Experience & Capabilities
Experience & Capabilities
KSAAC's capability is built on long experience in practice, research and teaching across accounting, actuarial work, finance and risk. The sections below set out, discipline by discipline, the main problem areas KSAAC works on and the professional experience behind them. Client details remain confidential.
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Problem areas and foundation by discipline
Main problem areas
- Reworking accounting policies, reporting and the financial close when a new standard takes effect
- Carrying actuarial measurement into the financial statements and disclosures
- Judging the accounting, and its tax effect, for transactions with little precedent and for fair-value measurement
Foundation
Experience both preparing and reviewing financial statements, together with research and commentary on accounting standards
- IFRS
- Financial reporting
- Accounting policy
- Complex transactions
- Financial analysis
Main problem areas
- Building IFRS 17 insurance contract measurement and managing the assumptions behind it
- Analyzing product strategy, profitability and insurers' embedded value (EV/MCEV) under IFRS 17 and K-ICS
- Valuing employee and retirement benefit obligations, and advising on how they are reflected in the financial statements
Foundation
Experience in insurers' actuarial and risk functions, actuarial consulting, appointed-actuary work, employee benefit valuation and teaching actuarial mathematics
- IFRS 17
- K-ICS
- Actuarial modeling
- Employee & retirement benefits
- Pricing & profitability
- Insurance valuation
Main problem areas
- Valuing shares, businesses and intangibles such as patents
- Financial and valuation analysis in mergers, acquisitions and disputes
- Grounding decisions in management diagnostics and financial analysis
Foundation
Valuation and due-diligence work in accounting and advisory practice in Korea and abroad, work inside a financial institution's finance function, and management diagnostics
- Valuation
- Financial analysis
- Corporate finance
- Business analysis
- M&A-related analysis
Main problem areas
- Designing enterprise risk management (ERM) frameworks and bringing financial, strategic and operational risk into decisions
- Designing capital and risk-management frameworks for K-ICS, and comparing international capital regimes with domestic rules to set a course
- Reviewing ALM and hedging strategy with interest-rate risk in view
Foundation
Risk management and ALM and hedging projects for insurers and financial institutions, enterprise risk management advice, and research and industry work on solvency regimes
- ERM
- Financial risk
- Operational risk
- Solvency
- ALM
- Risk modeling
Main problem areas
- Developing and validating analytical and forecasting models from financial, accounting and insurance data
- Redesigning accounting, finance and insurance workflows around AI and AI agents
- Implementing actuarial and financial calculations and automating routine work in Python
Foundation
Applying AI, AI agents, machine learning and Python to professional work, AI forecasting research, and teaching for public institutions, companies, financial institutions, professional bodies and universities
- AI
- Machine learning
- AI agents
- Generative AI
- Python analytics
- Automation
Main problem areas
- Reviewing the classification, measurement and tax issues of digital assets together
- Valuing digital assets when market prices are unstable
- Reviewing digital-asset risk management, including custody, liquidity and regulatory risk
Foundation
Research on, and professional courses in, digital-asset valuation, accounting, tax and risk management
- Accounting & tax
- Valuation
- Tokenization
- Stablecoins
- Risk & regulation
Problems that span disciplines
Complex regulatory and institutional change
Analyzing regulatory and institutional issues that cut across accounting, finance, actuarial work, risk and tax, and designing a company's response and how to carry it out
Integrated judgment on value, finance and risk
Analyzing connected factors such as enterprise value, financial structure, capital and risk together, to set the basis for decisions and their execution
AI and data transformation of professional work
Applying AI, data and AI agents to accounting, actuarial, finance and risk work, while designing the validation, controls and standards of professional judgment around them
Beyond advisory: research and education
KSAAC's experience goes beyond advisory work. It researches and publishes across accounting, tax and valuation, actuarial science, finance and risk, digital assets and AI, and teaches accounting, actuarial science, finance and risk alongside AI, machine learning and Python data analytics for public institutions, companies, financial institutions, professional bodies and universities. It also shares knowledge through articles in professional journals and other professional content.