1. INTELLIGENT SYSTEMS BUSINESS MOTIVATION BUSINESS INTELLIGENCE
M. Gams

2. Intelligent systems, BI
IN. SOCIETY
ENGINEERING, TECHNOLOGY, BUSINESS, ECONOMY
ARTIFICIAL INTELLIGENCE

3. Definition Business intelligence (BI) (Wikipedia)
mainly refers to computer-based techniques used in identifying, extracting, and analyzing business data, such as sales revenue by products and/or departments, or by associated costs and incomes.
BI technologies provide historical, current and predictive views of business operations. Common functions of business intelligence technologies are reporting, online analytical processing, analytics, data mining, process mining, complex event processing, business performance management, benchmarking, text mining and predictive analytics.

4. Definition Business intelligence (BI) (Wikipedia)
Sometimes used as a synonym for competitive intelligence, because they both support decision making, but BI uses technologies, processes, and applications to analyze mostly internal, structured data and business processes while competitive intelligence gathers, analyzes and disseminates information with a topical focus on company competitors.
For us, BI including some AI tool, artificial intelligence, intelligent systems, machine learning (seminar work rather not including genetic algorithms, decision systems)

5. COMPETITIVE VIEWPOINT THE LEGATUM PROSPERITY INDEX 2018
2017 rating rating Country
1 1 Norway
2 2 New Zealand
3 3 Finland
4 4 Switzerland
7 5 Denmark
5 6 Sweden
10 7 United Kingdom
8 8 Canada
6 9 Netherlands
12 10 Ireland
13 11 Iceland
14 12 Luxembourg
9 13 Australia
11 14 Germany
15 15 Austria
16 16 Belgium
18 17 United States
21 18 Slovenia
Economy Business Govern. Freedom SocialCap. Safety Education Health Nature
21 18 Slovenia 31 41(+15) (-5) 1
22 19 Malta
19 20 France Singapore Hong Kong Japan Portugal Spain Estonia Czech Republic Cyprus Mauritius Uruguay Costa Rica Slovakia Poland Italy South Korea
Analogy: soocer team; competition: player, team, coach, league // business, real life
Idea: AI will help gain advantage

6. BUSINESS INTELLIGENCE - theses
With AI methods it is possible to evaluate gain for past events (condition: enough data/information can be obtained if not, results are less valuable or less graded)
With AI approach, in „soft“ areas like business or economy or politics it is possible to evaluate gains
For nearly all future actions it is possible to predict future gains with better probability than before

7. BI – overview
AI methods, data mining, business AI methods, intelligent systems, agents, MAS
Nash equilibrium, prisoner dilemma, Wooldridge
Bounded rationality, behavioral economics; Herbert A. Simon, Nobel Prize for decision making in economy, Turing award
Agent / crowd predictability, R. Heiner
Robert Merton, Social Theory and Social Structure, self fulfilling prophecy, bank Millingville, 1949   

8. Intelligent Systems Properties
Learning, Flexibility, Adaptation, Explanation, Discovery
Intelligent system, some AI tool – agents (equilibrium, selling, e-commerce, trading ..), user profiling, …
(I)DM, (I)ML

9. BI practical

10. BI (IS) areas
Support for BI/IS solutions: BI/IS governance, BI/IS strategies, BI/IS maturity models, BI/IS success factors, and BI/IS performance
Emerging trends in BI: pervasive BI, BI 2.0 (social media and BI), and mobile BI
Real time data warehousing und operational BI
Applications of BI, such as customer relationship management and business performance management
Data warehousing and data integration
Predictive and advanced analytics, and data visualization
Data, text and web mining for BI
Management of knowledge and business process improvement
Social and behavioral issues , and social media usage
Capturing and sharing knowledge in social networks and distributed contexts
Design, development, adoption, usage, and impact of IS on KI
Inter-organizational IS BI systems, such as in the supply chain and learning

11. BI (IS) APPLICATIONS BUSINESS FINANCE
ECONOMY Related to a person, institution, country, continent …
Anything of this related to IS, i.e. using AI methods
RECOMMENDED METHODS FOR SEMINAL WORK DM on business-related data agent modeling on a business process
PRACTICAL EXAMPLES analyze efficiency of tax systems predict stock (share) values predict oil prices design a model for bank loans is selling country assets beneficial or not?

12. Intelligent systems Engineering, invisible intelligence
Practical directions, real-life problems
Verified AI methods: rule-based systems, trees, expert systems, fuzzy systems, neural networks, genetic algorithms, hybrid systems
Intelligent systems often simulate human bureaucrats, expert systems simulate experts

13. Motivation / business
People are expensive (to buy or maintain), computers cheap: computers work 24 hours a day, no vacations, network accessibility is worldwide, only 3% microprocessors in computers, an average car 16 microprocessors, exponential trend (faster, cheaper, more applications)
Intelligent systems are more friendly, more flexible than classical systems (not truly intelligent, just a bit more than classical)

14. Examples: S. Goonatilake, P. Treleaven: I. S. for Finance and Business
20 years ago substantial increase in IS Killer applications - breakthrough
Visa, 6 G trans. ann., 550G$, security; American Express, 15$ > 1.4$
typical: lots of data, new AI and HW cap.
quality improvement, lower costs,

15. Killer application American Express, Visa
Authorizer’s Assistant - an expert system
before: simple rigid rules, majority left to human supervisors, many people with different performance
Then new: an expert / intelligent system with many rules, copies expert supervisors, faster, cheaper, more equilibrated 10 times better per one transaction
(Visa - an neural network – DM and ML prevail)

16. Benefits
The key question – trust – can IS be trusted - obviously good enough (actually as good as average humans)
Intelligent systems enabled organizational changes in terms of HW, SW and humans
Work done better and faster, more profits, cheaper transactions
Less employed, more work done by computers
Problem – unemployment … NOT

17. A CASE STUDY: EAST EUROPEAN GOVERNMENT SELLS A COMPANY
CECIIS Varazdin,

18. Transition
 $$$$
CECIIS Varazdin,

19. N-DIMENSIONAL DECISION SPACE: PARETO FRONT
- $
- Companies
Green – Pareto front
Blue – possibilities
Red – typical human
CECIIS Varazdin,

20. AN EXAMPLE OF A BAD DECISION
The government gets 50 million
Each ear 10 million leave the country
In 5 years the gain is lost
In 10 years, the country looses 50 million and has lost ownership
Real example: banks
CECIIS Varazdin,

21. Discussion BI = IS/AI (DM) for business and economy
BI combine advantages of computer systems (cost, availability) with IS methods, simulating some human properties (learning, adapting, reasoning), and achieve better cost/benefit for several tasks in BI
How to use BI? IS/AI/DM (computer intelligence) + BI problem + additional knowledge (economic, BI)