Concepts - WeightofEvidence, Information Value

While checking on FinTech ML projects I came across these two concepts WeightofEvidence, Information Value. I found this link intuitive and understanding.

Basically when we bucketize, within each range of buckets we can, in turn, sub-divide the other factors based on distribution. In Retail Scenario

Customers Age Group (20-30, 30-40, 40-50). Within each bucket, we can find the percentage of fraudulent customers. It may be

20-30 - 4% fradulent
30-40 - 2.5%
40-50 - 1%

This technique helps to assign possible values and decide their impact. This is my understanding. We can also infer the same based on data analysis and distribution percentages across different classes.

More Reads - Link1, Link2, Link3, Link4

Happy Learning!!!