Expert System and AI

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Expert Systems
Banking & Insurance
• Mahesh Karane, Sunil Chauhan
• Balaji Iyer, Sanoop Nair

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Index
• What is Knowledge Management?
• What are Expert Systems?
• What is Artificial Intelligence?
• Human Expert v/s Expert System
• Features of Expert System
• Advantages & Disadvantages of Expert Systems
• Case Study of HDFC Bank
• ATM & UESA Expert Systems
• Putting Expert System to Work
• The Creator
• References

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What is Knowledge Management?
Knowledge Management (KM) is the process of creating value
from intellectual capital and sharing that knowledge with
employees, managers, suppliers, customers and other who need
capital.
KM is a process, not a piece of technology.
Knowledge Management Systems
• Content Management Systems e.g. Wikipedia
• Collaborative Systems e.g. Web Portals, Blogs, Social
Networking
• Expert Systems e.g. Caduceus & Mycin for medical diagnosis,
Prospector for prediction of mineral deposits.
KS

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What are Expert Systems?
The expert systems (ES) are the computer applications
developed to solve complex problems in a particular domain, at
the level of extra-ordinary human intelligence and expertise.
Capabilities of Expert Systems
• Advising
• Instructing and assisting human in decision making
• Deriving a solution
• Explaining & Interpreting input
• Predicting results
• Suggesting alternative options to a problem
ES

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What is Artificial Intelligence?
Artificial Intelligence (AI) is practical mechanisms that enable
computers to simulate the human reasoning process.
The study of how to make computers do things which human
can do better – The Turing test – Can computers think?
Commercial applications of AI you may not have expected
Driverless Cars (Artificial Pilots)
Forms of AI
Neural Networks
Artificial Life
AI

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What are Expert Systems?
Knowledge Base
It contains domain-specific and high-quality
knowledge.
Interface Engine
It acquires and manipulates the knowledge from
the knowledge base to arrive at a particular
solution.
User Interface
It provides interaction between user of the ES and
the ES itself.
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Components of Expert Systems
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Human v/s Expert System?
Comparison between an Expert System and Human Expert
Factor Human Expert Expert System
Time Working Days Only Anytime
Geography Local Anywhere
Safety Cannot be replaced Can be replaced
Damages Yes No
Speed and Efficiency Changes Consistent
Cost High Intermediate
Expert system is built on two factors either to replace or help an expert

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Features of an Expert System
Goal Driven Reasoning or Backward chaining
Should have simple reasoning mechanism i.e. If and then rules, frames based
Should be domain specific Quality of advice offered should be on the amount of knowledge stored
Encoding and storage of domain specific knowledge is economic process due to small size
Capable of assigning confidence values i.e. Confidence and Certainty factors

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Advantages of Expert System
Increased timeliness in decision making (24 Hours availability of ES)
Increased productivity of experts
Improved consistency in decisions
Improved understanding and explanation
Improved management of Uncertainty e.g. How tall is tall?
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Disadvantages of Expert System
How do you code common sense
Expertise is difficult to extract and encode
Expert “errors” transferred to model
Human Expert adapt naturally but an ES must be recoded
Human Expert can better recognize when a problem is outside domain knowledge, ES
would not be.
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CRM In Banking Sector – HDFC Bank
Products: Retail banking, Wholesale Banking, Treasury
Customers: 25 million+
Workforce: 55,000+ | Cities/ towns: 2,200+ | Branches: 3,400+ | CRMnext Users: 25,000+
Challenges
Single 360° customer view
Cumbersome process for monitoring of TAT
No banking CRM software implemented, leading to fragmented customer information in various lines
of business and multiple systems
Highly demanding and sensitive managed customer segment

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CRM In Banking Sector – HDFC Bank
Solutions
Single 360° customer view
Online accessibility to customer data for more than 15000 users through an effective banking CRM software CRMnext
Benefits
93% Improvement in sales turn-around-time
92% Increase in customer loyalty index
30% Reduction in average customer complaints
99% Uptime Schedule.
Today, 85 per cent of the transactions by customers takes place though non-branch channels. The mobile and Internet
banking channel contributes almost 55 per cent.

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Automated Teller Machines (ATM’s)
• A common banking example of an Expert System is an ATM machine.
• It performs the actions of an expert in particular domain (i.e. a bank teller) who would
perform when faced with a client requesting a cash withdrawal.
• The inputs required by an ATM system are quite simple like
• Client identification and Service Requests
• In this example, the definition of an Expert System becomes the same as that of an Expert
Model.
• (Client identified + funds in account available + account within limits + funds in the ATM
available + denominations available = Perform transaction).

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Underwriting Expert System Advisor (UESA)
• UESA covers three insurance policies
• i) Motor Vehicle Insurance, ii) Personal Accident Insurance, and iii) Travel Insurance.
• The knowledge-base collected for the UESA proposed consists of a collection of knowledge from
insurance underwriting experts and a website and constitutes a 16 Rule-Based procedure/strategies.
• Expert Systems Artificial Intelligence (AI) helps the Insurance Industry
1. to use computers as Underwriting Expert System Advisors to help customers/clients calculate risks
involved in taking on a particular insurance.
2. Other expert systems developed in the field of insurance helps customers to fill forms of an insurance
policy properly and accurately so that the form will not be rendered useless and the insurance policy
can go on and work out accordingly.
An Underwriting Expert System Advisor for Insurance Policies

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Knowledge-Base for UESA
• The knowledge of the system was collected from underwriting experts and from an insurance website,
www.metinsurance.com
• The main knowledge bases involved in the proposed system design for UESA were Personal Accident,
Motor/Vehicles and Travel Insurance Policies.
• User Requirements
• Users who will use the proposed UESA are most likely to be customers/clients who are seeking insurance policies
from an insurer (insurance company) OR
• Experienced underwriters can use UESA to help them make better and faster decisions about a policy, when a
recommendation is sought from them
Designing of the Required Knowledge-Base for UESA

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Putting Expert System to Work
1. N L Baroid, a drilling services company, created MUDMAN to analyze the drilling fluids, or “muds,”
2. Coopers & Lybrand has an ES called ExperTAX that helps accountants in reviewing the way their clients
accrue taxes and in offering tax planning advice.(3000 rules defined)
3. American Express Company uses an expert system to help its credit authorization staff sort through data
from as many as 13 data bases. The American Express credit card has no set spending limit.
4. The Expert System for Management of Malformation Disease of Mango (ESMMDM) has been developed
to predict the disease occurrence and suggest an appropriate crop protection and pest management
strategy
5. A Hybrid Legal Knowledge Based System named TPA-EXPERT for Indian Legal domain
Harvard Business Review

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The Creator
• Dr. Edward Albert Feigenbaum is a computer scientist working in
the field of artificial intelligence, and joint winner of the
1994 ACM Turing Award.
• He is often called the “Father of Expert Systems.“
• He founded the Knowledge Systems Laboratory at Stanford
University which focuses on expert systems for science and
engineering.

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Artificial Intelligence – BBC News
What is artificial intelligence?
• The objective of Artificial Intelligence is to
replace human intelligence in robots and
systems.
• Human Brain is the most complex object
on this planet.
• Nothing can replace Human Brain.
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