Description: Business success in the future depends on assumptions we make today. However, we operate in a dynamic environment and cannot know with certainty what lies ahead. Addressing the challenge requires a synergy between data science, expert judgement, and decision making to spot changing drivers of key risks and respond with appropriate business action. We will be presenting development of such an "ecosystem" technically enabled by Natural Language Processing to monitor and detect signals from news streams. NLP is of increasing importance for insurance companies. Additional application examples are available in session 23.

Description: This session will cover assumption determination for annuities under VM-21 with emphasis on contract holder behavior assumptions, prudent estimate mortality assumptions and measuring credibility.

Description: PartnerRe Life and Health is rapidly growing its presence in global markets. This growth means that our medical underwriting team has to handle 25 percent more cases every year. To manage these additional cases without increasing headcount at the same pace, the team has to operate more and more efficiently. In a market where response time is a key differentiator, we improve efficiency by using machine learning to triage and prioritize the underwriting team's case work. In this talk, we describe the model pipeline end to end. That is, we cover the entire implementation chain from accessing data to the eventual evaluation of the added value. In particular, we discuss often neglected topics such as model risk mitigation, technical deployment of the model and integration into business processes.

Description: Feature article discussing the power of psychosocial data.

Description: This article summarizes five key lessons we have learned in implementing LDTI and shares our insights on practical ways to address them. This is not an exhaustive list of implementation challenges, but companies that can successfully tackle the issues we describe should have a smoother data and systems implementation transition.

Description: This article explains the importance of centralizing modeling departments. It goes further and explains the importance of making all aspects of modeling reusable. It explains the consequences of decentralization.

Description: Blockchain technology has the potential to significantly improve the quality of life and overall health of the members of a health system, while also adding to administrative efficiencies. For the first time, we will have access to members’ entire diagnoses and prescription history, consumer behavioral attributes, and other socio-economic determinants which that are valuable inputs to designing appropriate benefits and proper care management plans. Through the blockchain, we will be able to access data not just of the existing members of the health system but also of potential enrollees and new entrants. The data can be accessed by querying the blockchain through a permissioned granted by the member. This information can be very useful in performing feasibility studies for evaluating entry into newer markets and/or newer products, developing customized care plans, and designing efficient value-based contracts. By executing smart contracts on the blockchain, we will be able to achieve administrative efficiencies like never before. The applications of blockchain technology are numerous and ground-breaking. Organizations that do not pay heed to the benefits that blockchain can bring may find themselves left behind as the rest of the industry marches forward in its quest for efficiency and member satisfaction.

Description: Read about The Bulletin Board Updates on important events related to the Technology Section.

Description: A personal account of how humor in the workplace improved productivity.