Risk Management

Basics of Financial Engineering | 2025.02.15

Risk Management is a systematic process through which financial institutions and investors identify, assess, and control various uncertainties and risks they face. It is a key element for the stability and sustainability of modern financial systems.

The importance of risk management has become even more pronounced since the global financial crisis in 2008, prompting financial institutions to establish complex risk management systems, while regulators have introduced stricter risk management standards.

On this page, we will explore various types of financial risks, quantitative risk measurement methodologies, effective risk management strategies, regulatory frameworks, and the latest developments in risk management.

1️⃣ Basic Concepts and Classification of Financial Risk

Risk can be defined as the possibility of deviation between expected and actual results, and in financial markets, this uncertainty manifests in various forms. Financial institutions and investors focus on effectively measuring and managing risk rather than completely eliminating it.

Definition and Characteristics of Risk

Basic Concept of Risk

• Definition of Risk
  In finance, risk is defined as the possibility of unexpected loss or the possibility of deviation from expected returns.

• Difference Between Risk and Uncertainty
  Risk refers to a situation where the probability distribution of outcomes is known, while uncertainty refers to a situation where the probability distribution itself is unknown (as distinguished by Frank Knight).

• Duality of Risk
  Risk encompasses not only the possibility of loss (downside risk) but also the possibility of greater than expected gains (upside risk).

• Relationship Between Risk and Return
  Generally, higher risk is associated with higher potential returns, and this risk-return trade-off is a core concept of financial theory.

Major Types of Financial Risk

The risks faced by financial institutions and investors can be broadly classified as follows:

Market Risk

Market Risk

• Definition
  It refers to the potential for the value of investments to decline due to fluctuations in market prices or interest rates.

• Key Components

  1. Equity Risk: Risk associated with fluctuations in stock prices.
  2. Interest Rate Risk: Risk arising from changes in interest rates.
  3. Foreign Exchange Risk: Risk resulting from changes in foreign exchange rates.
  4. Commodity Risk: Risk due to fluctuations in the prices of raw materials.
  5. Volatility Risk: Risk arising from changes in market volatility itself.

• Measurement Methodologies
  Market risk is primarily measured through Value at Risk (VaR), Expected Shortfall (ES), beta, sensitivity analysis, and other methods.

Credit Risk

Credit Risk

• Definition
  It refers to the possibility that a counterparty will fail to meet its contractual obligations (default risk) and the associated risk of loss.

• Key Components

  1. Default Risk: The risk that a borrower will not be able to repay the principal or interest on a loan or bond.
  2. Downgrade Risk: The risk of a decline in the value of securities due to a downgrade in the issuer's credit rating.
  3. Spread Risk: The risk that the credit spread (the difference from risk-free interest rates) will widen.
  4. Recovery Rate Risk: The uncertainty regarding the amount that can be recovered in the event of a default.

• Measurement Methodologies
  Credit risk is measured through credit ratings, probability of default (PD), loss given default (LGD), exposure at default (EAD), and credit VaR, among others.

Liquidity Risk

Liquidity Risk

• Definition
  It refers to the risk of not being able to buy or sell an asset in a timely manner at a fair price, or of not being able to secure the funds necessary to meet obligations.

• Key Components

  1. Market Liquidity Risk: The risk of being unable to buy or sell an asset without a significant price discount.
  2. Funding Liquidity Risk: The risk of being unable to procure necessary funds.
  3. Contingent Liquidity Risk: The increased liquidity demands due to unforeseen circumstances (e.g., credit rating downgrade).

• Measurement Methodology
  Liquidity risk is measured using methods such as bid-ask spreads, turnover ratios, liquidity-adjusted VaR, liquidity coverage ratio (LCR), and net stable funding ratio (NSFR).

Operational Risk

Operational Risk

• Definition
  It refers to the risk of loss resulting from inadequate or failed internal processes, people, systems, or external events.

• Key Components

  1. Process Risk: Errors in business procedures or control failures
  2. Human Risk: Employee mistakes, fraud, illegal activities
  3. System Risk: IT system failures, cybersecurity threats
  4. External Event Risk: Natural disasters, terrorism, external fraud
  5. Legal Risk: Lawsuits, contract breaches, regulatory violations

• Measurement Methodology
  Operational risk is measured through methods such as Basic Indicator Approach (BIA), Standardized Approach (SA), Advanced Measurement Approach (AMA), Key Risk Indicators (KRI), and loss data analysis.

Other Major Risk Types

Additional Risk Types

• Model Risk
  This is the risk arising from inaccuracies, errors, or inappropriate application of financial models. It can occur in complex derivatives pricing, risk measurement models, etc.

• Legal and Regulatory Risk
  This is the risk associated with changes in laws, regulatory tightening, or violations of regulations. The financial industry is continuously exposed to an evolving regulatory environment.

• Reputational Risk
  This is the risk of financial loss due to damage to a company's reputation. It can lead to loss of customer trust, decline in brand value, and more.

• Strategic Risk
  This is the risk arising from poor business decisions, inadequate strategy execution, or failure to respond to industry changes.

• Country Risk
  This risk arises from the political and economic situation of a specific country, including political risk, sovereignty risk, transfer risk, and more.

• Settlement Risk
  This is the risk that one party in a financial transaction pays the agreed value but does not receive that value from the other party.

Systematic Risk and Unsystematic Risk

Classification Based on Risk Diversification Potential

• Systematic Risk

  • A type of risk that affects the entire market and cannot be eliminated through diversification.
  • Examples of systematic risk include economic recession, interest rate fluctuations, and inflation.
  • This is related to market risk, measured by the beta (β) of a market portfolio.

• Unsystematic Risk

  • A type of risk unique to a particular company or industry that can be reduced through diversification.
  • Examples of unsystematic risk include changes in management, product failures, and labor disputes.
  • These risks can be minimized through efficient portfolio construction.

To effectively manage financial risks, it is important to systematically identify these various types of risks and apply appropriate measurement methods and management strategies for each. The next section will take a closer look at quantitative risk measurement methodologies.

2️⃣ Quantitative Risk Measurement Methodologies

In order to effectively manage risk, it is essential to accurately measure it first. Modern financial institutions utilize a variety of quantitative techniques to assess risk, and these methodologies are employed in various decision-making processes such as portfolio composition, capital allocation, and risk limit setting.

Traditional Risk Measurement Indicators

Basic Risk Measurement Methods

• Standard Deviation
  This is the most fundamental indicator for measuring the variability of returns, representing the average deviation from the expected return:

  σ = √[Σ(r_i - μ)² / n]

  Here, ( r_i ) represents the return for each period, ( \mu ) is the average return, and ( n ) is the number of observations.

• Beta
  It is a measure that assesses the market sensitivity of an individual asset or portfolio, indicating systematic risk:

  β = Cov(r_i, r_m) / Var(r_m)

  Here, r_i represents the return of asset i, and r_m represents the market return.

• Downside Risk Measurement

  1. Semi-variance: Variance considering only the returns below the average return
  2. Downside Deviation: Standard deviation of returns that fall below the Minimum Acceptable Return (MAR)
  3. Maximum Drawdown: The largest percentage drop in value from the peak to the trough

Value at Risk(VaR)

Value at Risk(VaR)

• Definition
  VaR is a measure that estimates the maximum loss that could occur over a specified period at a given confidence level:

  Prob(Loss > VaR) = 1 - confidence level

  For example, if the 1-day VaR at a 95% confidence level is $1,000,000, the probability of incurring a loss greater than $1,000,000 in a single day is less than 5%.

• Calculation Methods

  1. Historical Simulation Method.
     This method uses historical data to generate a profit and loss distribution, from which the specified percentile is derived as VaR.

  2. Parametric Method (Variance-Covariance Method)
     This method assumes that returns follow a normal distribution and calculates VaR based on the mean and standard deviation.

  VaR = -μ + zα × σ

  Here, zα is the α percentile of the standard normal distribution.

  3. Monte Carlo Simulation Method
     This method generates numerous scenarios of market variables using a probabilistic model, from which it derives a profit and loss distribution to calculate VaR.

• Limitations of VaR

  1. VaR does not provide information about worst-case scenarios (tail risk).
  2. VaR can underestimate risk in extreme market conditions.
  3. VaR only considers downside risk and does not distinguish between different sources of risk.
  4. The results can vary significantly depending on the methodology used for calculation.

Expected Shortfall(ES, or Conditional VaR)

Expected Shortfall(ES)

• Definition
  ES is the conditional expected loss exceeding VaR, providing better information regarding extreme loss scenarios:

  ES = E[Loss | Loss > VaR]

• Calculation Methods

  1. Non-parametric Method
     Calculate the average of all losses exceeding VaR from historical or simulation data.
  2. Parametric Method
     Under the assumption of a normal distribution:

     ES = -μ + σ × φ(zα) / (1 - α)

     Here, φ denotes the probability density function of the standard normal distribution.

• Advantages

  1. ES provides information about tail risk.
  2. ES offers a more conservative metric for downside risk compared to VaR.
  3. ES is a consistent risk measure that satisfies subadditivity.

• Applications
  Basel III recommends the use of ES instead of VaR for measuring market risk, and many financial institutions are utilizing ES for internal risk management.

Stress Testing and Scenario Analysis

Stress Testing and Scenario Analysis

• Stress Testing
  A technique for assessing the vulnerabilities of a portfolio or institution under extreme but plausible market conditions.

  Key Types:

  1. Sensitivity Analysis: Evaluation of the impact of changes in a single risk factor.
  2. Scenario Analysis: Evaluation of the impact when multiple risk factors change simultaneously.
  3. Reverse Stress Testing: Identification of scenarios that lead to a specific level of loss.

• Historical Scenarios
  Reproducing actual events such as past financial crises (e.g., the 1987 stock market crash, the 1997 Asian financial crisis, the 2008 global financial crisis) to assess the potential losses of the current portfolio.

• Hypothetical Scenarios
  Testing based on possible, yet unexperienced, market conditions. This is useful for preparing for new types of risks or extreme situations.

• Regulatory Stress Testing
  Stress tests conducted by financial regulatory authorities (such as central banks and financial supervisory agencies) to assess the stability of the financial system, requiring financial institutions to evaluate capital adequacy and liquidity based on designated scenarios.

Credit Risk Measurement Methodologies

Credit Risk Measurement Techniques

• Credit Ratings and Transition Matrices
  Credit risk is assessed using the ratings from credit rating agencies and the transitional probabilities between those ratings.

• Structural Models
  Models like the Merton model estimate the probability of default based on the value of a firm's assets and its capital structure.

  The Probability of Default in Merton model(PD):
  PD = N(-d₂)

  Here, d₂ is calculated similarly to the d₂ parameter in the Black-Scholes formula.

• Reduced-Form Models
  This approach models default as a probability process that cannot be observed directly, with representative models being those of Jarrow and Turnbull.

• Credit VaR (Value at Risk)
  A measure that estimates the maximum expected credit loss at a specific confidence level, considering the following elements:

  1. Probability of Default (PD): The likelihood that a borrower will fail to meet its debt obligations.
  2. Loss Given Default (LGD): The percentage of loss incurred when a default occurs.
  3. Exposure at Default (EAD): The total exposure amount at the time of default.
  4. Correlation: The default correlation among various borrowers.

Liquidity Risk Measurement Methodology

Liquidity Risk Measurement Techniques

• Market Liquidity Risk Measurement

  1. Bid-Ask Spread: The difference between the buying price and the selling price; wider spreads indicate lower liquidity.
  2. Market Impact Cost: The effect of large trades on prices.
  3. Liquidity-adjusted VaR: VaR that takes into account market liquidity costs.

• Funding Liquidity Risk Measurement

  1. Liquidity Gap Analysis: Analysis of the difference between cash inflows and outflows over a specified period.
  2. Liquidity Ratios:
     • Liquidity Coverage Ratio (LCR): Measures liquidity adequacy in short-term stress situations.
     • Net Stable Funding Ratio (NSFR): Measures funding stability over the medium to long term.
  3. Survival Period Analysis: Estimation of the period that can be operated without external funding during stress situations.

Integrated Risk Measurement

Integrated Risk Management Approach

• Economic Capital
  The amount of capital required to absorb unexpected losses at a specific confidence level.

  Economic capital = UL (Unexpected Loss) 
                   = Risk measure (VaR, ES, etc.) - EL (Expected Loss)

• Risk Concentration Analysis
  Identifies and measures excessive exposure to specific counterparties, industries, regions, or risk types.

• Risk-Return Analysis
  Evaluates the risk-adjusted return of various business lines or transactions using risk-adjusted performance metrics:

  1. RAROC (Risk-Adjusted Return on Capital): Risk-adjusted return relative to economic capital
  2. RORAC (Return on Risk-Adjusted Capital): Return relative to risk-adjusted capital
  3. RARORAC (Risk-Adjusted Return on Risk-Adjusted Capital): Combination of risk-adjusted return and risk-adjusted capital

Quantitative risk measurement is the first step in the risk management process. Based on these metrics, risk control, mitigation, and transfer management strategies can be established and executed. The next section will explore risk management strategies and methods.

3️⃣ Market Risk Management Strategies

Market risk is one of the most common risks faced by financial institutions and investors. Various strategies and tools are used to effectively manage the potential losses caused by market price fluctuations.

Market Risk Management through Hedging Strategies

Basic Concept of Hedging

• Definition of Hedging
  A strategy that involves taking a position that moves in the opposite direction of the original position to reduce risk.

• Full Hedge vs. Partial Hedge
  A full hedge aims to eliminate all risks, while a partial hedge manages only a portion of the risk, maintaining a certain level of market exposure.

• Static Hedge vs. Dynamic Hedge
  A static hedge is an approach that does not frequently adjust the hedge position, whereas a dynamic hedge continuously adjusts the position based on changing market conditions.

• Measuring the Hedging Effect
  Hedge effectiveness is typically assessed through the hedge ratio and the degree of risk reduction.

Hedging Using Derivatives

• Futures and Forward Contracts
  A contract that allows the buying and selling of an asset at a predetermined price at a specific point in the future, used to hedge against price volatility risk.

  hedge ratio = β × (underlying position value / futures value)

  Here, β is the regression coefficient between the changes in spot and futures prices.

• Options Contracts
  By paying a premium, one can acquire the right to buy or sell an asset at a predetermined price for a specific period, limiting downside risk while maintaining upside opportunities.

  1. Protective Put: Buying put options on a stock portfolio to limit downside risk.
  2. Covered Call: Selling call options on held assets to generate additional income.
  3. Collar: Combining the purchase of put options and the sale of call options to reduce costs.

• Swap Contracts
  These are agreements between two parties to exchange a series of cash flows over a specified period.

  1. Interest Rate Swap: Managing interest rate risk by exchanging fixed and floating interest rates.
  2. Currency Swap: Managing exchange rate risk by exchanging principal and interest in different currencies.
  3. Credit Default Swap: A contract that provides compensation in the event of a credit event, managing credit risk.

Portfolio Diversification and Asset Allocation

Diversification and Asset Allocation Strategy

• Principles of Effective Diversification
  Invest in assets with low or negative correlation to reduce the overall risk of the portfolio.

  Portfolio Variance: σ²_p = Σ_i Σ_j w_i w_j σ_i σ_j ρ_ij

  Here, ( w ) represents the asset weight, ( σ ) is the standard deviation, and ( ρ ) is the correlation coefficient.

• Strategic Asset Allocation
  Sets target weights for asset classes based on long-term investment goals and risk tolerance.

• Tactical Asset Allocation
  Temporarily deviates from strategic asset allocation based on short-term market outlooks to pursue additional returns.

• Risk Parity
  An approach that allocates assets so that each asset contributes equally to the portfolio's risk.

  w_i ∝ 1 / (σ_i × ρ_im)

  Here, ( ρ_im ) is the correlation coefficient between asset ( i ) and the overall portfolio.

Risk Limit Setting and Management

Risk Limit Management System

• Types of Risk Limits

  1. Nominal Limits: Maximum size restrictions on specific positions or exposures
  2. Risk-Based Limits: Limits based on risk measures such as VaR, beta, duration, etc.
  3. Loss Limits: Setting the maximum allowable loss amount
  4. Concentration Limits: Restrictions on exposures to specific sectors, regions, or counterparties

• Limit Monitoring and Reporting
  Includes regular limit monitoring, escalation procedures in case of violations, and periodic reporting to management and the board.

• Stop-Loss Strategy
  A strategy to liquidate positions when a predetermined loss level is reached to prevent further losses.

• Risk Budgeting
  A method of allocating the organization's overall risk tolerance across various business units, trading desks, and portfolio managers.

Advanced Strategies for Market Risk Management

Advanced Market Risk Management Techniques

• Conditional Risk Management
  An approach that dynamically adjusts risk management strategies according to changes in the market environment or volatility regime.

• Tail Risk Hedging
  A hedging strategy that prepares for extreme market events (tail events) using out-of-the-money options, volatility products, and more.

• Hedging Based on Stress Scenarios
  An approach that establishes hedging strategies based on the results of stress tests for extreme market conditions.

• Collateral Management
  The process of requiring and managing collateral to reduce credit risk in derivatives transactions, which includes variation margin and initial margin.

• Algorithmic Trading and Risk Management
  Using computer algorithms to analyze market risk in real time and automate trading decisions.

Effective market risk management requires a comprehensive approach that utilizes a variety of strategies and tools rather than relying on a single method. Additionally, it is important to continuously assess and adjust strategies in response to changes in market conditions.

4️⃣ Credit Risk Management Methodology

Credit risk refers to the possibility that a counterparty will fail to fulfill its contractual obligations, resulting in a risk of loss. For financial institutions, particularly banks, managing credit risk is a core function, employing various methodologies and tools to measure and manage this risk.

Credit Assessment and Rating Systems

Credit Assessment Process

• Internal Credit Assessment Systems
  Financial institutions use models and processes developed in-house to evaluate the creditworthiness of borrowers:

  1. Credit Scoring Models: Use statistical techniques to score borrower characteristics
  2. Rating Assignment Models: Consider financial indicators, qualitative factors, industry characteristics, etc., for assigning ratings
  3. Behavioral Scoring: Evaluates based on transaction patterns and repayment history of existing customers

• External Credit Rating Agencies
  Utilizes credit ratings provided by specialized agencies such as S&P, Moody's, and Fitch.

  Key rating systems:

  • Investment-grade ratings: AAA, AA, A, BBB (S&P/Fitch) or Aaa, Aa, A, Baa (Moody's)
  • Speculative-grade ratings: BB, B, CCC, CC, C (S&P/Fitch) or Ba, B, Caa, Ca, C (Moody's)

• Credit Rating Transition Matrix
  A matrix representing the transition probabilities between various credit ratings over a certain period, used to analyze the dynamic aspects of credit risk.

Modeling Expected and Unexpected Loss

Calculation of Expected Loss (EL)

Expected Loss is the average loss anticipated for credit exposure and is calculated as follows:

EL = PD × LGD × EAD

Here:

• PD (Probability of Default): The probability of default
• LGD (Loss Given Default): The loss rate in the event of default
• EAD (Exposure at Default): Exposure at the time of default

Unexpected Loss (UL) Measurement

The portion that exceeds the expected loss in the loss distribution, typically calculated as the difference between a specific percentile of the loss distribution (e.g., 99.9%) and the expected loss:

UL = VaR(99.9%) - EL

• Credit Portfolio Models
  A model that integrates the credit risk of a portfolio consisting of multiple borrowers:
  1. CreditMetrics: A model based on the correlation between credit rating transitions and asset values.
  2. KMV Model: A corporate default model that utilizes a structural approach.
  3. CreditRisk+: A model that employs an actuarial approach.
  4. CreditPortfolioView: A credit portfolio model that considers macroeconomic factors.

Credit Risk Mitigation Strategies

Methods of Credit Risk Mitigation

• Collateral
  By requiring assets that financial institutions can access in the event that a borrower defaults, credit risk is reduced:

  1. Tangible Collateral: Physical assets such as real estate, inventory, equipment, etc.
  2. Financial Collateral: Financial assets such as cash, securities, bonds, etc.
  3. Collateral Valuation and Management: Regular valuation, management of Loan-to-Value (LTV) ratios.

• Guarantees and Guarantors
  A contract in which a third party guarantees the borrower's debt, with the guarantor assuming responsibility in case of default.

• Credit Derivatives

  1. Credit Default Swap (CDS): A contract that provides compensation in the event of a credit event.
  2. Total Return Swap: A contract that exchanges the total return of a reference asset for a benchmark interest rate.
  3. Credit Linked Note: A bond where the repayment of principal varies based on the occurrence of a credit event.

• Securitization
  The process of pooling credit assets such as loans or bonds and issuing new securities, thereby distributing credit risk in the market:

  1. Asset-Backed Securities (ABS)
  2. Mortgage-Backed Securities (MBS)
  3. Collateralized Debt Obligations (CDO)

• Credit Limit Management
  Managing concentration risk by limiting maximum credit exposure to individual counterparties, industries, and regions.

Credit Risk Governance and Reporting

Credit Risk Governance Framework

• Credit Policies and Procedures
  Defines lending approval criteria, limit setting, methodology for assigning credit ratings, and collateral requirements.

• Delegation of Authority
  Establishes a structure for appropriately delegating credit approval authority based on risk levels and transaction sizes.

• Credit Committee
  Operates a specialized committee that reviews and approves major credit decisions.

• Independent Risk Oversight
  A credit risk management department, independent from sales, performs objective risk assessments and monitoring.

• Credit Risk Reporting
  Conducts regular reporting on key credit risk indicators, usage of limits, credit events, and qualitative changes in the portfolio.

Latest Trends in Credit Risk Management

Trends in Credit Risk Management

• Utilization of Artificial Intelligence and Machine Learning
  There is an increasing implementation of credit evaluation models, anomaly detection, and early warning systems utilizing big data and AI technology.

• Use of Alternative Data
  There is a growing trend to incorporate non-traditional data such as social media, mobile data, payment behavior, and e-commerce records into credit evaluations.

• Integration of Environmental, Social, and Governance (ESG) Factors
  Approaches that reflect a company's sustainability and ESG performance in credit evaluations are being strengthened.

• Dynamic Management of Credit Risk
  Dynamic management methods that proactively adjust credit policies and standards based on economic cycles, industry trends, and macroeconomic changes are becoming increasingly important.

• Regulatory Response and Internal Model Development
  Ongoing development and enhancement of Internal Ratings-Based (IRB) models to meet credit risk-related requirements under Basel III/IV are in progress.

Credit risk management is an essential function for the survival and prosperity of financial institutions. It is crucial to establish a more effective and proactive credit risk management system by leveraging advanced technologies and data analysis techniques alongside traditional credit analysis methodologies.

5️⃣ Operational Risk Management Framework

Operational risk refers to the risk of loss resulting from inadequate or failed internal processes, people, systems, or external events. Since the 2008 financial crisis, there has been a significant increase in interest in operational risk, alongside heightened regulatory scrutiny, making the establishment of a systematic management framework essential.

Identification and Assessment of Operational Risk

Methods for Identifying Operational Risk

• Risk and Control Self-Assessment (RCSA)
  A process in which business units identify the operational risks inherent in their activities and assess the effectiveness of controls.

• Risk Mapping
  An approach that systematically maps related risks by analyzing the organization's key processes and activities.

• Key Risk Indicators (KRIs)
  Quantitative indicators used to monitor the level of operational risk or the effectiveness of controls, serving as an early warning system:

  1. Transaction Error Rate: The ratio of errors among processed transactions
  2. System Downtime: The duration of IT system failures
  3. Employee Turnover Rate: The rate of turnover among key personnel
  4. Unresolved Audit Issues: The number of unresolved items identified in audits

• Scenario Analysis
  A method that hypothesizes extreme yet possible operational risk events and evaluates their impact and likelihood of occurrence.

Operational Risk Measurement Methodology

Operational Risk Quantification Approach

• Loss Distribution Approach (LDA)
  This approach uses historical loss data to model the frequency and severity distributions of losses to measure operational risk:

  1. Loss Frequency Distribution: Modeled using Poisson distribution or negative binomial distribution
  2. Loss Severity Distribution: Modeled using log-normal distribution, Weibull distribution, Pareto distribution, etc.
  3. Monte Carlo Simulation: Combines the two distributions to derive the total loss distribution

• Basel Regulatory Approaches

  1. Basic Indicator Approach (BIA): Sets a fixed percentage (α, typically 15%) of annual gross income as operational risk capital
  2. Standardized Approach (SA): Applies different factors (β) based on business lines
  3. Advanced Measurement Approach (AMA): Uses internal models for self-assessment

• Operational Risk VaR
  An indicator that measures the maximum expected operational loss at a specific confidence level, derived through the loss distribution approach.

• Scorecard Methodology
  A method for assessing operational risk by quantifying qualitative factors, taking into account control environment strength, process complexity, human factors, etc.

Operational Risk Control and Mitigation

Operational Risk Management Strategy

• Internal Control System
  A set of policies, procedures, and systems designed to prevent, detect, and correct risks:

  1. Preventive Controls: Measures to prevent errors or fraud from occurring in advance
  2. Detective Controls: Identifying and reporting issues that have occurred
  3. Corrective Controls: Resolving identified problems and preventing recurrence

• Segregation of Duties
  A principle that reduces the risk of fraud by separating functions such as transaction approval, execution, recording, and asset custody among different employees.

• Exception Management Process
  A process for systematically recording, approving, and monitoring exceptional situations that deviate from policies or procedures.

• Business Continuity Planning (BCP)
  A plan to maintain critical functions and quickly resume normal operations in the event of disasters or significant business interruptions:

  1. Business Impact Analysis: Assessing the impact of interruptions
  2. Recovery Strategy Development: Preparing alternative sites, backup systems, etc.
  3. Emergency Response Plan: Procedures for responding to crises
  4. Regular Testing and Training: Validating the effectiveness of the plan

• Insurance Transfer
  A strategy for transferring potential losses from operational risks to a third party through insurance:

  1. Property Insurance: Compensation for damage to physical assets
  2. Liability Insurance: Legal responsibility to third parties
  3. Crime Insurance: Losses due to employee dishonesty, fraud, etc.
  4. Cyber Insurance: Losses due to data breaches, cyber attacks

Operational Risk Governance and Reporting

Operational Risk Governance System

• Three Lines of Defense Model

  1. 1st Line of Defense: Business units and operational managers (risk ownership and day-to-day management)
  2. 2nd Line of Defense: Operational Risk Management Department (oversight, monitoring, policy establishment)
  3. 3rd Line of Defense: Internal Audit (independent validation and assurance)

• Operational Risk Committee
  A senior management committee that reviews operational risk policies, frameworks, and key issues, making decisions accordingly.

• Incident Reporting System
  A process for systematically reporting, analyzing, and tracking operational risk incidents, including loss data collection and issue resolution.

• Regular Reporting
  Regular reporting on key risk indicators, major operational risk exposures, loss incidents, control weaknesses, improvement activities, and more is conducted.

Technology and Cyber Risk Management

Technology Risk Management

• IT Governance
  A framework for managing IT risks that includes policies, procedures, responsibilities, and performance measurement.

• System Development Life Cycle (SDLC) Controls
  A control system that manages risks at all stages of new system development and changes to existing systems.

• Access Management
  A system for managing access to information and systems based on the principle of least privilege.

• Cyber Security
  A defense system to protect systems and data from cyber threats:

  1. Defense in Depth: Implementation of multiple layers of security controls
  2. Penetration Testing: Simulated hacking to identify vulnerabilities
  3. Security Monitoring: Real-time threat detection and response
  4. Incident Response Plan: Procedures for responding to cyber incidents

• Data Governance
  A system of policies and processes to ensure the availability, integrity, security, and usability of data.

• Cloud Risk Management
  A framework for managing specific risks associated with the use of cloud services (data sovereignty, service outages, vendor dependence, etc.).

Operational risk management goes beyond mere regulatory compliance; it is a key element in enhancing business resilience and sustainability. An effective operational risk management framework enables organizations to prepare for unexpected events, minimize losses, and achieve business objectives.

6️⃣ Liquidity Risk Management

Liquidity risk refers to the risk that an institution may not be able to meet its financial obligations in a timely manner or may not be able to sell assets without adverse changes in market conditions. The 2008 financial crisis vividly highlighted the importance of liquidity risk management, leading regulatory authorities and financial institutions to significantly strengthen their liquidity risk management practices.

Types and Causes of Liquidity Risk

Major Types of Liquidity Risk

• Funding Liquidity Risk
  This risk arises when an institution is unable to obtain necessary funds in a timely manner or can only do so at excessive costs.

  Main Causes:

  1. Bank runs
  2. Reduction or cancellation of credit lines
  3. Decline in institution's creditworthiness
  4. Tightening of short-term funding markets

• Market Liquidity Risk
  This risk occurs when assets cannot be quickly sold at a fair price due to market conditions.

  Main Causes:

  1. Market stress situations
  2. Concentration of illiquid assets
  3. Decrease in market participants
  4. Extreme price volatility

• Contingent Liquidity Risk
  This risk arises from the need for additional liquidity due to contingent events (such as a downgrade in credit ratings or an increase in collateral requirements).

Liquidity Risk Measurement Methods

Liquidity Risk Measurement Techniques

• Liquidity Gap Analysis
  This is a method of measuring the mismatch (gap) by comparing cash inflows and outflows over a specific period:

  Liquidity Gap = Liquidity Asset - Liquidity Liability

  Time Bucket Gap Analysis: Measures gaps by categorizing into various periods (1 day, 1 week, 1 month, 3 months, etc.).

• Cumulative Gap Analysis:
  Cumulatively assesses gaps across multiple time buckets to evaluate long-term liquidity positions.

• Liquidity Ratios:

  1. Liquidity Coverage Ratio (LCR):

  LCR = high-quality liquid assets / net cash out for 30 days ≥ 100%

  Requires holding sufficient high-quality liquid assets to survive a seriously stressed scenario for 30 days.

  2. Net Stable Funding Ratio (NSFR):

  NSFR = Available Stable Funding / Required Stable Funding ≥ 100%

  Maintains a stable funding structure for long-term assets and activities.

• Stress Testing
  A method for assessing liquidity positions under various stress scenarios, considering institution-specific, market-wide, and complex scenarios.

• Survival Period Analysis
  Measures the duration that an institution can operate without external funding in stressful situations.

Liquidity Risk Management Strategy

Liquidity Risk Management Techniques

• Maintaining a Liquidity Buffer
  Maintain a sufficient reserve of highly liquid assets (cash, government bonds, etc.) that can be used in stress situations.

• Diversification of Funding

  1. Diversification of Funding Sources: Utilize various funding sources such as retail deposits, wholesale funding, and bond issuance.
  2. Maturity Diversification: Achieve a balanced mix of short-term, medium-term, and long-term funding.
  3. Currency Diversification: Fund in various currencies to reduce the risk of market tightness in specific currency markets.
  4. Investor Base Diversification: Secure investors from various types and regions.

• Asset-Liability Management (ALM)
  Comprehensively manage the maturity, currency, and interest rate characteristics of assets and liabilities to minimize mismatches.

• Contingency Funding Plan (CFP)
  Establish response strategies and action plans in advance for liquidity crisis situations:

  1. Early Warning Indicators: Metrics to identify early signs of a liquidity crisis.
  2. Crisis Response Strategies by Stage: Actions based on the severity of the situation.
  3. Emergency Funding Sources: Central bank loans, emergency credit lines, asset liquidation plans, etc.
  4. Communication Plan: Effective communication strategies with stakeholders.

• Collateral Management
  Systematically manage the availability, quality, and value volatility of collateral assets to ensure funding capability.

Basel III Liquidity Regulation and Response

Basel III Liquidity Regulation Framework

• Liquidity Coverage Ratio (LCR) Requirements

  • Hold high-quality liquid assets (HQLA) to cover more than 100% of net cash outflows over a 30-day stress scenario.
  • Definition and classification of high-quality liquid assets (HQLA).
  • Methodology for calculating cash outflows and inflows.

• Net Stable Funding Ratio (NSFR) Requirements

  • Maintain a stable funding structure for over one year.
  • Calculation of required stable funding based on the liquidity characteristics of assets.
  • Calculation of available stable funding based on the stability of liabilities.

• Regulatory Response Strategies

  1. Adjusting Business Model: Restructuring the portfolio to focus on businesses with lower liquidity consumption.
  2. Optimizing Debt Structure: Increasing the proportion of stable funding (such as retail deposits and long-term bonds).
  3. Adjusting Asset Composition: Increasing the share of high-quality liquid assets and reducing illiquid assets.
  4. Changing Pricing Policy: Reflecting liquidity costs in the internal funds transfer pricing (FTP).

Case Studies and Lessons of Liquidity Crises

Major Liquidity Crisis Cases

• 2008 Lehman Brothers Bankruptcy
  The primary causes of the bankruptcy were excessive reliance on short-term funding, inadequate collateral management, and a rapid decline in funding ability due to loss of trust.

  Lesson: Importance of funding diversification, strengthening stress tests, considering collateral value volatility.

• 2007 Northern Rock Bank Run
  Northern Rock, a UK mortgage bank, faced a severe liquidity crisis due to excessive reliance on wholesale funding. When the short-term funding market froze, it resulted in the first major bank run in UK history.

  Lesson: Value of the stability of retail deposits, managing reliance on wholesale funding, the central bank's role as a lender of last resort.

• 2010 European Sovereign Debt Crisis
  The sovereign debt crises in countries like Greece, Ireland, and Portugal had serious implications for the liquidity of the banking system.

  Lesson: The connection between sovereign risk and liquidity risk, the complexity of cross-border liquidity management, currency mismatch risk.

Liquidity risk management is essential for the survival of financial institutions. Effective preparation for liquidity crises can be achieved through maintaining appropriate liquidity buffers, diversifying funding structures, establishing comprehensive contingency plans, and developing sophisticated measurement and monitoring systems.

7️⃣ Risk Management and Regulatory Framework

Financial risk management is essential not only for achieving internal management goals but also for regulatory compliance. Particularly after the global financial crisis of 2008, the strengthening of financial regulations has made the link between risk management and regulatory frameworks even more important.

Developments and Key Aspects of the Basel Accords

Development of the Basel Accords

• Basel I (1988)
  The first international banking capital regulatory framework, which primarily focused on credit risk:

  • Minimum capital requirement of 8%
  • Application of a simple risk-weighting system
  • Uniform risk weight (100%) applied to most corporate exposures

• Basel II (2004)
  A framework aimed at refining risk measurement and expanding the scope of risks:

  1. Pillar 1: Minimum capital requirements (credit risk, market risk, operational risk)
  2. Pillar 2: Supervisory review process (self-assessment of banks' risks and review by supervisory authorities)
  3. Pillar 3: Market discipline (enhancing transparency through disclosure requirements)

• Basel III (2010-2019)
  A revised framework aimed at enhancing the resilience of the banking system post-financial crisis:

  1. Strengthening capital requirements:
     • Common Equity Tier 1 (CET1) ratio minimum of 4.5%
     • Additional Capital Conservation Buffer of 2.5%
     • Additional capital requirements for systemically important banks
  2. Introduction of leverage ratio: minimum capital ratio relative to total assets (generally 3%)
  3. Introduction of liquidity regulations: LCR and NSFR
  4. Limits on large exposures: restrictions on exposure to a single counterparty

• Basel IV (2017-2023)
  The final stage of Basel III (often referred to as Basel IV) includes the following changes:

  1. Revision of the Standard Approach (SA) for credit risk: reducing reliance on external credit ratings, improving risk sensitivity
  2. Limitations on the Internal Ratings-Based (IRB) approach: restrictions on eligible asset types for advanced IRB, introduction of parameter floors
  3. New Standardized Approach (SMA) for operational risk: replacing existing methodologies
  4. Output Floor: Internal model-based Risk-Weighted Assets (RWA) cannot be less than 72.5% of the Standard Approach

International and Domestic Regulatory Framework

Key Regulatory Frameworks

• International Regulatory Bodies

  1. Basel Committee on Banking Supervision (BCBS): Establishes international banking regulatory standards
  2. International Organization of Securities Commissions (IOSCO): Coordinating securities market regulation
  3. Financial Stability Board (FSB): Monitoring and advising on the stability of the international financial system

• Major Financial Regulations in the United States

  1. Dodd-Frank Act: Enhances financial stability, supervises systemic risk, consumer protection
  2. Comprehensive Capital Analysis and Review (CCAR): Stress testing program for large banks
  3. Volcker Rule: Restrictions on banks' proprietary trading and investment in hedge funds/private equity

• Major Financial Regulations in the European Union

  1. Capital Requirements Directive/Regulation (CRD/CRR): EU implementation of Basel III framework
  2. European Market Infrastructure Regulation (EMIR): Regulation of OTC derivatives markets
  3. Markets in Financial Instruments Directive II (MiFID II): Regulation of investment services, enhancing market transparency

• Major Financial Regulations in South Korea

  1. Banking Supervision Regulation: Capital regulation and risk management requirements for banks in Korea
  2. Financial Companies Governance Act: Establishing sound governance for financial companies
  3. Financial Group Supervision System: Comprehensive management of risks across financial groups

Risk Governance and Regulatory Response

Risk Governance Framework

• Role of the Board

  • Approval of risk management strategies and policies
  • Setting and overseeing risk appetite
  • Reviewing the effectiveness of the risk management framework
  • Supervising the cultivation of a risk culture

• Risk Committee

  • Review of risk strategies and policies
  • Monitoring key risk exposures
  • Assessing the adequacy of the risk management framework
  • Providing risk-related recommendations to the board

• Role of the Chief Risk Officer (CRO)

  • Directing enterprise-wide risk management activities
  • Developing risk policies and limits
  • Establishing risk measurement and reporting systems
  • Enhancing risk culture
  • Providing independent risk assessments to management and the board

• Three Lines of Defense Model

  1. 1st Line of Defense: Business Lines (Risk Ownership)
  2. 2nd Line of Defense: Risk Management Function (Oversight and Monitoring)
  3. 3rd Line of Defense: Internal Audit (Independent Assurance)

Internal Capital Adequacy Assessment Process (ICAAP) and Internal Liquidity Adequacy Assessment Process (ILAAP)

Capital and Liquidity Adequacy Assessment Process

• Internal Capital Adequacy Assessment Process (ICAAP)
  A process for banks to identify all significant risks and assess whether they hold sufficient capital to address those risks:

  1. Risk Identification and Assessment: Identifying all significant sources of risk
  2. Capital Planning: Forecasting current and future capital requirements
  3. Stress Testing: Evaluating capital adequacy under extreme conditions
  4. Board Approval and Oversight: Reviewing and approving results
  5. Documentation and Reporting: Systematic documentation of the process and results

• Internal Liquidity Adequacy Assessment Process (ILAAP)
  A process for financial institutions to assess their ability to manage liquidity and funding risk in both normal and stressed conditions:

  1. Liquidity Risk Identification: Identifying institution-specific sources of liquidity risk
  2. Liquidity Buffer Calculation: Evaluating necessary liquidity in preparation for stressed conditions
  3. Funding Strategy: Developing funding plans across various time horizons
  4. Contingency Planning: Outlining responses to liquidity crises
  5. Governance and Documentation: Documenting liquidity management frameworks and results

Regulatory Response Strategy

Effective Regulatory Response Measures

• Monitoring regulatory changes and impact analysis

  • Systematic tracking of new regulatory initiatives
  • Quantitative and qualitative assessment of potential impacts
  • Analysis of the impact on the business model

• Proactive response and execution plans

  • Securing sufficient preparation time for regulatory changes
  • Clear implementation roadmap and assignment of responsibilities
  • Identification of necessary system and process changes

• Integration with business strategy

  • Incorporating regulatory requirements into strategic decision-making processes
  • Optimizing the business portfolio considering capital, liquidity, and cost efficiency
  • Reflecting regulatory costs in internal pricing

• Constructive relationship with regulatory authorities

  • Maintaining transparent and open communication
  • Engaging constructively in regulatory discussions
  • Actively responding to inspections and feedback

Risk management and regulatory compliance are closely linked activities. An integrated approach is needed that leverages regulatory requirements as opportunities for building a robust risk management framework rather than merely viewing them as compliance obligations. Particularly as the financial environment and regulations continue to evolve, it is essential to maintain a flexible and adaptive risk management framework.

8️⃣ Latest Trends and Developments in Risk Management

With the rapid changes in the financial environment and advancements in technology, the field of risk management continues to evolve. In this section, we will explore the latest trends and new approaches in risk management.

Utilization of Artificial Intelligence and Machine Learning

AI and Machine Learning-Based Risk Management

• Risk Measurement and Modeling

  • Credit risk modeling using large-scale unstructured data
  • Improved market risk measurement through time series forecasting
  • Understanding interactions among risk factors through complex pattern recognition

• Anomaly Detection and Early Warning

  • Capturing early signs of operational risk events
  • Enhancing the accuracy of financial fraud detection models
  • Real-time monitoring of market anomalies

• Scenario Analysis and Stress Testing

  • Automation of scenario generation using machine learning
  • Impact analysis of complex stress scenarios
  • Modeling interactions among various risk factors

• Challenges in Utilizing AI

  • Ensuring model explainability
  • Preventing algorithmic bias
  • Managing model risk
  • Data quality and governance

Big Data and Advanced Analytics

Big Data Risk Analysis

• Utilization of Alternative Data

  • Market sentiment analysis through social media data
  • Assessment of physical risks using satellite images, sensor data, etc.
  • Behavior-based credit evaluation using payment data, mobile usage patterns, etc.

• Real-time risk monitoring

  • Immediate risk detection through streaming analytics
  • Real-time pattern analysis of large-scale transaction data
  • Visualization of risk indicators and implementation of dashboards

• Network Analysis

  • Risk transfer analysis among connected counterparties
  • Modeling of systemic risk network effects
  • Identification of financial crime networks

• Natural Language Processing (NLP)

  • Automated analysis of news, reports, and regulatory documents
  • Market direction prediction through sentiment analysis
  • Legal risk assessment via automated review of contracts and legal documents

Climate Risk and ESG Integration

Sustainability and Risk Management

• Climate Risk Management

  • Physical Risk: The impact of natural disasters and long-term environmental changes caused by climate change on assets, operations, and supply chains.
  • Transition Risk: Risks associated with regulations, technology, market changes, and reputational aspects that arise during the transition to a low-carbon economy.
  • Climate Scenario Analysis: Assessment of risk impacts based on various climate change pathways.
  • Portfolio Carbon Footprint: Measurement and management of carbon emissions from investment and lending portfolios.

• ESG Risk Integration

  • Integration of Environmental, Social, and Governance (ESG) factors into risk assessment.
  • Development of ESG scoring and risk rating models.
  • Compliance with ESG-related regulatory requirements.
  • Consideration of sector-specific and regional ESG risk characteristics.

• Sustainable Finance Risk

  • Greenwashing Risk: Reputational and regulatory risks arising from exaggerating or falsely claiming sustainability.
  • Risk management of sustainable finance products (such as green bonds and sustainability-linked loans).
  • Compliance with climate-related financial disclosure (TCFD).

Risk Culture and Human Elements

Risk Culture and Behavioral Risk

• Components of Risk Culture

  • Tone from the Top: Emphasizing the importance of risk management by leadership
  • Accountability and Transparency: Clear assignment of responsibilities and transparent communication
  • Effective Challenge: Encouraging constructive criticism of assumptions and decisions
  • Incentive Alignment: Linking compensation systems with risk accountability

• Behavioral Risk

  • The impact of individual and organizational decision-making biases on risk management
  • Managing cognitive biases such as Groupthink, overconfidence, and loss aversion
  • Reducing fraud risk through the establishment of an ethical culture

• Assessment and Improvement of Risk Culture

  • Risk culture surveys and assessment tools
  • Risk awareness training and education programs
  • Improving risk communication
  • Cultivating a culture of learning from failure

Resilience and Crisis Management

Strengthening Organizational Resilience

• Operational Resilience

  • The ability to deliver essential services even during disruptions
  • Identifying critical business services and setting impact tolerances
  • Vulnerability assessments and scenario testing
  • Developing recovery strategies and response plans

• Cyber Resilience

  • An integrated approach to preventing, detecting, responding to, and recovering from cyber attacks
  • Strategies for protecting critical digital assets
  • Cyber incident response plans
  • Building a security culture

• Crisis Management Framework

  • Identifying and categorizing potential crisis situations
  • Establishing crisis response organizations and decision-making structures
  • Communication strategies and protocols
  • Crisis simulations and training

The Evolution of Integrated Risk Management

Evolving Approaches to Risk Management

• Advancements in Enterprise Risk Management (ERM)

  • Transition from siloed approaches to integrated approaches
  • Consideration of interactions and correlations between risks
  • Linking strategic decision-making with risk management
  • Striving for a balance between risk and performance

• Risk Appetite Framework

  • Clarifying the organization's risk appetite
  • Setting quantitative and qualitative risk limits
  • Allocating risk tolerance by business line
  • Monitoring compliance with risk appetite

• Risk-Based Performance Management

  • Utilizing Risk-Adjusted Return on Capital (RAROC, RORAC, etc.)
  • Reflecting risk costs in internal pricing
  • Optimizing the business portfolio from a risk perspective
  • Strategic resource allocation considering risks

Future Perspectives on Risk Management

Future Directions of Risk Management

• Data-Driven Risk Management

  • Expansion of Predictive and Prescriptive Analytics
  • Utilization of Multimodal Data (text, images, voice, etc.)
  • Scenario Creation and Analysis Using Generative AI
  • Increased Importance of Data Governance and Ethics

• Risks of Digital Assets and Decentralized Finance (DeFi)

  • Risk Management of New Asset Classes such as Cryptocurrencies and Tokenized Assets
  • Special Risk Factors in Blockchain-Based Finance
  • Smart Contract Risks
  • Managing Regulatory Uncertainty

• Emergence of Geopolitical Risks

  • Impact of Intercountry Conflicts and Tensions on Financial Systems
  • Supply Chain Risks and Economic Disruption
  • Risk Management of Sanctions and Trade Restrictions
  • Strategies for Regional Diversification and Resilience Enhancement

• Democratization of Risk Management

  • Increased Accessibility to Cloud-Based Risk Management Tools
  • Empowering Risk Management Capabilities in SMEs and Emerging Markets
  • Spread of Open Source Risk Models and Methodologies
  • Increased Sharing of Risk Management Knowledge and Best Practices

As the financial industry and technological environment continue to evolve, risk management is also developing in a more sophisticated and integrated direction. The emergence of new types of risks, advancements in data and analytical technologies, and a growing interest in sustainability provide both challenges and opportunities for risk managers. Effective risk management is evolving to not only defend against uncertainty but also to support sustainable value creation through informed decision-making.

9️⃣ Conclusion: The Importance of Risk Management

Risk management is an essential component for the stability of modern financial systems and the sustainability of individual financial institutions. In a complex and interconnected global financial environment, risk is unavoidable; however, systematic risk management allows for the identification, measurement, control, and transformation of risks into opportunities.

The importance of risk management can be found in the following aspects:

Core Values of Risk Management

• Ensuring Financial Stability
  Effective risk management enables financial institutions to maintain stable operations despite unexpected shocks and market volatility. This contributes to the stability of not just individual institutions but the entire financial system.

• Preserving and Creating Value
  Risk management goes beyond merely preventing losses; it facilitates sustainable value creation by efficiently allocating and managing risks. Measuring risk-adjusted performance helps identify genuine value-creating activities.

• Optimizing Decision-Making
  Systematic risk analysis enables better-informed decision-making. By clearly understanding the trade-offs between risk and return, organizations can make optimal decisions aligned with their strategic objectives.

• Efficient Resource Allocation
  A risk-based approach assists in allocating scarce resources, such as capital, liquidity, and human resources, to activities that yield the highest returns relative to their risks.

• Building Resilience
  A robust risk management framework enhances an institution's ability to maintain core functions and recover quickly in the face of unexpected crises.

Financial risk management has made remarkable advancements over the past few decades, but many challenges remain. New risk factors such as digital innovation, climate change, and geopolitical instability continue to emerge, and the methodologies and tools for managing these risks are continuously evolving.

In the upcoming series on the fundamentals of financial engineering, we will delve into more advanced topics, including time series analysis, financial engineering programming, and practical applications of financial engineering, based on these risk management concepts. A solid understanding of risk management will provide an essential foundation for learning more complex financial engineering concepts.

🔟 References and Recommended Materials

For a deeper understanding of risk management, the following resources may be helpful:

Recommended Books

• “Financial Risk Management" (Author: John C. Hull, Publisher: Wiley)
• "Risk Management and Financial Institutions" (Author: Rene Stulz, Publisher: Wiley)
• "Measurable Risk Management: A New Approach to Value and Financial Risk" (Author: Peter C. Fishburn, Publisher: Wiley)
• "Economic Capital Allocation and Risk Management" (Author: Andrea Lilienthal, Publisher: McGraw-Hill)
• "Operational Risk: Measurement and Management" (Author: Carol Alexander, Publisher: FT Press)
• "Credit Risk: Pricing, Measurement, and Management" (Author: Darrell Duffie, Publisher: Princeton University Press)
• "Principles and Practice of Financial Risk Management" (Author: Kwangwoo Park, Publisher: Hongmunsa)

Online Resources

• Global Risk Management Survey (Deloitte): https://www2.deloitte.com/global/en/pages/financial-services/articles/gfsi-risk-management-survey.html
• Basel Committee on Banking Supervision (BCBS): https://www.bis.org/bcbs/
• International Swaps and Derivatives Association (ISDA): https://www.isda.org/
• Financial Stability Board (FSB): https://www.fsb.org/
• Financial Supervisory Service Risk Management: https://www.fss.or.kr/
• Korea Risk Management Society: https://www.krm.or.kr/
• Global Association of Risk Professionals (GARP): https://www.garp.org/
• PRMIA(Professional Risk Managers' International Association): https://www.prmia.org/

Major Journal

• Journal of Risk and Uncertainty
• Journal of Risk
• Journal of Operational Risk
• Journal of Credit Risk
• Journal of Risk Management in Financial Institutions
• Risk Analysis
• Risk Management
• Journal of Banking & Finance
• Journal of Financial Stability

Free Sortware and Library

• Python: pandas, numpy, scipy, matplotlib, scikit-learn, statsmodels, PyPortfolioOpt
• R: quantmod, PerformanceAnalytics, rugarch, fPortfolio, riskmetrics
• Open Source Risk Management Tool: OpenRisk, Open Source Risk Engine (ORE)
• Finance and Risk Data: Yahoo Finance, FRED(Federal Reserve Economic Data)

Disclaimer

• The content of this blog is written for educational and informational purposes and should not be considered an investment recommendation or a substitute for financial advice. For actual financial decisions, please seek the advice of a professional.