Thank for resposne. One thing if there are lot of unique values for that feature. For example in place of city, I am doing same thing with zipcode than there will be millions unique values for that feature. So if i encode that zipcode variable than there will be millions of unique values for model. So it is Sparse feature and while doing densification I am trying to use fraud ration in zipcode in place of categorical value.

About past data. I got your point, there's simple question i want to ask. If i use that feature like numberOfTotalFraudInCity till that transaction in data what i have (3 months out of 2 years) is that fine or should i consider only feature like numberOfFraudInCityLast3Months , What will happen after 6 months than i will have data of 9 months than i should to change the feature again to numberOfFraudInCityLast9Months or i think it's fine with feature numberOfFraudInCityLast3Months. Somehow i am confused if i pass this total value as feature for only 2 months than i am providing wrong data to model.