Study finds environmental liability insurance reduces industrial carbon emissions.
problem Reduction of industrial carbon emissions.
method Two-way fixed effect model using provincial (city) level panel data from 2010 to 2020.
result Environmental liability insurance reduces industrial carbon emissions at both direct and indirect levels, with varying effects.
Study classifies liability insurance policies using machine learning.
problem Classifying liability insurance policies with or without claims.
method Used machine learning models like nearest neighbour and logistic regression on Actuarial Challenge dataset.
result Models accurately classified policies into claims and non-claims groups.
Mean-field approximations simplify insurance liability calculations.
problem High-dimensional system of equations makes insurance liability calculation infeasible.
method Use mean-field model to replace high-dimensional system with a low-dimensional non-linear system.
result Insurance liability converges to mean-field approximation as cohort size increases.
Study optimal strategies for insurer's dividends, investments, and liabilities.
problem Maximize insurer's utility of dividend payments over an infinite horizon.
method Perturbation approach to obtain optimal strategy and value function in closed form.
result Obtained optimal strategy and value function for log and power utility.
Framework for realistic insurance liability valuation.
problem Economic realism in insurance liability valuation.
method Replication approach of no-arbitrage theory, considering capital and fulfillment conditions.
result Identifies conditions for market price recovery and extends production for insolvency.
Study optimizes insurance liability cash flows with regulatory capital requirements.
problem Valuation of insurance liabilities under regulatory capital constraints.
method Multiple-prior optimal stopping theory applied to insurance liabilities, considering hypothetical transfer and repeated capital requirements.
result Proposes a valuation functional for non-replicable cash flows, incorporating a margin for regulatory capital considerations.
In this paper we propose a general framework for modeling an insurance liability cash flow in continuous time, by generalizing the reduced-form framework for credit risk and life insurance. In particular, we assume a nontrivial dependence structure between the reference filtration and the insurance internal filtration.…
Algorithmic insurance tackles financial risks from AI errors, proving CVaR-optimal thresholds reduce tail risk.
problem High-stakes AI errors lead to heterogeneous losses, challenging traditional insurance assumptions.
method Analyzed binary classification performance to tail risk exposure, using CVaR to quantify extreme losses.
result CVaR-optimal thresholds reduce tail risk up to 13-fold compared to accuracy maximization.
New method for insurance valuation combining hedging and risk minimization.
problem Current insurance valuation methods do not reflect regulatory risk measures.
method Two-step hedging procedure using generalised regression.
result The method produces portfolios neutral to risk measures like VaR or expectiles.
Neural networks assess asset-liability risk over time.
problem Challenging valuation of portfolios with complex products.
method Neural network approach for conditional portfolio valuation.
result Effective risk assessment for banking and insurance portfolios.
Mack-Net model combines Mack's model with RNNs for better insurance liability estimation.
problem Accurate estimation of insurance liabilities for better financial decision-making.
method Integrates Mack's reserving model with Recurrent Neural Networks (RNNs).
result Improves accuracy of general insurance liability assessment.
We present an approach to market-consistent multi-period valuation of insurance liability cash flows based on a two-stage valuation procedure. First, a portfolio of traded financial instrument aimed at replicating the liability cash flow is fixed. Then the residual cash flow is managed by repeated one-period replicatio…
This paper investigates market-consistent valuation of insurance liabilities in the context of, for instance, Solvency II and to some extent IFRS 4. We propose an explicit and consistent framework for the valuation of insurance liabilities which incorporates the Solvency II approach as a special case. The proposed fram…
Stochastic model for pension insurer assets and liabilities with mortality risk.
problem Modeling assets and liabilities with mortality risk in pensions insurers.
method Multivariate stochastic process for asset and liability returns, capturing dynamics and dependencies.
result Efficient computation of a million scenarios on personal computers.
Study validates Libor model for insurance benefits calculation.
problem Valuation of long-term insurance guarantees.
method Mean-field Libor market model, numerical ALM, aggregated life insurance data.
result Derives estimators for future discretionary benefits.
This study examines how risky investments affect insurance capital valuation.
problem Standard cost-of-capital assumptions do not account for risky investments.
method Analyzed effects of allowing buffer capital investments in risky assets.
result Decomposition of buffer capital contributions varies with riskiness.
This paper maps the insurability of AI risks across various insurance products.
problem Emerging AI risks and their implications for insurance coverage.
method Coding 55 AI threat classes against 26 insurance products using public carrier materials and threat catalogs.
result Identification of a four-tier insurability frontier: affirmatively insured, silent-AI exposures, actively excluded, and unstructured perils.
Paper introduces new actuarial-consistent valuations for insurance liabilities.
problem Valuation of insurance liabilities considering both financial and actuarial risks.
method Proposes two-step actuarial valuations and actuarial-consistent procedures.
result Actuarial-consistent valuations are equivalent to two-step actuarial valuations under coherence.
Limited liability creates a conflict of interests between policyholders and shareholders of insurance companies. It provides shareholders with incentives to increase the risk of the insurer's assets and liabilities which, in turn, might reduce the value policyholders attach to and premiums they are willing to pay for i…
This study compares direct and indirect methods for estimating own funds in life insurance, finding indirect methods more effective under realistic asset-liability coupling.
problem Computing own funds for life insurers using direct and indirect methods in a risk-neutral pricing framework.
method Introduced a novel family of mixed estimators including both direct and indirect methods, integrated into a control variate framework for variance reduction.
result The indirect method is more effective under realistic asset-liability coupling, but neither method is universally superior.
Paper proposes a natural hedging framework with graphical assessment for longevity risk management.
problem Lack of a unified framework for natural hedging and graphical risk assessment.
method Structured natural hedging framework integrated with a graphical risk metric.
result Demonstrates flexibility, interpretability, and practical value for longevity risk management.
Reinforcement learning improves insurance claims reserving by learning from all claim trajectories.
problem Traditional reserving models learn only from settled claims, missing valuable data from ongoing claims.
method Formulated as a Markov decision process, uses reinforcement learning to update OCL estimates sequentially.
result Soft Actor-Critic implementation achieves competitive claim-level accuracy and strong aggregate performance.
The paper optimizes dividend strategies for companies with assets and liabilities under solvency constraints.
problem Maximizing dividends while adhering to solvency requirements in the face of correlated asset and liability movements.
method Developed verification lemmas to show optimal barrier dividend strategies in two cases: with and without shareholder funding.
result Optimal dividend strategies are barrier-type, derived in closed form and illustrated.
We introduce a generic model for spouse's pensions. The generic model allows for the modeling of various types of spouse's pensions with payments commencing at the death of the insured. We derive abstract formulas for cashflows and liabilities corresponding to common types of spouse's pensions. We show how the standard…
Model calculates capital requirements for multi-line insurance companies.
problem Measuring and capitalizing on incurred claims risk for multi-line property and casualty insurers.
method Stochastic model integrating accident semester, development lag effects, autocorrelation, and hierarchical copula.
result Model accurately reproduces empirical loss ratio dynamics and quantifies overall portfolio risk.
Optimal portfolios for fat-tailed risks using a new tail risk measure.
problem Optimizing portfolios for pension funds and insurance liabilities with extreme risk sensitivity.
method Developed a new tail risk measure (Extreme Deviation, XD) and optimized portfolios based on this measure.
result Optimal portfolios maximize return per unit of XD, balancing hedging and risk contributions.
In this paper we study the pricing and hedging problem of a portfolio of life insurance products under the benchmark approach, where the reference market is modelled as driven by a state variable following a polynomial diffusion on a compact state space. Such a model guarantees not only the positivity of the OIS short …
The aim of this paper is to define the market-consistent multi-period value of an insurance liability cash flow in discrete time subject to repeated capital requirements, and explore its properties. In line with current regulatory frameworks, the approach presented is based on a hypothetical transfer of the original li…
Paper introduces a new principle for fair redistribution of insurance surplus.
problem Fair redistribution of surplus in life insurance policies.
method Introduces ISU decomposition principle based on infinitesimal sequential updates.
result Existing heuristic formulas can be replicated as ISU decompositions.
Two-dimensional transition rates improve life insurance reserve calculations.
problem Calculating life insurance reserves with Markov assumptions.
method Introducing two-dimensional forward and backward transition rates.
result Two-dimensional transition rates enable more accurate reserve calculations.
This note fills the gap in market-consistent valuation of lifelong health insurance products.
problem Market-consistent valuation of lifelong health insurance products is not well-addressed.
method Constructs a valuation portfolio to separate Best Estimate into policy data and financial instrument prices.
result The Best Estimate valuation is not uniquely determined by prevailing term structures and requires a stochastic model.
Derives equations for life insurance reserves with interest rate uncertainty.
problem Life insurance reserves with stochastic interest rates.
method Partial differential equations for reserves under stochastic interest rates.
result Explicit solutions for reserves under specific models.
We study a continuous-time asset-allocation problem for an insurance firm that backs up liabilities from multiple non-life business lines with underwriting profits and investment income. The insurance risks are captured via a multidimensional jump-diffusion process with a multivariate compound Poisson process with depe…
In this paper we investigate novel applications of a new class of equations which we call time-delayed backward stochastic differential equations. Time-delayed BSDEs may arise in finance when we want to find an investment strategy and an investment portfolio which should replicate a liability or meet a target depending…
Financial undertakings often have to deal with liabilities of the form 'non-hedgeable claim size times value of a tradeable asset', e.g. foreign property insurance claims times fx rates. Which strategy to invest in the tradeable asset is risk minimal? We generalize the Gram-Charlier series for the sum of two dependent …
Paper solves investment and consumption problem with unknown risk, providing explicit solutions.
problem Solving consumption-investment problem with unknown market price of risk and terminal liability constraint.
method Introduced a coupled forward-backward stochastic differential equation (FBSDE) and provided an explicit solution.
result Explicit expressions for optimal investment strategy and value function derived.
The paper uses neural networks to price complex life insurance contracts with multiple risk factors.
problem Pricing equity-linked life insurance contracts with various stochastic risk factors.
method Assuming hedging to reduce local variance, the price is expressed as a system of non-linear PDEs. Reformulated as a backward SDE with jumps, solved numerically using neural networks.
result Neural networks provide an efficient numerical solution for pricing these complex contracts.
In a market with stochastic volatility and jumps, we consider a VIX-linked fee structure for variable annuity contracts with guaranteed minimum withdrawal benefits (GMWB). Our goal is to assess the effectiveness of the VIX-linked fee structure in decreasing the sensitivity of the insurer's liability to volatility risk.…
Financial markets are exposed to systemic risk (SR), the risk that a major fraction of the system ceases to function, and collapses. It has recently become possible to quantify SR in terms of underlying financial networks where nodes represent financial institutions, and links capture the size and maturity of assets (l…
A framework tackles model uncertainty in ALM, providing robust investment strategies.
problem Model uncertainty in asset liability management (ALM).
method Wasserstein barycenter approach to handle various information sources and uncertainties.
result The proposed framework selects robust investment portfolios that remain optimal under various uncertainties.
Compact formulas for evaluating insurance policies' risks.
problem Quantifying demographic risk in insurance portfolios.
method Cohort-based approach with market-consistent valuation.
result Formal closed formula for idiosyncratic risk (accidental mortality).
This paper considers the problem of predicting the number of events that have occurred in the past, but which are not yet observed due to a delay. Such delayed events are relevant in predicting the future cost of warranties, pricing maintenance contracts, determining the number of unreported claims in insurance and in …
In this paper we study data from the yearly reports the four major Swedish non-life insurers have sent to the Swedish Financial Supervisory Authority (FSA). We aim at finding marginal distributions of, and dependence between, losses on the five largest lines of business (LoBs) in order to create models for Solvency Cap…
Method estimates joint distribution of bivariate outcomes.
problem Modeling dependence between bivariate outcomes.
method Semiparametric distribution regression.
result Method performs similarly or better than alternatives in finite samples.
Enhanced Tweedie model for insurance claims using CatBoost.
problem Accurately modeling aggregate claims with zero-inflated data.
method Refined Tweedie model with boosting methods in CatBoost.
result Marked improvement in model performance for insurance analytics.
New CDC scheme avoids intergenerational subsidies, offering better outcomes.
problem Intergenerational cross-subsidies in UK CDC schemes.
method Collective-Drawdown CDC approach using explicit insurance contracts.
result Better pension outcomes with no intergenerational cross-subsidies.
RL-CVaR model improves insurance reserving under economic stress.
problem Managing insurance reserve setting under claim development uncertainty and macroeconomic stress.
method Reinforcement Learning (PPO) with CVaR constraints, trained under regime-aware curriculum.
result RL-CVaR policy reduces solvency violations and tail-risk compared to classical methods.
The paper models SaaS products as insurance, offering new pricing tools.
problem Modeling capped-usage SaaS products with insurance principles.
method Frequency-severity decomposition, premium calculation, Monte Carlo simulations.
result SaaS pricing can be analyzed using insurance actuarial methods.