Credit Risk Introduction

Must read book: Introduction to Actuaries and Actuarial Science
www.amazon.com/dp/B0C699MHDH
these videos go through the syllabus objectives for the Financial Exams of ST5/F105/SA5/F205. They are raw, unedited and contain a large amount of opinion. I've taken a skeptical approach to the subject and my views may not be correct. Feel free to correct me in the comment section below. I'll be releasing a new video every day
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[@MJtheFellowActuary]

I've released New Course on Credit Risk, Market Risk, Capital, Copulas and other ERM topics: Click the Link www.udemy.com/course/theory-of-credit-risk-models/?referralCode=67C9ADA77C3EE60F0BE3

[@katlegozabala123]

your ability to make the content relatable is invaluable man, thank you

[@jeremiahdeborah1395]

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[@YeahBuddy]

This is a very well done video. I would say late payments are a variable that would be used to calculate the probability of default. This is why late payments often lower a person’s credit score. Looking forward to watching more!

[@nomuntu]

great ability to explain!!!!

[@nyaka4272]

Thanks so much...great explanation

[@TheCutestEvil]

great explanation !! thank you! As a beginner in this field, it has really helped me understand basics.

[@jeremiahdeborah1395]

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[@martalena6053]

You are awesome! Please continue this great job!!!

[@MJtheFellowActuary]

Thank you so much!! :-)

[@1996JRC]

Cheers for the videos - very well explained. Would you consider doing one on calculating the matching adjustment for a given portfolio of assets?

[@rasrahmani3087]

Great explanations. Thanks mate!

[@lebogangmoichela7879]

You, Sir, are brilliant.

[@Griffatron3000]

Very well explained, thanks

[@tlhogid663]

Awesome video

[@Adam-vp4oe]

Hi MJ, I wanted to make a complimentary comment to your conundrum mentioned at 5:30 forward. Categorizing for probability of default (or PD) is illegal in most countries in most fashions. In the US it can be considered redlining or against UDAAP. Most of PD is based on many factors but mostly the Debt Service Coverage Ratio which is different for corporates than individuals but can be googled for formula. This basically looks at excess cash from income after sole expenses to service the cumulative debt payments. The loss if defaulted is usually based on the loan to value of collateral taken. The quality of these ratios are then typically ranked into grades and each grade can reflect a percentage of loss likelihood or loss percentage after collateral sold. I hope that give some insight on the micro scale of credit modeling. I really enjoy your video going over the macro view. It's very insightful.

[@MJtheFellowActuary]

+Adam Cogan thank you so much for this comment. These videos are essentially me studying out loud and trying to wrestle with the concepts and idea. I really appreciate your response

[@Adam-vp4oe]

It is very enlightening is something I hope to work my way up into, I'd like to be a "quantitative/qualitative credit risk modeler". Are you studying mathematics or does your college have an actuary program?

[@MJtheFellowActuary]

I studied at Wits and fortunately we had a dedicated Actuarial Program :-)

[@rowansiddig9043]

Hi MG and Adam .. I have to develop a credit risk assessment system. I do not know anything about this topic. I need you to guide me with all books, videos, scientific papers and articles. Thanks for this video

[@jcn268]

interesting , never knew there was this much philosophy in actuarial science

[@Obi1Kenobiii]

Hi MJ, can I ask you what program are you using to draw this presentation?

[@sathishbandolero]

Thank you

[@Kaplanel]

hello, thank you. Could you please suggest me a book related to credit risk assessment? thanks

[@MJtheFellowActuary]

Enterprise Risk Management by James Lam

[@Kaplanel]

MJ the Student Actuary hello, thank you but I am looking for something that focus on credit risk management. could you suggest me smt ? thanks..

[@DeepakSharma-ho4eq]

@@Kaplanel advanced credit risk analysis and management Ciby Joseph Publisher Wiley Finance

[@rishabhs4956]

Awesome!! 💚💚💚

[@chitalusooka4978]

thank you

[@llamabridge2962]

This was awesome

[@reachDeepNeuron]

my question is when we have credit score of each customer , is that not sufficient to sanction his loan .. Why do build a predictive model ?

[@jeremiahdeborah1395]

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[@vaquezartup365]

Our lecturer wrote Risk index ={[E(ROA)+CAP] \ ROA } Wat is it about Do you have a tutorial on it

[@TheMcallist1]

Hi MJ, great video. Thanks. I was just wondering what app you use to make the videos? Thanks

[@MJtheFellowActuary]

I'm just using SNote on the Samsung Tablet along with a Screen Recorder :-)

[@TheMcallist1]

Thanks MJ

[@phantomdevil8096]

What's your great nation bro

[@yuxichen8661]

Is systemic and systematic risk the same thing?

[@MJtheFellowActuary]

No! Despite their similar spelling, it’s easy to confuse them

[@yuxichen8661]

@@MJtheFellowActuary oh thanks for your answer, may I ask what’s the difference between them exactly?

[@apextamang2009]

the paradox is u can tell the bank are shit . but they are the people who are expert in credit lending .so they are taking also a fee. and we need them

[@stefanosa5050]

Can probability of default be zero?

[@jeremiahdeborah1395]

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[@MJtheFellowActuary]

Theoretically yes, practically no. The future is uncertain and so there is always a chance (no matter how small) that the loan isn’t repaid no matter how creditworthy the borrower is.

[@TheWayofWyrd]

Rubbish