Federal State Educational Budgetary Institution of Higher Education
<<FINANCIAL UNIVERSITY UNDER THE GOVERNMENT
OF THE RUSSIAN FEDERATION>>
Department of Banking and Financial Markets
DEPARTMENTS OF INSURANCE AND SOCIAL ECONOMY
DISCIPLINE <<FINANCIAL MARKETS>>
THEME: << BIG DATA IN INSURANCE>>
STUDENT:
Enebeli Ijeoma Alexandra
GROUP: IFF20-3
TEACHER: something sth
Moscow 2022
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Table of Contents
INTRODUCTION ....................................................................................................... 3
ANALYSIS OF THE INSURANCE MARKET ...................................................... 4
CURRENT STATE of the European Insurance Market ......................................... 4
REGULATION OF THE INSURANCE MARKET .............................................. .9
State regulation of insurance activities...................................................................9
Functions of insurance supervision ...................................................................... 11
CONCLUSION .......................................................................................................... 13
REFERENCES .......................................................................................................... 14
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INTRODUCTION
As long as human civilization itself, the practice of assuring financial loss
protection and risk mitigation has existed. As the world begins to shift more towards
technological development in every sphere, like many other industries, so has the
insurance sector begin to move more rapidly towards it. This has even become more
accelerated thanks to the covid pandemic. Leading commercial life insurance, property
and casualty, and health and medical insurance carriers make up most of the over $5.9
trillion global insurance market today.
The use of data analytics to target clients has long been a priority for the
insurance sector. Large-scale information gathering and storage are now possible
thanks to the digital revolution. Because it is too complicated to be processed using
conventional data processing methods, this data is referred to as big data. Big data is
used in the insurance industry to describe the use of unstructured and/or structured data
to affect underwriting, rating, pricing, forms, marketing, and claims management. The
insurance business is entering a new era of data analytics that promises fresh
perspectives to improve customer acquisition, risk underwriting, fraud detection, and
claim resolution. The use of big data in the insurance sector is expanding because of
waves of data from consumer POS transactions, mobile interactions, and car telematics.
Like any other sector, the industry has seen the usage of technology develop
exponentially. New methods of tracking, assessing, and reducing risk have been tested
by insurance companies thanks to advanced technologies and digital platforms.
According to Paul Ford, co-founder, and CEO of Traffk, insurance companies need to
change to keep up with shifting consumer demographics and preferences. For insurance
firms, big data is particularly attractive and distinctive. Data is possibly one of their
most valuable assets because they don't have any physical goods to produce and sell.
Big data is used by businesses to provide better customer service, which can
boost profit since the majority of businesses' top priority is to improve the customer
experience. The main objective of this paper is to highlight the roles of Big Data in the
insurance market.
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WHAT IS BIG DATA?
Big data is a collection of structured, semi structured, and unstructured data that
is gathered by organizations and can be mined for information for use in advanced
analytics applications like machine learning and predictive modelling. The three Vs are
frequently used to describe big data:
 the huge volume of data in various locations.
 the variety of data types typically housed in big data systems.
 and the velocity at which much of this data is being done all these things.
Big data in the context of insurance refers to unstructured and/or structured data that is
applied to underwriting, rating, pricing, forms, marketing, and claims processing.
USE OF BIG DATA IN INSURANCE
Insurance firms try to shield us and assist us when necessary. They create a fund
by collecting money from various customers, often known as policyholders. These
businesses promise to send us a certain amount of money when we need it. The
fundamental concept of predicting and diversifying risk serves as the foundation of
insurance companies' business strategies. The basic insurance model entails combining
individual payer risk and spreading it across a wider portfolio.
Like many other industries, the insurance sector has moved toward digital
platforms. Therefore, the use of big data technologies by insurance businesses is made
possible by the interchange of data over the internet. The move to digital platforms has
created new opportunities for information sources that can be used to precisely identify
a customer's segment and comprehend the intricate behavioural patterns of that
consumer. The nature of insurance is changing from pure risk protection to risk
prediction and prevention thanks to new technologies.
The use of big data benefits insurance businesses greatly in many ways. First
off, it expands the profit margin for insurance firms and boosts premium revenue. Big
data technology offers a solid assurance for controlling real-time customer demand
effectively, choosing high-quality clients, lowering loss ratios, and boosting revenues.
Big data can partially address information asymmetry, accurately categorize customers
based on their actual circumstances, allow businesses to charge higher risk premiums
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for clients with higher risk levels and lower risk premiums for clients with lower risk
levels, encourage businesses to retain high-quality clients as well as create beneficial
customer groups through customer behavior analysis, and increase the overall
profitability of insurance companies.
Second, big data increases the market share of insurance businesses. Big data
can enable precise product marketing. Through the analysis of user behavior, the
products may be accurately given to clients who require them. Using big data
technologies, insurance businesses may effectively search for customers from a variety
of angles and approaches, identifying possible new customers and identifying potential
needs of current clients. This allows them to expand their traditional sales channels and
increase their market share.
Additionally, the use of big data broadens the area for insurance sector
development. Big data technology has crossed the line between currently insurable and
uninsurable risks, turning previously uninsurable risks into insurable risks and
broadening the scope of the insurance industry. This has made it possible for client
resources to be shared throughout other business entities.
Big data can help insurers with their underwriting, rating, marketing, anti-fraud,
and claim settlement procedures, but insurance regulators must determine whether this
technology is good for or bad for customers. Consumers are also concerned about the
security of obtained data and the preservation of their privacy.
Big data is used by insurers in a variety of ways such as:
1. Pricing: To calculate the cost of risk and establish premiums for their insurance
policies, insurers rely on data and statistics. To prevent information asymmetries
between the customer and the insurer, the principle of transparency compels
consumers to provide all information that the insurer deems is pertinent to pricing
their risk. In most insurance categories, insurers are free to decide which variables
they will consider when determining premiums. Data is used by insurers to
determine the pertinent price variables and their differences. They assess customer
fees in accordance with the risk they pose as well as other commercial factors.
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2. Fraud Detection: Every stakeholder pays a higher premium because of fraud. Big
data can protect insurance companies from these types of frauds. Insurance
companies can discover cases that need further inquiry by comparing a person's data
to historical fraudulent profiles using predictive modelling. Through the anti-fraud
network, the insurance company can obtain the customer's purchase information
and claim information in real time. It can then use big data analysis technology to
evaluate the customer's credit standing and refuse to underwrite them. Using the
customer's purchase information, insurance companies can also confirm whether
the customer has purchased duplicate or excess insurance in order to avoid paying
a high premium for insurance.
3. Cost Optimization: One of the many advantages of utilizing technology is cost
reduction. Machines are now playing a bigger part in the economy, which boosts
efficiency and eventually lowers costs. Big data technology can be used to automate
manual operations, improving their effectiveness and cutting down on the amount
of money needed to handle claims and administrative expenditures. As a result, the
businesses will be able to charge their customers lower premiums and hence
compete successfully.
4. Insurance products personalization: Big data is crucial to the customisation of
insurance products. Unstructured data analysis can assist businesses in providing
services that are tailored to the demands of their clients. Insurance firms enable the
standardization of insurance's characteristics by using the unique information about
their customers, such as their gender, social networks, health issues, personalities,
and other details. For instance, big data life insurance based on a customer's medical
history and the habits detected by activity trackers can be made more individualized.
The information can also be used to choose a price strategy that is both profitable
for the business and matches the client's budget.
Other applications include claims management, where insurers can assess loss or
damage to segment or, in certain situations, automate claims using big data which
makes it considerably easier for providers to make important decisions regarding
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claims, such as whether or not to pay a claim, and a tool to forecast and even alter
consumer behaviour.
CONCLUSION
This is only the beginning of what big data can do in the insurance industry. Big
data is a persistent phenomenon. The rise of the Internet of Things (IOT) can be found
to have an influence for the current spike in big data's appeal in the insurance industry.
The term "Internet of Things" describes everyday objects that are all around us and
have internet connectivity. Almost everything and everyone’s data can be found online,
through social media or other media.
The opportunities provided by big data in insurance will expand along with the
proliferation of IoT devices online and changes in customer behaviour, as will the
cloud's ability to store such vast amounts of data. By 2025, the worldwide datasphere
is predicted to grow to 175 zettabytes, according to IDC predictions.
In order for insurance companies to remain competitive and meet rising client
demand, insurers must carefully assess their technology stacks in light of the expanding
worldwide capacity for data collection and storage as well as the developments in AI
and machine learning. However, insurers must also get ready for organizational change
in addition to spending money on big data analytics, hiring and educating the proper
personnel, and putting in place corporate-wide procedures to control data aggregation.
This necessitates the capacity to manage change. Analytics is no longer just another IT
project; it is a game-changer with the ability to impact businesses.
Insurance's big data market was worth $2.4 billion in 2018 and is expected to
even grow more in the foreseeable future. Half of all automobiles on the planet will
have telematics-based insurance coverage by the year 2030. 10% of annual propertycasualty insurance losses, or up to $32 billion, are attributable to fraud.
REFERENCES
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1. Big Data in Insurance. The Use of Big Data Technology in Insurance Industry.
URL:
https://beinsure.com/big-data-in-insurance-role-uses-of-big-data-
technology-in-insurance-industry/
2. BIG DATA. URL: https://content.naic.org/cipr-topics/big-data
3. Impact
of
Big
Data
on
the
Future
of
Insurance.
URL:
https://actuaries.asn.au/Library/Opinion/2016/BIGDATAGPWEB.pdf
4. What is big data in insurance? URL: https://artificial.io/company/blog/what-is-bigdata-in-insurance
5.