Artificial Intelligence is the field of computer science that studies how machines can be made to act intelligently. The benefit of using The benefit of.

Slides:



Advertisements
Similar presentations
By Jessica Mendoza & John Ester
Advertisements

Chapter 1 Business Driven Technology
Data Mining in Computer Games By Adib Adam Hussain & Mohammed Sarfraz.
Data Mining Glen Shih CS157B Section 1 Dr. Sin-Min Lee April 4, 2006.
1.08 Describe the nature of the insurance industry Acquire knowledge of the insurance industry to obtain a foundation for employment in insurance.
The Decision-Making Process IT Brainpower
3.7 Market Research for EC Market research is aimed at finding information that describes the relationship between consumers, products, marketing methods,
DATA MINING CS157A Swathi Rangan. A Brief History of Data Mining The term “Data Mining” was only introduced in the 1990s. Data Mining roots are traced.
By Matt Goliber and Jim Hougas Data Mining and Knowledge Discovery.
Developing A Strategy For The Internet Age The Five Forces Model
Data Mining Jessica Jackson Kimberli Klein Kevin Wood.
Artificial intelligence 4 Expert systems 4 Neural nets 4 Data base mining.
Data Mining By Archana Ketkar.
Data Mining Adrian Tuhtan CS157A Section1.
Chapter 1 Accounting System Insights ACCOUNTING INFORMATION SYSTEMS The Crossroads of Accounting & IT © Copyright 2012 Pearson Education. All Rights Reserved.
Principles of Marketing
Data Mining & Data Warehousing PresentedBy: Group 4 Kirk Bishop Joe Draskovich Amber Hottenroth Brandon Lee Stephen Pesavento.
Features and Functions of Information Systems. What are information systems?  Information systems consist of software, hardware and communication networks.
Compute the cost of different types of life insurance. Understand advantages and disadvantages of different types of life insurance. Slide 1 OBJECTIVES.
TURKISH STATISTICAL INSTITUTE INFORMATION TECHNOLOGIES DEPARTMENT (Muscat, Oman) DATA MINING.
Marketing Research – Collecting Data
Enterprise systems infrastructure and architecture DT211 4
Health Insurance: The Basics Independent Living. 5 Things You Should Know About Health Insurance… Insurance costs a lot but having none costs more If.
3-1 Chapter Three. 3-2 Secondary Data vs. Primary Data Secondary Data: Data that have been gathered previously. Primary Data: New data gathered to help.
Data Mining By Andrie Suherman. Agenda Introduction Major Elements Steps/ Processes Tools used for data mining Advantages and Disadvantages.
Data Warehousing by Industry Chapter 4 e-Data. Retail Data warehousing’s early adopters Capturing data from their POS systems  POS = point-of-sale Industry.
By: Dr. Mohammed Alojail College of Computer Sciences & Information Technology 1.
Data Mining By Jason Baltazar, Phil Cademas, Jillian Latham, Rachel Peeler & Kamila Singh.
By Dina and Sanskriti. Online marketing  is the marketing of products or services over the Internet.  many forms of it. This includes: display advertising,
Information Age In Which We Live Session 2. Introduction Knowledge is Power What you don’t know will hurt you Business are using information to reel in.
aidevel GEORGE-BOGDAN IVANOV - BOGDAN-IVANOV.COM TECH AIDEVEL
Ethical Issues in Information Technology First Annual Conference on Ethics and Technology Chicago, 1996 Mary Malliaris.
Database : collection of information. data management tool. huge volumes. like a filing system. providing answers.
Chapter 6: Foundations of Business Intelligence - Databases and Information Management Dr. Andrew P. Ciganek, Ph.D.
Database Design Part of the design process is deciding how data will be stored in the system –Conventional files (sequential, indexed,..) –Databases (database.
 Fundamentally, data mining is about processing data and identifying patterns and trends in that information so that you can decide or judge.  Data.
Advanced Database Course (ESED5204) Eng. Hanan Alyazji University of Palestine Software Engineering Department.
Next Back MAP 3-1 Management Information Systems for the Information Age Copyright 2002 The McGraw-Hill Companies, Inc. All rights reserved Chapter 3 Data.
Concepts in Enterprise Resource Planning Fourth Edition
1 Technology in Action Chapter 11 Behind the Scenes: Databases and Information Systems Copyright © 2010 Pearson Education, Inc. Publishing as Prentice.
6.1 © 2007 by Prentice Hall 6 Chapter Foundations of Business Intelligence: Databases and Information Management.
Computer in Everyday Life
Artificial Intelligence, Expert Systems, and Neural Networks Group 10 Cameron Kinard Leaundre Zeno Heath Carley Megan Wiedmaier.
DATA MINING PREPARED BY RAJNIKANT MODI REFERENCE:DOUG ALEXANDER.
Chpt 9 TECHNOLOGICAL CHANGES FOR THE FUTURE. Introduction The competition environment in the future: Situation of business always change from time to.
CHAPTER 8 DATA MINING BASICS.
Academic Year 2014 Spring Academic Year 2014 Spring.
6-1 Copyright © 2013 Pearson Canada Inc. Databases and Information Management CHAPTER SIX.
Data Mining Copyright KEYSOFT Solutions.
WHAT IS DATA MINING?  The process of automatically extracting useful information from large amounts of data.  Uses traditional data analysis techniques.
Miloš Kotlar 2012/115 Single Layer Perceptron Linear Classifier.
Artificial Intelligence, simulation and modelling.
Chapter 3 Building Business Intelligence Chapter 3 DATABASES AND DATA WAREHOUSES Building Business Intelligence 6/22/2016 1Management Information Systems.
FACULTY EXTERNSHIP OPPORTUNITIES IN DATA SCIENCE AND DATA ANALYTICS Facilitated by: FilAm Software Technology, Clark Freeport Zone Ecuiti, San Francisco,
Artificial Intelligence and Machine Learning in Big Data and IoT: The Market for Data Capture, Analytics, and Decision Making 2016 – 2021 Phone No.: +1.
DATA MINING IN INFORMATION MANAGEMENT – APPROACHES AND IMPLICATIONS BY 1.OSHODI ISMAIL OLAKUNBI [ ] 2.SALAKO TESLIM AKOLADE [ ] 3.ODUTAYO.
By: Megan Ryan Phillip Striggow Jonathan Zamora Marquenon Franklin
Data Mining.
Business Intelligence Minor
Classification of models
Databases and Information Management
Dr Paul Lewis Chief Technology Officer
Adrian Tuhtan CS157A Section1
Artificial Intelligence with Heart: Improving Customer Experience through Sentiment Analysis.
MACHINE LEARNING.
Data mining Data mining is the process of analyzing data from different perspectives and summarizing it into useful information.
3.7 Market Research for EC Market research is aimed at finding information that describes the relationship between consumers, products, marketing methods,
Welcome! Knowledge Discovery and Data Mining
Promising “Newer” Technologies to Cope with the
Presentation transcript:

Artificial Intelligence is the field of computer science that studies how machines can be made to act intelligently. The benefit of using The benefit of using AI enabled software is that properly trained machines can make decisions and predictions on important future events with the accuracy at the level of a human expert.

John McCarthy, professor of computer science, works at the artificial intelligence lab in Stanford, Calif. McCarthy, father of artificial intelligence and professor emeritus at Stanford University, has died at age 84. The university announced that McCarthy died early Monday, Oct. 24, 2011, at his home in Palo.

DATA MINING ADVANTAGES DISADVANTAGES DATA MINING – Intelligence Agent with great potential to help companies focus on the most important information in the data they have collected about the behaviour of their customers and potential customers. It is the process of analyzing data from different perspectives and summarizing it into useful information

Insurance industry needed Data Mining Software as a new tool for knowledge discovery. Companies in the Insurance industry collected enormous amounts of data about their clients. This is invaluable information about customers behaviour, activities, and preferences. INSURANCE BUSINESS

- Predict which customers will buy new policies; - Spot and understand new business trends in claims; - Detect customers, belonging to frequent buying patterns. Advantages Data Mining in Insurance Business

Insurance companies collect information about their customers in many ways for understanding their purchasing behaviours trends. However companies don’t last forever, some days they may be acquired by other or gone. At this time the personal information they own probably is sold to other or leak. Because of privacy issues, people are afraid of their personal information is collected and used in unethical way that potentially causing them a lot of trouble Privacy Issues Insurance companies owns information about their employee and customers including social security number, birthday, payroll and etc. There have been a lot of cases that hackers were accesses and stole big data of so much personal and financial information available, the credit card stolen and identity theft become a big problem. Security issues Disadvantages Data Mining in Insurance Business

Information collected by Insurance Companies through data mining can be misused. This information is exploited by unethical people or business to take benefit of vulnerable people or discriminate against a group of people. Data mining technique is not perfectly accurate therefore if inaccurate information is used for decision- making will cause serious cons equence Misuse of information/inacc urate information