66 research outputs found
Applications of Clustering with Mixed Type Data in Life Insurance
Death benefits are generally the largest cash flow item that affects
financial statements of life insurers where some still do not have a systematic
process to track and monitor death claims experience. In this article, we
explore data clustering to examine and understand how actual death claims
differ from expected, an early stage of developing a monitoring system crucial
for risk management. We extend the -prototypes clustering algorithm to draw
inference from a life insurance dataset using only the insured's
characteristics and policy information without regard to known mortality. This
clustering has the feature to efficiently handle categorical, numerical, and
spatial attributes. Using gap statistics, the optimal clusters obtained from
the algorithm are then used to compare actual to expected death claims
experience of the life insurance portfolio. Our empirical data contains
observations, during 2014, of approximately 1.14 million policies with a total
insured amount of over 650 billion dollars. For this portfolio, the algorithm
produced three natural clusters, with each cluster having a lower actual to
expected death claims but with differing variability. The analytical results
provide management a process to identify policyholders' attributes that
dominate significant mortality deviations, and thereby enhance decision making
for taking necessary actions.Comment: 25 pages, 6 figures, 5 table
Real-time Monitoring for the Next Core-Collapse Supernova in JUNO
Core-collapse supernova (CCSN) is one of the most energetic astrophysical
events in the Universe. The early and prompt detection of neutrinos before
(pre-SN) and during the SN burst is a unique opportunity to realize the
multi-messenger observation of the CCSN events. In this work, we describe the
monitoring concept and present the sensitivity of the system to the pre-SN and
SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is
a 20 kton liquid scintillator detector under construction in South China. The
real-time monitoring system is designed with both the prompt monitors on the
electronic board and online monitors at the data acquisition stage, in order to
ensure both the alert speed and alert coverage of progenitor stars. By assuming
a false alert rate of 1 per year, this monitoring system can be sensitive to
the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos
up to about 370 (360) kpc for a progenitor mass of 30 for the case
of normal (inverted) mass ordering. The pointing ability of the CCSN is
evaluated by using the accumulated event anisotropy of the inverse beta decay
interactions from pre-SN or SN neutrinos, which, along with the early alert,
can play important roles for the followup multi-messenger observations of the
next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure
- …