Each bank has a lot of different verticals. Before, for each and every vertical, they had to implement a different fraud solution. Presently, the main purpose of SAS is to maintain a centralized platform for all of the verticals — like agriculture, NSME, and home loans. For each and every vertical, they created a centralized platform where the bank can monitor everything from one system. That is the main purpose of SAS Fraud Management.

It is a little bit costly. Otherwise, it's pretty good. Suppose you are going to create a data science model or an analytical model. With Python, you have to write long subcodes, but with SAS, you just have to drag and drop those things. If you know all of the logic and all of the theories, then it's a very comfortable tool to use.

The security is also very good. That's why most of the industry is adopting SAS. Data security is very good because the Reserve Bank of India has approved it. That said, almost all the banks are now implementing SAS as an all-in-one solution.

The solution is easy to use. 

It's pretty stable in terms of performance. The performance overall is very good. 

The solution can scale well.

The initial setup is pretty easy. It's not too difficult.