Gamification in Banking

Gamification is a business strategy which applies game design techniques to non-game contexts to drive user behavior.

what is non-game context mean here is some objective other than success in the game like business impact, Social impact, personal improvement etc.

Why Gamification:

Let us look at different areas of it:

It's broadly divided into three areas:

1.External  -  Marketing, Sales, Customer Engagement

2.Internal - HR, Productivity enhancement, Crowdsourcing

3.Behaviour Change - Health and wellness,Sustanibility, Personal finance.

Market segmentation of gamification:

Before moving on applying gamification to banking as a domian our inspiration comes from the positive results it got when applied by many companies with increase of  sales, productivity improvement and health and wellness improvement.

Keeping in mind the positive impact of applying game design techniques in non -game contexts we can apply the same to banking. we are here exploring applying gamification to a bank website where some thousands of customers uses internet banking everyday.  

While considering gamification techniques banking has it's own regulations:

•Record Keeping

•Reserve Requirements

•Currency manipulation

•Anti –fraud

•Money laundering

•Consumer Protection

•Taxation and accounting

We here describe few areas where gamification can be applied in an internet banking website.

Although every bank offers its users some pricing plans that increases the chance of banking with their bank, our gamification techniques  will have a bigger impact.

User login to their internet banking website and how does it will be if user experience of the 

site having points he gained for his accounts maintenance, considering record of paying debts 

within timeline, his awareness on security initiatives by their bank to protect their customers 

information that is part of anti -fraud and money laundering which are serious problems in today's 

world. 

Regular expressions with Python

This is post on getting and writing programs with regular expressions using python as programming language.

There would be many theoretical intro of why do we use regualar expressions. In simple, regex are used for parsing data either in search engine or web scraping.

Regular expressions: The following line of code is the syntax of regex in python.

Regexp<name> = regexp.search()

Before getting into the lines of code let's have a glance at the patterns.

Quick patterns:

[abc]		A single character of: a, b, or c
[^abc]		Any single character except: a, b, or c
[a-z]		Any single character in the range a-z
[a-zA-Z]		Any single character in the range a-z or A-Z
^		Start of line
$		End of line
\A		Start of string
\z		End of string
.	Any single character
\s	Any whitespace character
\S	Any non-whitespace character
\d	Any digit
\D	Any non-digit
\w	Any word character (letter, number, underscore)
\W	Any non-word character
\b	Any word boundary

(…)	Capture everything enclosed
(a|b)	a or b
a?	Zero or one of a
a*	Zero or more of a
a+	One or more of a
a{3}	Exactly 3 of a
a{3,}	3 or more of a
a{3,6}	Between 3 and 6 of a
a{ ,6}	Not more than 6 of a
	For any pattern  : ? – A regex followed by ? implies zero or one of the occurrence *-   A regex followed by *implies Zero or more of the occurrence (Used for optional ) + - A regex followed by + implies one or more occurrence {x, y} – A regex with boundaries repeat itself in between x and y {x, }  - A regex with lower bound is >/ x {, y} – A regex wit upper bound  is  </ y {x} – A regex with exact x times Using # is a comment Using \# in a regexp matches for the character #. . : Matches any character except \n \. : Matches only dot Special case in escape character: For the regexp [-a-zA-Z]: It considers hypen(–) as a character and looks for it. With Python: R with regular expressions in python: Using r ‘regexp’ turns off backslash impact of python in the expression Re library: To work with regular expressions in python we need to import ‘re’ library into our code and is as below: import re If a regular expression looks like this: Pattern = r’^[A-Z][a-z]{2}\d{1,3}\.\d{1,3}\.\d{1,3}\.\d{1,3}$’ It might be difficult to revisit the code and to debug this. Python avoids this with multiline expression using VERBOSE mode. Pattern = r’’’                ^                 [A-Z][a-z]{2} \d{1,3}\.\d{1,3}\.\d{1,3}\.\d{1,3} $                ‘’’ Exp = re.compile(pattern, re.VERBOSE) or Exp = re.compile(pattern, re.X) Simple example code for Regular expression import sys import re address_pattern = r''' ^ (?P<Address1>P\.*O\.*\s*(BOX|Box|box)\s\d{1,5}) # address1 field (?P<City>\s*\w*\W*\s*\w*\W*\s*\w*\W*\s*) # text between address and zip code $ ''' address_reg_exp = re.compile(address_pattern, re.VERBOSE) text = "PO Box 1055 Jefferson City, MO 65102" match = address_reg_exp.search(text) g = match.groups() if match: print match.group('Address1') print match.group('City')