2015 Summer projects- SAS credit risk project summary

SAS Credit Risk Project

Designed & led by Financial Math Alumnus- Jonathan Leonardelli

Objective:
For students to apply credit risk concepts while developing SAS programming skills

Goals:
1. Become Base SAS certified
2. Have an understanding of CCAR and Basel II calculations
3. Learn how to model PD / LGD / EAD
4. Use equations to calculate Expected Loss (EL), RWA (Risk Weighted Assets), and capital ratios

By Aisha Barnes & Preethi Kankanala- The purpose of the summer SAS case study was to develop an understanding of the different steps that are involved in calculating the loss portion of CCAR (Comprehensive Credit Analysis & Review). CCAR is a regulatory framework that ensures Bank Holding Companies (BHCs) have enough capital under the worst scenarios. This is tested under various stress-testing scenarios.

In our case study, we analyzed a portfolio of different products and estimated the capital that is required to hold the portfolio under three different scenarios. For this, we have estimated the historic Probability of Default (PD)*, Loss Given Default (LGD)* and Exposure at Default (EAD) and forecasted the future values using a variety of techniques (e.g., regression models) in SAS. Then we used these values to estimate risk weighted assets and capital.

This exercise helps BHCs ensure that they have enough capital if there is any change in the economic conditions. If the capital plan does not pass regulatory review, then the company has to change it to ensure there is adequate regulatory capital.

"Throughout the project, Financial Math Alumnus and Board Member, Jonathan Leonardelli, directed and mentored our team. We gained knowledge and enhanced our technical and business skills under his guidance. The project provided us hands-on experience on estimating the credit metrics and how to apply them with real world problems."- Preethi Kankanala, December 2015 Graduate

"This summer I experienced real application of how I will use my Financial Mathematics degree. I learned how to program in SAS and plan to gain certification. I used SAS to find the amount of capital a bank reserves to meet the Basel II requirements. I feel confident in having these skills."- Aisha Barnes, December 2015 Graduate

*PD (Probability of Default) = likelihood that a loan will default in the future
*LGD (Loss Given Default) = amount a bank will lose if a customer defaults on their loans

(All the project groups presented their summaries at the end of the summer session. More info to come soon from the other groups).

Financial Math Alumni Panel Discussion on Big Data, High Frequency Trading and more…

(Above left to right- Jeff Scroggs, Jonathan Leonardelli, Jared Bogacki, Ryan Wesslen, Albert Hopping, Emmanuel Sanchez)

Jeff Scroggs, Director of the Financial Mathematics Program, conducted a panel of industry experts on trends in financial mathematics and quantitative risk.  Three of the practitioners,  Jared Bogacki (BB&T),  Jonathan Leonardelli (Financial Risk Group), and Emmanuel Sanchez (Allianz), were from the class of 2004 – the first class to graduate with a Masters of Financial Mathematics.  Two of the panelists,  Albert Hopping (SAS Institute, class of 2007) and Ryan Wesslen (Bank of America, class of 2009), were more recent graduates.

The panel offered the audience an opportunity to see what role quants play in optimal business practices.

All the panelists agreed that their Masters of Financial Mathematics from NC State opened opportunities for career advancement, ranging from a entry-level quant positions to promotions to lead quant.

Jared Bogacki started with the topic of 'Big Data'.  'Big Data' is the use of data sets so large and complex that it has become difficult to process them using traditional tools or data processing applications.  It is currently a hot specialization for quants, and will likely remain a sector of the job market that is hungry for well-qualified people. 'Big Data' is a broad term that covers several topics including analytics used to glean market sentiment as well as some aspects of high frequency trading.