A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
New method for individual claims reserving using machine learning.
Model predicts individual insurance claim reserves using activation patterns.
New method simplifies individual claims reserving.
Reinforcement learning improves insurance claims reserving by learning from all claim trajectories.
Traditional non-life reserving models largely neglect the vast amount of information collected over the lifetime of a claim. This information includes covariates describing the policy, claim cause as well as the detailed history collected during a claim's development over time. We present the hierarchical reserving mod…
Develops a new GLM framework for claims reserving with adaptive estimation.
LLMs help automate extraction of actuarial variables from unstructured claims data.
The article derives a formula for predicting claims uncertainty using the GCC method.
New model bridges pricing and reserving for insurance claims.
New model for disability insurance reserving handles delays in claim information.
Our article considers the class of recently developed stochastic models that combine claims payments and incurred losses information into a coherent reserving methodology. In particular, we develop a family of Heirarchical Bayesian Paid-Incurred-Claims models, combining the claims reserving models of Hertig et al. (198…
In this paper we examine the claims reserving problem using Tweedie's compound Poisson model. We develop the maximum likelihood and Bayesian Markov chain Monte Carlo simulation approaches to fit the model and then compare the estimated models under different scenarios. The key point we demonstrate relates to the compar…
The paper proposes an original methodology for constructing quantitative statistical models based on multidimensional distribution functions constructed on the basis of the insurance companies' data on inshurance policies (including policies with deductible) and claims incurred. Real data of some Russian insurance comp…
Paper proposes a new reserving model using machine learning techniques.
A method for analysing the risk of taking a too low reserve level by use of Chain Ladder method is developed. We give an answer to the question of how much safety loading in terms of the Chain Ladder standard error has to be added to the Chain Ladder reserve in order to reach a specified security level in loss reservin…
Within the Solvency II framework the insurance industry requires a realistic modelling of the risk processes relevant for its business. Every insurance company should be capable of running a holistic risk management process to meet this challenge. For property and casualty (P&C) insurance companies the risk adequate mo…
We propose a novel approach for loss reserving based on deep neural networks. The approach allows for joint modeling of paid losses and claims outstanding, and incorporation of heterogeneous inputs. We validate the models on loss reserving data across lines of business, and show that they improve on the predictive accu…
In this paper the utility optimization problem for a general insurance model is studied. The reserve process of the insurance company is described by a stochastic differential equation driven by a Brownian motion and a Poisson random measure, representing the randomness from the financial market and the insurance claim…
Neural networks improve loss reserving with case estimates and transaction data.
We consider a large, homogeneous portfolio of life or disability annuity policies. The policies are assumed to be independent conditional on an external stochastic process representing the economic-demographic environment. Using a conditional law of large numbers, we establish the connection between claims reserving an…
Optimizes insurance pricing to minimize ruin probability under various claim dependencies.
RL-CVaR model improves insurance reserving under economic stress.
Chain-ladder reserving is sensitive to outliers, leading to unreliable estimates.
New models for insurance claims accounting for delays.
Paper proposes robust methods to detect and treat outliers in multivariate loss reserving.
In this article we consider the parameter risk in the context of internal modelling of the reserve risk under Solvency II. We discuss two opposed perspectives on parameter uncertainty and point out that standard methods of classical reserving focusing on the estimation error of claims reserves are in general not approp…
This paper addresses recalibration issues in hedging callable assets, proposing a new risk-adjusted approach.
We develop a class of non-life reserving models using a stable-1/2 random bridge to simulate the accumulation of paid claims, allowing for an essentially arbitrary choice of a priori distribution for the ultimate loss. Taking an information-based approach to the reserving problem, we derive the process of the condition…
SynthETIC simulates insurance claims with customizable features.
A new framework combines multiple loss reserving models for better predictive performance.
Neural network model improves loss reserving accuracy and distribution flexibility.
Paper addresses unbalanced data in common shock models for loss reserving.
In this paper, we detail the main simulation methods used in practice to measure one-year reserve risk, and describe the bootstrap method providing an empirical distribution of the Claims Development Result (CDR) whose variance is identical to the closed-form expression of the prediction error proposed by Wüthrich et a…
We provide a dual characterisation of the weak-closure of a finite sum of cones in adapted to a discrete time filtration : the cone in the sum contains bounded random variables that are -measurable. Hence we obtain a generalisation of Delbaen's m-stability condition…
Consider two insurance companies (or two branches of the same company) that receive premiums at different rates and then split the amount they pay in fixed proportions for each claim (for simplicity we assume that they are equal). We model the occurrence of claims according to a Poisson process. The ruin is achieved wh…
Develops a support-aware framework for reserve-policy selection in advertising markets.
We consider a financial contract that delivers a single cash flow given by the terminal value of a cumulative gains process. The problem of modelling and pricing such an asset and associated derivatives is important, for example, in the determination of optimal insurance claims reserve policies, and in the pricing of r…
The paper models SaaS products as insurance, offering new pricing tools.
The net-premium principle is considered to be the most genuine and fair premium principle in actuarial applications. However, an insurance company, applying the net-premium principle, goes bankrupt with probability one in the long run, even if the company covers its entire costs by collecting the respective fees from i…
Study compares ruin probabilities under independence vs. dependence assumptions.
Model estimates foreign exchange reserve compositions of undisclosed central banks.
Overprocuring reserves can improve network efficiency by using excess reserves for congestion management.
Study examines value relevance of oil and gas reserve disclosures in London Stock Exchange.
Threadneedle is a multi-agent simulation framework, based on a full double entry book keeping implementation of the banking system's fundamental transactions. It is designed to serve as an experimental test bed for economic simulations that can explore the banking system's influence on the macro-economy under varying a…
Optimal dividend strategy with irreversible reinsurance constraints.
New pricing framework allocates costs of operating reserves and transmission.
Many online companies sell advertisement space in second-price auctions with reserve. In this paper, we develop a probabilistic method to learn a profitable strategy to set the reserve price. We use historical auction data with features to fit a predictor of the best reserve price. This problem is delicate - the struct…
We introduce a new approach to incorporate uncertainty into the decision to invest in a commodity reserve. The investment is an irreversible one-off capital expenditure, after which the investor receives a stream of cashflow from extracting the commodity and selling it on the spot market. The investor is exposed to pri…