Risk refers to uncertainty. Financial risk is the possibility of an asset fluctuating in price due to uncertainty. We sorted out the current entire risk classification, which can be roughly divided into the following categories:
Credit risk
refers to the possibility that the debtor is unable or unwilling to perform the debt and cause losses to the creditor.
Liquidity risk
refers to the possibility of being unable to meet payment obligations due to insufficient liquidity.
Interest rate risk
refers to the possibility of asset price fluctuations caused by the uncertainty of interest rates.
currency risk
It refers to the possibility of asset price fluctuation caused by the uncertainty of exchange rate.
Operational risk
refers to the risk of direct or indirect loss due to imperfect or problematic internal operating processes, personnel, systems or external events.
Legal risk
refers to the validity and enforceability of legal documents such as various contracts and commitments related to financial institutions, including external compliance risks and regulatory risks.
Inflation risk
refers to the risk that inflation will reduce the rate of return of economic entities in the first quarter or increase their financing costs.
Environmental risk
refers to the risks brought about by the natural, political and social changes faced by participants in financial activities.
National risk
refers to the possibility of loss caused by the sovereign behavior of a country in international economic activities.
Among the above risks, Tomato Risk Control is particularly good at credit risk-related content. We understand that risks can bring losses as well as gains. Rejecting risk is tantamount to rejecting corresponding benefits. How to balance risks and benefits requires a quantitative scale, so we introduced the concept of quantitative risk. One of the core purposes of quantitative risk control is to keep the risk at an acceptable level.
How to quantify financial credit risk, if we look at the history of human development, we will find that the major historical human financial events are roughly sorted out as follows:
The history of the financial system is as old as the history of human civilization, and
there have been many outbreaks of systemic financial risks.
1634-1637 Tulip Bulb Craze
1929.10.29 Wall Street Crash
2007 Subprime Mortgage Crisis
1933 Glass-Steagall Amendment Act
1999 Financial Services Modernization Act
2010 Dodd-Frank Act
Accompanied by these major financial processes, people gradually discovered The stable and harmonious development of its finance is inseparable from the regulatory framework, so along with the financial incidents, the Basel Accords were born one after another. There is nothing wrong with it, the Basel Accord was born with financial events, and its main mission is to prevent the collapse of the financial system:
•1988 Basel Accord I (from 1974)
•1992-1996 Basel Accord Amendment
•2005 Basel Accord II
•2009 Basel AccordII. 5
•2010-2024 BaselAccord III (with FRTB etc.)
Looking at the quantitative risks of the Basel Accord, its evolution has also evolved to the third version, Basel Accord III. Just as risks need to be dispersed, risk management also needs to be supported by concerted efforts. There will still be serious risks in relying on industry self-discipline alone.
The three pillars of the Basel Accord:
Pillar 1: Minimum capital constraints/liquidity constraints
Pillar 2: Strict supervision/bank internal control and capital planning
Pillar 3: Strengthening information disclosure/market discipline
and understanding of the Basel Accords After the logic, you will understand that one of the most important things is to classify assets. In the financial field, we have a more professional term called: asset pooling.
Pooling refers to putting homogeneous debts with similar risk characteristics into the same portfolio or asset pool (Pooling), and unanimously estimating the Basel risk parameters of the asset pool, including the probability of default (hereinafter referred to as "PD"), default Loss rate (hereinafter referred to as "LGD") and default risk exposure (generally refers to credit cards, including EAD and CCF). The above are the three types of credit pool division scenarios: PD, LGD, EAD pool division.
Of course, in common credit scenarios, it is more divided by product. Taking credit assets as an example, the three elements of credit risk are calculated separately for each non-retail loan. Retail loans are divided into three categories under standard circumstances:
1. Mortgage loans (Mortgage)
2. Qualified revolving retail loans
3. Other types of non-accounts receivable
asset pools are the most common for bank students to do this kind of related business problems encountered. What tools are commonly used for pool splitting? Can conventional algorithms such as decision trees and logistic regression be used? In addition, are there any relevant case introductions related to pool division? Has anyone answered the above questions?
I hope that everyone can understand the above content and not panic.
For more reporting content of these indicators, please pay attention to:
~Original article
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