Advanced my friends who have been always helping and

 

Advanced databases and their
applications

BUSINESS INTELLIGENCE

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CONTENT

           

ACKNOWLEDGEMENT       

INTRODUCTION

HISTORY OF THE COMPANY

VISION

MISSION

DATA WAREHOUSE

v
WHAT
IS DATA WAREHOUSING?

v
PURPOSE
OF USING DATA WAREHOUSE

 

DATA MINING

v
WHAT IS DATA MINING?

v
PURPOSE OF USING DATA MINING

 

BIG DATA ANALYTICS

v
WHAT IS BIG DATA ANALYTICS?

v
PURPOSE OF USING BIG DATA ANALYTICS

 

DATA WAREHOUSING, DATA MINING & BIG
DATA ANALYTICS IN ROYAL & SUN ALLIANCE INSURANCE COMPANY LTD

BENEFITS THAT THE COMPANY GAIN BY USING
ABOVE TECHNIQUES

SUMMARY

CONCLUSION

 

 

 

 

     
 

ACKNOWLEDGEMENT

 

I
would like to express my sincere gratitude to our module leader Mr. Rasika
Alahakoon, for his invaluable guidance in making this assignment based on
Business Intelligence.

Also
I am thankful to my parents and my friends who have been always helping and
encouraging me.

 

INTRODUCTION

 

Globalization, unpredictable markets,
lawful changes and organizational progress have a gigantic impact on business
environments in most industries. More and more IT is deployed to manage the complication.
As a result, companies and administrations have to switch increasing volumes of
data which have become a valuable asset. The ability to benefit from this asset
is progressively essential for business success. Hence, fast storage, trustworthy
data access, intelligent information reclamation, and new decision-making appliances
are required. Business Intelligence (BI) and Performance Management (PM) offer
solutions to these challenges.

 

Company               :
– RSA Insurance Group plc (trading as RSA,
formerly Royal and Sun Alliance)

                       Company
Logo     :-                                   

 

 

 

 

 

HISTORY OF THE COMPANY

 

 

RSA Insurance Group plc (trading as RSA,
formerly Royal and Sun Alliance) is a British multinational general insurance
company headquartered in London, United Kingdom. RSA has major operations in
the UK & Ireland, Scandinavia and Canada and provides insurance products
and services in more than 140 countries through a network of local partners.

It has 17 million customers. RSA was
formed by the merger of Sun Alliance and Royal Insurance in 1996. RSA is listed
on the London Stock Exchange and is a constituent of the FTSE 100 Index. In
1706, the original Sun Insurance company was established by Charles Povey.

Over the past three centuries, The Company
developed into the internationally recognized FTSE 100 business known today as
RSA. Around 14,000 people are still making things better for over nine million clients
in more than 100 countries.

 

 

 

VISION

 

“Our
business is built around our customers. By focusing on their needs we challenge
ourselves to achieve more”

-Stephen
Hester-

Group
Chief Executive, RSA

 

      
 MISSION

 

“Whilst
our 2015 performance represents significant progress from 2013 to 2014, we
target deeper performance improvements over the next few years to take our
business toward best-in-class”

-Martin
Scicluna-

Chairman,
RSA

 

 

 

DATA WAREHOUSE

 

WHAT
IS DATA WAREHOUSING?

           

An
electronic storage of a large amount of information by a business is called as
Data warehousing. Data warehousing is an energetic element of business
intelligence that works systematic techniques on business data. The theory of
data warehousing was introduced in 1988 by IBM investigators Barry Devlin and
Paul Murphy. The need to warehouse data progressed as computer systems became
more multifaceted and handled increasing amounts of data.

 

 

 

PURPOSE
OF USING DATA WAREHOUSE

 

For
taking considering organization (data related) with their decision making
process, data warehousing work as the foundation. It makes information easy to reachable
as the company can produce reports, like Operational & Originality report
from the data warehouse. Also Data Warehouse obliges reporting and analytics. For
operational reasons like a contact center, Data warehouse can be used.

 

                    DATA
MINING

 

                        WHAT IS DATA MINING?

 

To turn raw data into useful information,
Data mining is a process that is used by companies. Businesses can learn more
about their customers by using software to look for configurations in large collections
of data, and also can develop more effective marketing strategies as well as
increase sales and lessening costs. Data mining depends on operative data gathering
and warehousing as well as computer processing. The methods are used in several
ways like shopping basket analysis, in the banking sector, in the insurance
sector, fraud detection based on behavioral and historical data.

                       

                        PURPOSE OF USING DATA
MINING

 

The
organizations identify relationships between price, product, financial
indicators, customer demographics, and further with the help of data mining.
Data mining empowers organizations to then regulate the impact on sales,
customer fulfillment, and corporate profits.

 

 

                   BIG DATA ANALYTICS

 

                        WHAT IS BIG DATA ANALYTICS?

 

Big
data analytics bring up the strategy of considering large volumes of data, or
big data. Wide variety of sources, including social networks, sensors, videos,
digital images, and sales transaction records is gathered from this big data.
The purpose in analyzing all this data is to expose designs and connections
that strength otherwise be unseen, and that might provide valuable insights
about the users who generated it. Through this insight, businesses may be talented
to gain a superiority over their opponents and make superior business
decisions.

 

                        PURPOSE OF USING BIG DATA ANALYTICS

 

It
is to take action and to make more truthful decisions and to do so quickly. Irrespective
of industry or environment, situational awareness means having an understanding
of what organization  need to know, what
they have control of, and conducting analysis in real-time to identify differences
in normal patterns or performances that can affect the outcome of a business or
process. If the company have these things, making the right decision within the
right aggregate of time in any environment becomes much easier.

 

DATA WAREHOUSING, DATA MINING & BIG
DATA ANALYTICS IN ROYAL & SUN ALLIANCE INSURANCE COMPANY LTD

 

RSA
Group of companies has their major procedures in the UK & Ireland,
Scandinavia and Canada and be responsible for insurance products and services
in more than 140 countries through a network of local partners, so that the
company has to use these Business Intelligence Techniques for the improvements
and well-being of the customers and the company.

To
engage data mining processes successfully, the company should know who the
customers are. They listed them by name, function, job title, and business unit
so they can communicate with them regularly. After that, they must be able to
identify the appropriate business opportunities. In MIS, The company significances
are based on business needs as articulated to them by the clients through ad
hoc requests and project management meetings and processes. Constant
communication, reintegration and feedback are required to ensure that, the
company invested their resources in proper ways. The modern advancement in capably
transforming and offering data is formal data warehousing.

 

The
company uses these kind of data warehousing techniques.

 

·        
Claims Analysis

Now
a days, this has become the most predominant, and the most successful, use of
data warehousing in the insurance industry. Companies have gathered archives of
5, 10 or even 20 years of raw claim or loss data. This base of protected party
and occurrence data can be collected into a rich and comprehensive analytic
resource when combined with the right relative information.

·        
Service
Optimization

People
get near term and tangible payback for their warehouse investment when analysis
creates the opportunity to take cost out of the system or to better utilize
existing resources. A potentially higher value outcome is to create completely
new service offerings.

 

 

 

 

 

·        
Customer Share

 

The insurance industry
has long known what other businesses are only just learning: It is more
efficient to sell more to an existing customer than it is to find a new one. A
data warehouse can be used to link customer information across lines of
business to produce a composite customer view. Comparative analysis and
profiling can create representative portfolios of insurance coverage. Gap
analysis can identify customers who have potential needs not being served
today. This can feed marketing campaigns by outbound telemarketing or
traditional field agent outreach to sell more business into the existing
customer base.

 

·        
Market Coverage and Niche Development

Customers
are being targeted based on a more sophisticated view of behavior. This is very
different from the traditional methods of actuarial analysis or underwriting. A
data warehouse can be used in all phases of market identification and
penetration.

·        
Product Profitability

Products
are becoming more narrowly defined and are being deployed against more focused
target customer groups. It is no longer acceptable to measure profitability at
just the business unit level or only for a few large customer categories.

·        
Customer Profitability

There
are generally accepted accounting principles for recognizing revenue but this
only applies to aggregate totals at the business unit level. If product level
profitability is difficult, customer level profitability is a nightmare.

 

For
Increase customer loyalty, unlock hidden profitability & reduce client
churn, they use these kind of methods in data mining techniques.

 

 

 

·        
Identifying fraud insurance claims.

 

Through the mining of
historical information, insurance companies can spot claims with a high
percentage of recovering money lost through fraud and develop rules to help
them flag future fraudulent claims.

 

 

·        
Business practices
such as, acquiring new customers, retaining existing customers, performing sophisticated
classification, correlation between Policy designing and policy selection. 

 

As
a reputed insurance company, RSA Group has follows these kind of methods using big
data analytics.

 

·        
Telematics in auto insurance:
Use of telemetry data for optimized tariffs and incentives for claim reduction,
calculation of optimal insurance premiums for the individual risk of damage,
for example: ‘Pay-how-you-drive’ tariffs.

 

·        
Telematics in health insurance:
Use of health and life-style data for the calculation of new healthcare plans.

 

·        
Real-time scoring for credit and
plausibility check upon application: Analytical evaluation
of existing customer data, external statistics, Internet data and information
from geo-systems in real-time.

 

·        
Real-time scoring for fraud in damage
report: Analytical evaluation of party and contract data,
historical data, internet data and geosystems.

 

 

BENEFITS THAT THE COMPANY GAIN BY USING
ABOVE TECHNIQUES

 

v  The
company was able to identify those commercial customers who already had one of
their single standard covers and who had a good loss ratio so they can offered
these valued customers a new branded multi risk coverage, giving them better
service while earned higher premiums.

 

v  The
long-term benefits of better customer relations and the company can give higher
lifetime value to the customers.

 

v  The
company made a significant reduction in the loss ratio in the automobile
insurance.

 

v  The
company is able to combine data from different sources, in one place.

 

v  The
company increases their data consistency and enhances end-user access to a wide
variety of data.

 

v  The
company increases their productivity and decreases computing costs.

 

SUMMARY

 

In
the modern world, all the industries gathered information and making their
business process with help and methods of new techniques like, Business
Intelligence & Knowledge Management. If so the companies use ideas on data
mining, data warehousing, big data analytics for the well-being of the clients
as well as the company. In this assignment, the techniques that has been used
by Insurance companies for their insurance claims analysis was mentioned in
detail.

CONCLUSION

                       

As
I mentioned above, all these Business Intelligence Techniques are used and will
be using for the improvements and the growth of several industries like
Insurance sector, Banking sector, Supermarket chains, Medical sector etc. When
the processes and the data capacities are become large scales, the inventors
have to find agile solutions for gather and store these data with a
professional way. So, these techniques like big data analytics, data mining,
data warehousing and knowledge management is playing an effective and agile
roles. The industries and the companies who combined with these solutions can
easily predict their future implements with profitable ways, not only that,
they can have pleasant combination with their clients by giving them the high
quality services too.                

 

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