Are you a (re)insurer looking to adopt AI and machine learning (ML) techniques to boost your performance and the efficiency of your processes? Do you want to nurture a culture of innovation in your company?
We can deliver a virtual workshop designed to educate your team on the applications of AI and machine learning. Through this 1.5-hour interactive session we will cover the most relevant use cases in the insurance domain and the opportunities and challenges posed by adopting these advanced technologies. Our experts will provide practical examples, share lessons learnt from successfully delivered AI and ML projects and run exercises tailored to the specificities of your business. We will also provide insights on how you can upskill your team to enable them to develop, train, test and deploy models in a safe, controlled manner and how you can address aspects of model transparency and explainability.
This workshop is intended for insurers, reinsurers and pension funds, and will be relevant for senior stakeholders and key members of your Risk, Actuarial, Finance, Accounting, Reporting and Underwriting teams.
The topics that will be covered include:
- Customer segmentation
- Machine learning in pricing, assessment of fairness
- Chatbots, customer support
- Extracting information from documents
- Mortality and lapse (churn) predictions
- Fraud and anomaly detection
We will help you identify and prioritise your projects to maximise return on investment. The agenda for the session is shaped jointly with you, according to your business needs.
About the team
Bence is a senior actuary with 20+ years of experience in life actuarial science and reporting in Solvency II, IFRS, BMA EBS and ICS regulations. His focus has been on actuarial and risk modelling - including capital projections, market risk management and internal model validation – and ERM framework design. Bence delivers business transformation, reinsurance, new authorisation and M&A projects and is keen on applying machine learning and data analytics for actuarial use cases.
Marino is a Senior Quantitative Risk & Machine Learning consultant at Finalyse. He is a qualified actuary with 7 years of experience. He has successfully delivered several projects for banks and insurance companies including a conversational chatbot, AI-powered price optimisation engine, Deep Learning time-series forecast models, challenger software for Credit Risk, AML, and PEP models for traditional and fully digital banking. His expertise extends to non-life insurance pricing, risk modelling, and regulatory frameworks such as IFRS and Solvency II. He is proficient in Python, Linux, Docker, Flask, GCP, Azure, AWS, and various other tech stacks.
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