Analytics in a Big Data World: The Essential Guide to Data Science and its Applications

CHAPTER 8 Example Applications

Analytics is hot and is being applied in a wide variety of settings. Without claiming to be exhaustive, in this chapter, we will briefly zoom into some key application areas. Some of them have been around for quite some time, whereas others are more recent.

CREDIT RISK MODELING

The introduction of compliance guidelines such as Basel II/Basel III has reinforced the interest in credit scorecards. Different types of analytical models will be built in a credit risk setting.¹ A first example are application scorecards. These are models that score credit applications based on their creditworthiness. They are typically constructed by taking two snapshots of information: application and credit bureau information at loan origination and default status information 12 or 18 months ahead. This is illustrated in Figure 8.1.

Figure 8.1 Constructing a Data Set for Application Scoring

Table 8.1 provides an example of an application scorecard.

Table 8.1 Example Application Scorecard

Characteristic Name	Attribute	Points
Age 1	Up to 26	100
Age 2	26−35	120
Age 3	35−37	185
Age 4	37+	225
Employment status 1	Employed	90
Employment status 2	Unemployed	180
Salary 1	Up to 500	120
Salary 2	501−1,000	140
Salary 3	1,001−1,500	160
Salary 4	1,501−2,000	200
Salary 5	2,001+	240

Logistic regression is a very popular application scorecard ­construction ...