ACTOMATE
LOSS MODEL ROBOT
The Loss Model Robot is an analytics and decision-making tool that helps insurers compare insurance and reinsurance structures to make optimal decisions. It supports simulations using historical claims experience or selected parameters, helping users evaluate how different structures may perform under different scenarios. Users can adjust key reinsurance settings, such as how much risk to retain, how much risk to transfer, and the level of protection need for different business lines. The solution then produces clear result summaries to help teams understand the possible claims cost, risk exposure, and financial impact under each scenario. It also helps insurers estimate the target reinsurance premium they should pay for different reinsurance structures. By making the analysis faster and easier to review, the solution supports more informed and practical reinsurance decisions.
For more information on Loss Model Robot, click HERE
analytics
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Simulates insurance and reinsurance outcomes using past claims experience or selected parameters.
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Supports multiple lines of business and multiple scenario analysis.
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Helps users review key risk indicators including expected loss, variability, VaR and TVaR.
optimisation
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Compares reinsurance structures such as excess of loss, quota share, surplus share and stop loss settings.
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Helps users estimate the target RI premium to pay for different reinsurance structures
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Supports alignment of reinsurance protection with actual risk exposure.
decision
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Produces quick and easy-to-understand result summaries for management review.
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Supports underwriters, reinsurance teams, actuarial teams and management in making data-driven structure decisions.
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Helps teams choose suitable protection levels while considering cost, risk and capital efficiency.
Who Can Use It
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Underwriters and reinsurance teams for insurance and reinsurance structuring.
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Actuarial departments for portfolio management and risk analysis.
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Management teams for decision-making and review of reinsurance structure options.
Why It Matters
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Enhanced efficiency: reduces manual effort in complex reinsurance structure analysis.
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Improved decision-making: provides data-driven insights from simulations and actual claims experience.
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Customizable approaches: allow users to tailor parameters and structures based on business needs.
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Quick access to results produces immediate and easy-to-understand summaries to support faster decisions
PRACTICE LEADER
Lim Jone Keat
Technology Development Lead
Jone Keat joined Actomate in 2020, he is the Technology Development Lead of the company. He has over 5 years of experience serving as a programmer and software developer in the actuarial industry. Jone Keat has practical experience in both the software development and actuarial works including frontend and backend web applications, application programming interface (API), database, and actuarial valuation in Malaysia.
Jone Keat is proficient in R, Visual Basic for Applications (VBA), HTML and CSS, and he is learning Javascript and Rust programming languages. He is also proficient with actuarial applications and automation tools such as Excel, Data Conversion System (DCS) and Data3Sixty. He has worked on several software development projects, including ReACC Robot for reinsurance accounting, LRC Robot, LIC Robot for IFRS 17, and job recruitment application. To better understand our client needs, Jone Keat is proactively involved in actuarial valuation projects of general insurance. Jone Keat is also an experienced trainer, he has developed training materials and conducted technology trainings to internal staff.
Jone Keat has prior work experience in the economic database company, to ensure the accuracy and timeliness of the economic data and financial forecast. In his prior experience, Jone Keat is equipped with knowledge of building automation tools to enhance the efficiency of the operations, and modelling time series.
Jone Keat graduated from Universiti Tunku Abdul Rahman with a BSc (Hons) in Actuarial Science. He is currently studying towards attaining Fellowship of the Casualty Actuarial Society (CAS).