The Dynamic Time Warping Method for Clustering

The method is similar to that used in the translation of transactions. It relies on a technique called dynamic time warping, which can be useful for feature engineering. When you have enough data it's really important to use elestem and an about dynamic time war actually, it's an old technique. And when you look at the results you're getting back, can you think of ways that the bank might make them actionable? What could this lead to? Is it for promotion or better customers service? How can they use the insights?