The Quantitative Risk Analytics Professional (QRA) is a 3 month advanced certification program by Ivy Professional School co-designed with Genpact aimed at creating a pool of data scientists with expertise in handling complex financial data with the help of advanced level statistical modeling and risk analytics tools. This first of its kind Industry-academia collaboration has curriculum designed in collaboration with Genpact. (Read more about Genpact & Ivy Professional School partnership here). Analytics India Magazine reviewed our course (Read here)
What you get
Genpact and Ivy Pro School come together for a unique collaboration especially focused on Quantitative Financial Risk Analytics.
The course has been designed in close collaboration with Genpact’s Senior Risk Practitioners. During the course of the program, students are constantly monitored and mentored by them.
Weekend delivery ensures that you don’t have to leave your current job to join this course
Hands on Learning on real life projects using Advanced Analytical tools (SAS and R) and latest models used in Risk Analytics.
Opportunity to work with Genpact and other large Analytics firms as a level 2 Risk Analyst.
- Statistics for risk modeling using SAS
- SAS programming (base SAS and Advanced SAS)
- Credit Risk foundation
- Risk Modeling fundamentals: Predictive Analytics
- Risk Modeling fundamentals : Deep dive
- Model validation – regulations’ context
- Credit Risk – Overview of Basel Norms
- Credit Risk – Setting up and Building Models, estimating LGD, EAD
Who should Attend
Data Analytics professionals who want to make their next big move to mid-level financial risk analytics roles
What is Quantitative Financial Risk Analytics?
Quantitative Financial Risk Analytics involves the use of quantitative models, statistical methods, numerical algorithms, and software to address the challenging and important issues associated with big financial data. It includes:
- Credit Risk Analytics
- Operational Risk Management
- Regulatory compliance
- Capital planning and forecasting
- Fraud Analytics, and
- Market Risk Analytics