I work with SAS Analytics solutions, specifically with SAS Data Mining, because I extract information from the core system of the bank via ODBC connections and use SAS Base on the servers. I am the admin of the servers of SAS Analytics for all risk and I use SAS Base and SAS Enterprise Guide, the client version, and Miner. In fact, I do the maintenance of Miner. For example, in some cases the server was reset and all services on the server were not running correctly. Then I manually put the reset of Miner in order. With this, Miner is available for all the teams of risk. For a model, for example, the area, in particular model build, in risk, uses SAS Miner many times. For the strategy of the areas of collection, for example, they make a train, Random Forest, and some types of segmentation models for the strategies.
Finance Business Intelligence at Banco Santander Mexico SA Institucion de Banca
Real User
Top 10
Mar 28, 2025
I use SAS Analytics ( /products/sas-analytics-reviews ) in my work to analyze data, such as selecting credits for traditional securitization. Recently, I used SAS Analytics ( /products/sas-analytics-reviews ) for the project roster from Santander, selecting and evaluating credits, and conducting historical research on the reception of contracts to issue securitization. I don't use machine learning models but focus on analytics processes and report creation using macros.
Global Data Architecture and Data Science Director at FH
Real User
ModeratorTop 5
Feb 24, 2021
We use SAS Analytics for all data analysis, quick exploratory data analysis, statistical analysis, predictive modeling, and rapid data management in risk analytics. Predominantly, we're using risk analytics, but I plan to extend it to marketing and other departments as well. The primary focus here is risk analytics and portfolio management in this organization. But in the past, I have used it in various industries for numerous use cases like demand forecasting, inventory management, customer relationship management, strategic analytics, M&A, HR analytics, business intelligence, and analytical data marts. I have also used SAS extensively for developing risk scoring models, model risk management, collection analytics, and marketing analytics very effectively for banking and financial services.
SAS Analytics offers a powerful suite of tools for statistical analysis, predictive analytics, and data handling, making it ideal for industries requiring robust data-driven decisions. Its extensive capabilities cater to professionals familiar with SQL and demand forecasting needs across sectors. With a strong presence in analytics, SAS Analytics provides a seamless experience for data preparation, exploration, and reporting. Users benefit from its ability to handle large data sets, generate...
I work with SAS Analytics solutions, specifically with SAS Data Mining, because I extract information from the core system of the bank via ODBC connections and use SAS Base on the servers. I am the admin of the servers of SAS Analytics for all risk and I use SAS Base and SAS Enterprise Guide, the client version, and Miner. In fact, I do the maintenance of Miner. For example, in some cases the server was reset and all services on the server were not running correctly. Then I manually put the reset of Miner in order. With this, Miner is available for all the teams of risk. For a model, for example, the area, in particular model build, in risk, uses SAS Miner many times. For the strategy of the areas of collection, for example, they make a train, Random Forest, and some types of segmentation models for the strategies.
I use SAS Analytics ( /products/sas-analytics-reviews ) in my work to analyze data, such as selecting credits for traditional securitization. Recently, I used SAS Analytics ( /products/sas-analytics-reviews ) for the project roster from Santander, selecting and evaluating credits, and conducting historical research on the reception of contracts to issue securitization. I don't use machine learning models but focus on analytics processes and report creation using macros.
This is an application I use for data prep, data exploration, BI reporting, and some basic automated analytics.
We use SAS Analytics in the area of Business Intelligence (BI), particularly for analyzing data and generating reports.
Our use case involves leveraging SAS Analytics to support experts in various departments such as collections and customer analysis.
Our number one use case for SAS Analytics is data analytics. We have about 50 data analysts on our team who are currently using it day in and day out.
We use SAS Analytics for all data analysis, quick exploratory data analysis, statistical analysis, predictive modeling, and rapid data management in risk analytics. Predominantly, we're using risk analytics, but I plan to extend it to marketing and other departments as well. The primary focus here is risk analytics and portfolio management in this organization. But in the past, I have used it in various industries for numerous use cases like demand forecasting, inventory management, customer relationship management, strategic analytics, M&A, HR analytics, business intelligence, and analytical data marts. I have also used SAS extensively for developing risk scoring models, model risk management, collection analytics, and marketing analytics very effectively for banking and financial services.
Our primary use case is analytics and reporting in our production area.
We use this solution for CRM and retention marketing.