Core Expertise · 02
Actuarial
Actuarial work turns uncertain future cash flows into numbers that can be relied on today, and assesses the value of insurance and long-term benefit obligations. KSAAC works on IFRS 17 insurance contract measurement, actuarial assumptions and modeling, product and profitability analysis, insurer valuation, and employee and retirement benefit valuation and advice.
Key capabilities
- IFRS 17 insurance contract measurement
- Actuarial assumptions & models
- Product development & pricing
- Employee & retirement benefit valuation
What we cover
IFRS 17 insurance contract measurement
Supporting the full measurement process for insurance contracts: model, assumptions, risk adjustment, closing and analysis of results.
Assumptions, models and appointed-actuary work
Setting and managing actuarial assumptions, building and validating actuarial models and systems, and supporting appointed-actuary work.
Product development, pricing and profitability
Reviewing product strategy, pricing and the profitability of new products in light of IFRS 17 and K-ICS.
Valuation of insurers
Embedded value (EV/MCEV) and the valuation of insurers.
Employee and retirement benefit valuation and advice
Measuring defined-benefit obligations for retirement and other employee benefits under IAS 19 (K-IFRS 1019), with advice on actuarial assumptions, valuation reports and how the results are reflected in the financial statements.
From insurance contracts to capital
Insurance contract measurement is where solvency calculation begins. This page covers how contracts and assumptions are measured; how the results flow into capital, solvency and risk management is covered under Risk.
Assumptions and models
Experience analysis, assumption setting and model validation
Insurance contract measurement
IFRS 17 measurement, risk adjustment and closing
Capital and solvency
K-ICS required and available capital
Risk management
ALM, interest-rate risk and enterprise risk management
Actuarial × AI & Data
Actuarial assumptions start with data. On the basis of deep actuarial practice, KSAAC uses Python, machine learning and AI-supported modeling for experience and assumption analysis, for calculating and validating cash flows and present values, and for automating research and recurring work.
One example is research showing that AI and time-series data augmentation can improve mortality forecasts.
See AI & Data