis leading to a more accurate picture.

Insuring for the Twenty-First Century

While insurance has been largely unchanged over the last century, it is currently experiencing a significant shake-up thanks to the advent of new technologies. Complex supply-chain management and cyber safety form two areas that insurance is woefully underprepared to generate risk profiles for. Online business insurance falls under the broad category of cyber insurance as well. Aon Inpoint reports that global premiums on cyber insurance are growing at an astonishing rate of 30% per year. Despite this, insurers lack the technology to be able to price the risks within fields like these accurately. Unlike property and vehicles, cyber risk is an entirely different entity altogether. Cyber risk is based, not on geographical location, but rather on interconnectivity and interaction between multiple locations across a LAN or WAN. The risk might be so widespread, not just between a handful of city blocks of buildings, but between two computer systems installed on entirely different continents all together.

Dealing with New Technology Appropriately

As time goes by, the insurance industry will need to update the way it sees both new challenges and traditional risk profiles. Integration of technology such as machine learning, artificial intelligence, IoT, and natural language processing all have a place in how insurance calculates risk. Finding where each of these technologies fit and how they can benefit the industry is the major challenge facing insurance today. Despite this, many insurance companies have realized that embracing new technology offers them a competitive edge in an already saturated market. Those who take to technology sooner stand to benefit more from its widespread acceptance in the industry.

TAGGED: big data, data, data analytics, insurance, insurance industry
Steve Jones November 22, 2020 June 26, 2019
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