Association Rules- An exercise

An Insurance Company is planning to launch a new Insurance product in the market by packaging some of the add-ons it had been offering in it’s motor Insurance policies. It has listed out following five add-ons for this exercise.

a) Depreciation waiver benefit
b) Daily cash allowance while the car is under repair
c) Cover for personal luggage loss
d) On road assistance to car and car passengers
e) Medical Extension.

From the records, following number of incidences of various combinations of add-ons is found.

f(a) = 489, f(b) = 823, f(c) = 56, f(d) = 372, f(e) = 649, f(a,b) = 682, f(a,c) = 68,
f(a,d) = 532, f(a,e) = 89, f(b,c) = 312, f(b,d) = 279, f(b,e) = 24, f(c,d) = 52, f(c,e) = 10,
f(d,e) = 189, f(a,b,c) = 227, f(a,b,d) = 295, f(a,b,e) = 378, f(a,c,d) = 1, f(a,c,e) = 10,
f(a,d,e) = 512, f(b,c,d) = 2, f(b,c,e) = 13, f(b,d,e) = 187, f(c,d,e) = 10, f(a,b,c,d) = 0, f(a,c,d,e) = 5, f(b,c,d,e) = 2, f(a,b,d,e) = 198, f(a,d,c,e) = 4, f(a,b,c,d,e) = 85.

Here f(x,y,z) means number of policies in which add-ons x,y and z have been taken and remaining add-ons have not been taken.

You work on these data to find some association rules. The association rules will be in following form:

“A person opting for add-ons x,y is likely to opt for w as well”.

Let us call the first set i.e. x,y as current set and the second set w as associated set. There can be any number of add-ons from a,b,c,d,e in these sets. An add-on cannot be in both the sets.

Let there be a threshold value and a threshold probability for accepting an association as association rule. Threshold value is the minimum number of incidences for current set and the threshold probability is the minimum probability of someone taking the associated set add-ons if he has taken the current set add-ons.

For this exercise take the threshold value as 2000 and the threshold probability as 0.4.

If you need any clarification, please ask that as comment to this post.

Optimizing logic operations

Below link takes you to a page where you get study material on Logic operations. Concepts discussed here are close enough to that discussed in the class.
http://www.facstaff.bucknell.edu/mastascu/eLessonsHTML/Logic/Logic3.html

After understanding that try this question:

Question: A life insurance company decides to gift its customers as part of its CRM initiative. It wants to use following data for deciding the gift to be given to a customer.

A) Number of years of regular premium payment more than 4 years
B) Annual premium amount not less than Rs. 16000
C) Education level of the customer at least Master and
D) Annual income of the policy holder at least Rs 700000

If the condition B and any two or more of remaining conditions are satisfied the customer qualifies for "High Valued Customer" gift.
If the condition A and at least one of the remaining conditions are satisfied the customer qualifies for 'Valued Customer' gift.
Customers qualifying in both the above categories will get the higher of the two gifts that is 'High Valued Customer' gift only.

Derive logic expressions for each of the categories (High valued customer and Valued customer) that will generate the list of customers qualifying in that category.

Algorithm in Nature

This post is of general interest. May be understood as per the interest level. It may be interesting to note that mathematical algorithms are present in nature everywhere and derive that such algorithms can be used in automating many intelligent functions. Have a look at

http://www.mcs.surrey.ac.uk/Personal/R.Knott/Fibonacci/fibnat.html

Managing BI Implementation Project

CPM/PERT provides useful insight in the project and helps in managing that. Actvities breakdown structure should be prepared for the BI implementation project and the CPM/PERT should be applied.

Some useful information on this techniques and its implementation using excel is available at the following link:

http://hadm.sph.sc.edu/courses/J716/CPM/CPM.html

Data Mining Tutorial

Those who are comfortable with Mathematics and Statistics may enjoy data mining tutorial here.

http://www.autonlab.org/tutorials/

Business Intelligence

This site contains various readings about business intelligence including white papers, articles, community content etc.

http://businessintelligence.ittoolbox.com/topics/

Some readings on BI in Insurance

Those who are interested in knowing how some of the Insurance companies are using business intelligence, may like to read few pages from

http://www.informationbuilders.com/solutions/insurance.html