Training On Risk Analytics and Management

Financial risk management is the practice of protecting economic value in a firm by using financial instruments to manage exposure to risk: operational risk, credit risk and market risk, foreign exchange risk, shape risk, volatility risk, liquidity risk, inflation risk, business risk, legal risk, reputational risk, sector risk etc. Financial risk management can be qualitative and quantitative, which requires identifying its sources, measuring it, and plans to address them.

Among these, credit risk and market risk are the most important sectors in many financial institutions and telecom companies. A credit risk is risk of default on a debt that may arise from a borrower failing to make required payments, and a market risk is the risk of losses in positions arising from movements in market prices.

To help people step into this career, SparkData Ltd. and YIFA Management Group collaborate together to provide training programs in credit risk and market risk. These programs will train you with the required skill set, domain expertise and industry knowledge quickly. All our instructors have Master or PhD degrees with over 10 year working experience in government and financial industry.

Below are the brief outlines of these joint programs by SparkData and YIFA Management Group.

Interested? Questions? Please contact us for details: info@sparkdata.ca

Credit Risk Analytics and Management

Program Requirements:

  • Bachelor or higher education in Maths, Statistics, Finance, Science, Engineering.
  • Able to program with one of the SAS/SQL/R/Python analytic tools.
  • Previous experience in big data analytics is preferred.

Customer marketing and customer risk management are both important business sectors in financial, telecom, insurance and other industries. What is credit risk and how can we manage the business risk effectively?

This project will give you the fundamental knowledge, methodologies and skills in credit risk analytics and management, such as:

  • Credit risk and risk scorecard models. 
  • Credit score components and usages.
  • Validate the performances of credit risk models and scores with decile/twentile analysis, odds chart, lift curve, cumulative gains chart, KS, ROC, AUC, GINI etc.
  • Calculate expected loss with risk management KPIs such as PD, EAD, LGD etc.
  • Implement credit risk scores to management financial portfolio and mitigate risk losses.

Project Description

  • Quickly gain the domain knowledge and practices of of credit risk industry.
  • Hands-on experience on quantitative credit risk analyses by using SAS/R/Python programming.
  • Grasp the knowledge, technique and skills in credit risk analytics.
  • Develop business insights and analytical thinking by working on the challenging project and give oral presentations in class as well.

Learning from working is the best way for grasping real work skills. Through this project,  you can gain the domain knowledge, business insights and technical skills quickly, and start a career in the credit risk field.

Market Risk Analytics with Python

Program Requirements:

  • Bachelor, Master or PhD degree in Maths, Statistics, Finance, Science, Engineering with a strong interest into finance, or MBA with quantitative analysis backgrounds.
  • Working professionals who would like to change career path into market
    risk field.
  • Python programming is preferred.

Market risk can be measured by Value at Risk (VaR), Sensitivities and Stress Testing.  VaR is the main tool for market risk management in financial institutions.

The highlight will be hands on experience for students to master VaR methodology by working on a VaR project for your own selected stock portfolio in different projects.

Project Description

  • Learn market risk concepts and metrics including VaR, Sensitivities, and Stress Testing.
  • Build risk models to calculate parametric, historical and Monte Carlo VaR by automatically extracting stock price data from Yahoo Finance in Python.
  • Implement European option pricing model in Black Scholes and its Greeks. Design risk report for stock investment portfolio.
  • Develop and automate risk report using Python and Excel.

Project Benefits

  • Quickest way to learn how banks report and manage market risk.
  • Gather reporting business requirement from the instructor and reflect the
    requirements in reports.
  • Project can be presented in job hunting or an interview.
  • Enhance extensive knowledge on metrics including VaR, Sensitivities
    (Delta, Gamma, Vega), Stress Testing.
  • Using Python and Excel to complete automation and reporting.

At the end of the training, students will finish their own applications on parametric, historical, & Monte Carlo VaR, European option pricing and Greeks in Black Scholes, and Stress Testing.

Contact Us

Contact us today so that you can start in the right direction towards your dream job, and learn how we can tailor our services to help you get there. Please email us:  info@sparkdata.ca

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