Deep learning text embeddings improve fraud detection in healthcare insurance.
problem Improving fraud detection in healthcare insurance claims.
method Proposed deep learning architectures for text embeddings.
result Our approach outperforms other methods in detecting fraudulent claims.
High quality risk adjustment in health insurance markets weakens insurer incentives to engage in inefficient behavior to attract lower-cost enrollees. We propose a novel methodology based on Markov Chain Monte Carlo methods to improve risk adjustment by clustering diagnostic codes into risk groups optimal for health ex…
Study predicts high-cost patients using insurance claims data.
problem Accurately identifying high-cost patients to manage costs.
method Applied machine learning to health insurance claims data.
result Developed a high-performance algorithm with 91.2% AUC.
Study decomposes racial healthcare disparities via shifts in mediator distributions.
problem Racial disparities in healthcare expenditures and their underlying drivers.
method Framework decomposing disparities into mediator distribution shifts and residual components, using MEPS data.
result Substantial disparities persist even when mediators are equalized, suggesting unmeasured or structural factors.
Deep neural network predicts health costs better than traditional models.
problem Accurate prediction of healthcare costs for optimal cost management.
method Developed a deep neural network to predict future health care costs from health insurance claims records.
result Deep neural network outperformed ridge regression and Morbi-RSA models in cost prediction.
Unsupervised model detects healthcare fraud from patient visit data.
problem Detecting fraudulent healthcare bills from patient visit data.
method Uses LSTM and seq2seq models for anomaly detection, normalizes scores with EDF.
result Improves anomaly detection for high class imbalance problems.
Machine learning models outperform traditional actuarial methods in predicting health insurance costs.
problem Improving accuracy in health insurance pricing to identify concession opportunities.
method Developed and evaluated two machine learning models at the patient and employer-group levels.
result Machine learning models outperformed traditional actuarial models by 20% in predicting costs.
Isthmus platform simplifies ML/AI integration in healthcare.
problem Challenges in deploying ML models in healthcare due to data quality, regulatory, and security issues.
method Turnkey, cloud-based platform addressing data quality, clinical relevance, and regulatory compliance.
result Reduces time to market for operationalizing ML/AI in healthcare.
SARD improves deep learning clinical prediction performance.
problem Deep learning models struggle to match linear models in healthcare predictions.
method Reverse Distillation to initialize deep models, combined with contextual and temporal embeddings.
result SARD outperforms state-of-the-art methods on clinical prediction outcomes.
It is not clear how to target patients who are most likely to benefit from digital care management programs ex-ante, a shortcoming of current risk score based approaches. This study focuses on defining impactability by identifying those patients most likely to benefit from technology enabled care management, delivered …
PNNs improve personalized healthcare policies using mixed integer programming.
problem Learning treatment policies for patients with limited data.
method Prescriptive networks (PNNs) trained with mixed integer programming.
result PNNs outperform existing methods in reducing peak blood pressure.
Deep Claim predicts payer responses from claims data using deep learning.
problem Predicting payer responses from claims data to improve healthcare performance.
method Learning complex dependencies in claim inputs to create a compact representation, then using deep learning to predict responses.
result Deep Claim improves claim denial prediction by 22.21%.
Study insurance pricing under correlation ambiguity without increasing prices or reducing utility.
problem Understanding the dependence structure between insurance and financial risks.
method Dynamic equilibrium analysis of insurance pricing with worst-case beliefs.
result Correlation ambiguity does not necessarily increase insurance prices or reduce insurers' utility.
Paper proves Pareto efficient insurance for multiple entities.
problem Optimizing insurance for multiple policyholders and insurers.
method Sum-minimization characterization and pairwise implementability analysis.
result Characterization of Pareto efficient insurance arrangements.
Study on systemic risk in European insurance sector, showing insurer connections during stress.
problem Understanding systemic risk connectedness in European insurance sector.
method Common connectedness framework applied to returns, volatility, value-at-risk, and expected shortfall.
result Insurers are a significant component of systemic risk connectedness, especially during stress episodes.
The paper examines how risk reduction and insurance choices interact under convex premium principles.
problem Interaction between self-protection and insurance demand under convex premium principles.
method Investigates optimal prevention efforts and insurance shares using distortion risk measures.
result Self-protection and insurance are complementary, but ex ante moral hazard can turn this into a substitution effect.
Parametric insurance offers better risk-sharing in high-risk settings than traditional indemnity insurance.
problem High-risk environments where traditional indemnity insurance is unaffordable or ineffective.
method Comparison of excess-of-loss indemnity insurance and parametric insurance within a mean-variance framework, considering fixed costs and binding budget constraints.
result Parametric insurance yields higher welfare for risk-averse individuals, especially when indemnity insurance is impractical.
The paper examines insurance market dynamics and optimal regulation.
problem Equilibrium outcomes in dynamic insurance markets.
method Analyzes three equilibrium outcomes: positive, zero, and market failure.
result Insurers may accept underwriting losses by investing profits, especially with negative correlations.
We consider an investor who wants to select her/his optimal consumption, investment and insurance policies. Motivated by new insurance products, we allow not only the financial marke but also the insurable loss to depend on the regime of the economy. The objective of the investor is to maximize her/his expected total d…
Optimal insurance contract limits insurer's risk exposure variance.
problem Designing an optimal insurance contract limiting insurer's risk exposure variance.
method Derive optimal policy semi-analytically, focusing on actuarially fair case.
result Expected coverage is larger for wealthier insured, indicating normal good.
Paper models demand and solvency for index insurance, combining traditional and measurable index-based coverage.
problem Reducing protection gaps for emerging risks.
method Develops a model for demand and solvency conditions, combining traditional and index-based insurance.
result Deduces a product that benefits from both traditional and index-based insurance approaches.
Two pension funds mutually insure against longevity risk.
problem Mutual insurance against systematic longevity risk for pension funds.
method Mathematical demonstration and market clearing condition.
result Insurance provides little benefit when fund preferences are similar, but can be beneficial when preferences vary significantly.
Reinsurance can help life insurers maintain higher capital guarantees without losing utility.
problem Decreasing capital guarantees in life insurance products.
method Dynamic investment-reinsurance optimization problem with simultaneous Value-at-Risk and no-short-selling constraints. Introduced guarantee-equivalent utility gain for comparison.
result Optimally managed reinsurance allows insurers to offer higher capital guarantees without reducing expected utility.
The study examines how formal index insurance compares to informal risk sharing in managing natural disasters.
problem The challenges of natural disasters and the effectiveness of index insurance in risk management.
method A three-strategy evolutionary game model to analyze the competitive relationship between formal index insurance, informal risk sharing, and non-insurance.
result Basis risk and loss ratio significantly impact the adoption rate of index insurance, with different strategies preferred under varying conditions.
This paper explores how insurance contracts can be traded in financial markets.
problem The exclusion of arbitrage in insurance contracts due to their non-tradability.
method Defining strategies on insurance portfolios and combining them with financial trading strategies.
result The existence of an insurance-finance-consistent probability, leading to the expected discounted cash-flows.
Paper analyzes strategic underreporting in competitive insurance markets.
problem Strategic underreporting by insureds in competitive insurance markets.
method Develops a dynamic insurance market model with two competing companies and a continuum of insureds, examines the interaction between strategic underreporting and competitive pricing under a Bonus-Malus System framework.
result Establishes the existence and uniqueness of the insureds' optimal reporting barrier and its dependence on BMS premiums; proves the existence of Nash equilibrium premium strategies.
Study of insurer games with model uncertainty in reinsurance and investment strategies.
problem Model uncertainty and competitive insurers' performance under worst-case scenarios.
method Formulated robust mean-field game for non-linear system, derived closed-form solutions.
result Relative concerns lead to new hedging terms in investment and reinsurance strategies.
New model for insurance states using Markov jump processes with non-countable state space.
problem Modeling insurance states with non-countable state spaces.
method Developed a new Thiele's differential equation for continuous time rehabilitation rates.
result Allows for consistent calculation of reserves in disability insurance.
The paper models insurance market dynamics under uncertainty and financial frictions.
problem Modeling insurer behavior under uncertainty and financial frictions.
method Dynamic equilibrium model of insurance market with competitive insurers maximizing shareholder value.
result Investment can lead to lower insurance prices and negative loadings under certain conditions.
Probabilistic ML improves healthcare data analysis.
problem Insufficient understanding and incomplete data in healthcare.
method Examination of probabilistic machine learning models for healthcare challenges.
result Probabilistic models enhance healthcare data analysis and model building.
Study of insurance market equilibria with risk-averse policyholders.
problem Analyzing optimal insurance contracts in a monopoly market with risk-averse policyholders.
method Modeling Stackelberg equilibria with a profit-maximizing insurer and a risk-averse policyholder.
result Equilibrium contracts exhibit a layer-type structure, providing full insurance over pessimistic loss layers and no coverage over optimistic ones.
Develops a Bonus-Malus model for cyber risk insurance to incentivize cybersecurity.
problem Lack of effective insurance strategies to incentivize cybersecurity.
method Proposes a Bonus-Malus model and a mathematical model with a numerical algorithm.
result Demonstrates how a Bonus-Malus system resolves moral hazard and benefits the insurer.
Study compares ruin probabilities under independence vs. dependence assumptions.
problem Underestimation of ruin probability when claims are dependent.
method Copulas for claim dependence analysis, sensitivity analysis.
result Dependent claims lead to underestimation of ruin probability.
Optimal insurance strategy for maximizing RDEU under various premium principles.
problem Maximizing a risk-averse individual's RDEU with insurance priced by a distortion-deviation principle.
method Proved necessary and sufficient conditions for the optimal solution, considered ambiguity orders, and analyzed specific examples.
result Conditions for no insurance or deductible insurance to be optimal.
The paper calculates bonus values in complex insurance schemes.
problem Calculating bonus payments in multi-state with-profit life insurance.
method Combines financial risk simulation with insurance risk methods.
result Efficient numerical procedures for bonus calculation.
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.
Study optimal investment-reinsurance strategies in equity-linked insurance products using Stackelberg game theory.
problem Optimizing investment and reinsurance strategies in equity-linked insurance products with capital guarantees.
method Modelled as a Stackelberg game where reinsurer acts as leader and insurer as follower, with general utility functions and power utility functions analyzed.
result Derive Stackelberg equilibrium for general utility functions and calculate it explicitly for power utility functions, finding reinsurer optimizes premium to incentivize maximal reinsurance purchase.
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 finds farmers are willing to pay higher premiums for higher coverage in agricultural insurance.
problem Determining the demand factors and WTP for agricultural insurance.
method Conducted a survey of 200 farmers to analyze the impact of socio-demographic variables and premium on insurance purchase decisions.
result Farmers are willing to pay higher premiums for higher coverage in agricultural insurance.
A statistical description and model of individual healthcare expenditures in the US has been developed for measuring value in healthcare. We find evidence that healthcare expenditures are quantifiable as an infusion-diffusion process, which can be thought of intuitively as a steady change in the intensity of treatment …
Survey of extreme value modeling techniques for insurance.
problem Modeling of insurance industry's extreme events.
method Truncation, tempering, censoring, regression techniques.
result Adapted techniques for insurance applications.
Develops workflow for synthetic insurance datasets.
problem Lack of realistic publicly available insurance datasets.
method Uses CTGAN neural network architecture to generate tabular data.
result Synthesized datasets evaluated positively in multiple aspects.
Extends insurance-finance arbitrage concept to include model uncertainty.
problem Evaluating hybrid insurance products in uncertain financial markets.
method Introduces robust asymptotic insurance-finance arbitrage and QP-evaluations. result No robust asymptotic insurance-finance arbitrage exists under certain conditions.
Proposes a framework to create fair IDRs by enforcing demographic parity constraints.
problem Discrimination in IDRs trained on biased data.
method Incorporates DP and CDP constraints into IDR estimation.
result Theoretically optimal IDRs can be efficiently obtained through perturbations.
Study on cyber insurance viability using statistical models.
problem Exploring insurability of cyber risk and its factors.
method Regression models (GAMLSS, ordinal regressions) and utility modelling.
result Provides insights into insurability of cyber risk.
Under the Basel II standards, the Operational Risk (OpRisk) advanced measurement approach allows a provision for reduction of capital as a result of insurance mitigation of up to 20%. This paper studies the behaviour of different insurance policies in the context of capital reduction for a range of possible extreme los…
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.
In this paper we investigate the local risk-minimization approach for a combined financial-insurance model where there are restrictions on the information available to the insurance company. In particular we assume that, at any time, the insurance company may observe the number of deaths from a specific portfolio of in…