Applying actuarial expertise to create management insights


Successfully completed projects and tasks

Actuarial controllingImprovement of an Excel based model used for business planning.I corrected a large number of errors, improved the stability of the model, added cross checks. My model was then used for the mid term business planning of my client.
AuditPerform audits and lead audit teams. Communicate findings with client.Timely completion of audit engagements with all areas covered and no uncaught issues remaining.
DocumentationWrote and reviewed documentation e. g. for reporting processes and actuarial models.Reviewed MCEV documentation on group level and improved it where necessary (e. g. with respect to consistency, clarity). Rewrote the corresponding manual, taking into account feedback from stakeholders such as local entities.
Due diligenceAnalyses of business transactions with focus on risk capital situation.Evaluation of investment case and estimate risk capital based on standard formula.
Due diligence regarding reinsurance contractA client was contemplating taking up full reinsurance for a part of its in force business. I helped with the processes by coordinating activities between actuarial departments, the reinsurance department, accounting and the potential reinsurers that were invited. I prepared information packs including PowerPoint slide packs for various committees and made sure information was ready at the agreed deadline.All involved parties were well informed and information was compiled with a level of detail appropriate to the recipients.
Implementation of UnifyI supported business units with implementing the Unify software used to manage the production process for IFRS 17. This included assessing the existing process and requirements and integrating the Risk Agility Financial Modeller (RAFM) production at the core of this process. The processes was designed to be as flexible as possible, e. g. by reading in relevant parameters necessary for steering the process instead of hard coding those parameters into the workflow.The client can now run projections on Unify by uploading a management table that is filled in Excel. The Unify model has already been successfully used in a couple of reporting cycles. As the first business unit was very happy with the outcome, I got referred to colleagues from other business units which I also helped with the implementation.
Methodology developmentDeveloped tailor made methodologies based on legal requirements and client's specific situation.Developed a model for expense inflation which was to be presented to the regulator for model approval.
Methodology reviewReviewed and gave advice where to improve methodology.Reviewed the profit and loss attribution methodology.
Model developmentDeveloped and tested models based on Prophet and MoSes/Risk Agility Financial Modeller (RAFM).Developed an ALM model in Prophet (Life-DFA); developed models for clients in MoSes and improved performance of models in RAFM.
Oracle SQLBuild extensive queries in PL/SQL including documentation within the code and additional accompanying documents.Developed an extensive PL/SQL query (as a package) which can be run to populate a table that is used to deliver data from one team to another, including built in checks and validation reports. This package collects data from a number of different tables, does a series of additional calculations and data cleaning and aggregates it into the target table.
People managementLead teams of up to 10 actuaries.Hired and managed a team in Bratislava.
Project managementManaged change projects, ensuring milestones are reached in time, communication with stakeholders, set up dashboards.Managed a group wide project where reporting responsibilities were in part moved to a service centre in Bratislava.
ProposalsAcquired leads and co-authored proposals for new projects.Successfully and continuously acquired projects.
PythonSet up Python models that read in data, perform analyses and produce outputs as Excel files and charts.I built a machine learning model that predicts the Solvency II (SII) ratio based on a standard set of economic inputs. I tested polynomial regression, random forest and a number of differently configured neural networks. Especially neural networks are able to near-cast the solvency ratio with a very satisfactory precision.
ReinsuranceSet up a model to calculate reinsurance payments based on a live portfolio from the client. The goal was to use this model to calculate the semi annual payments (in and outgoing) based on the reinsured portfolio. A secondary goal was to validate the contract with respect to potential ambiguities and feasibility of calculations.Based on my feedback, some contractual formulae were updated to make them more concise, easier to implement and better aligned with the intended risk transfer.
Also my model is now used to calculate the net payments between insurer and reinsurer.
ReportingI supported the client with reporting tasks with respect to statutory planning and forecasts, Solvency II (SII) quarterly reports and reporting requirements by the local regulator. I did this with minimal introduction and only basic existing documentation, which I heavily extended during the process.All deadlines were met and results were reported correctly. As a part of the process, steps were streamlined, additional safety checks were built in and errors in the (mostly Excel based) reporting tools were systematically identified and corrected.
Risk Agility Financial Modeller (RAFM) model upgradesTable access was revised to be compatible with Unify table management (using an alternative approach to external sources which proved to be more flexible and more transparent). Inputs to the RAFM model were better managed, obsolete variables were removed and common coding errors were fixed.The client has a model that is running faster, where assumptions are better organised, with a fairly lean and transparent implementation due to an alternative approach to external sources.
Risk capital modelDeveloped models, mainly using Excel/VBA and corresponding reports / dashboards.Developed a group risk capital model.
Risk reportingReviewed and consolidated reports from local business units, prepared calculations and reports for own risk capital components.Aggregation and diversification of risk capital and presentation of impact to management.
Solvency II model implementation in PythonImplemented the Solvency II (SII) standard formula in a Python model. This Python model reads in all relevant parameters and data, calculates the individual risk capital quantities and performs their aggregation using the prescribed correlation matrix. This includes the market and life underwriting risks as well as the counterparty default risk module (credit risk).The new model is very flexible as all parameters are read through an Excel sheet. The calculation is very fast (less than 10 minutes for a full run) and transparent. Complex and/or repetitive calculations are performed in functions, the code can be easily reviewed and is commented in line. My client uses this model now instead of the prior Mathcad model.
Surrender value calculationsThe actuarial team had to perform surrender value calculations to support the customer service. This included verifying the surrender value based on account statements issued by the investment company plus calculating surrender charges. Special care had to be taken when contracts were adjusted. Although the process was supposed to be automated, there were a lot of special cases to be considered plus known issues with the implemented surrender value tools. Also numbers by the various systems involved in the process did not always reconcile, which had to be resolved or at least validated or raised as an issue.All calculations were performed within the agreed response times and customer service received correct surrender values. I found out several bugs which were corrected in the meantime.
Valuation of investment caseReview and restructuring of valuation modelsWas asked to review around a dozen investment cases and corrected them where necessary.