Implementation of Gaussian Process Regression in Estimating Motor Vehicle Insurance Claims Reserves

This study aims to calculate the allowance for losses by applying Gaussian Process regression to estimate future claims. Modeling is done on motor vehicle insurance data. The data used in this study are historical data on PT XYZ's motor vehicle insurance business line during 2017 and 2019 (January 2017 to December 2019). Data analysis will be carried out on the 2017 - 2019 data to obtain an estimate of the claim reserves in the following year, namely 2018 - 2020. This study uses the Chain Ladder method which is the most popular loss reserving method in theory and practice. The estimation results show that the Gaussian Process Regression method is very flexible and can be applied without much adjustment. These results were also compared with the Chain Ladder method. Estimated claim reserves for PT XYZ's motor vehicle business line using the chain-ladder method, the company must provide funds for 2017 of 8,997,979,222 IDR in 2018 16,194,503,605 IDR in 2019 amounting to Rp. 1,719,764,520 for backup. Meanwhile, by using the Bayessian Gaussian Process method, the company must provide funds for 2017 of 9,060,965,077 IDR in 2018 amounting to 16,307,865,130 IDR, and in 2019 1,731,802,871 IDR for backup. The more conservative Bayessian Gaussian Process method. Motor vehicle insurance data has a short development time (claims occur) so that it is included in the short-tail type of business.

Floral Diversity, Ethnobotanical and Cultural Significance of Medicinally Important Wild Edible Fruits in Northern Pakistan

The current exploration provides an important ethnobotanical data about the usage of Wild Edible Fruit species from Northern Pakistan. It is the first study on the ethnobotanical uses of WEFs, quantitatively assessed using several indices. A novelty of use reports, part use and mode of utilization is derived from comparison with previous published research works. The major focus of this investigation is to document the traditional information, usage and to assess conservation status of WEFs. Ethnobotanical information is recorded through semi-structured and open-ended interviews using questionnaire and group discussions from 538 local informers of varied ages, gender, education levels, and experience. The ethnobotanical information was quantitatively analyzed using indices like FIV, RFC, FIC, RI, UV, JI, FI, CI and PR. The study reported 95 WEF species and their traditional uses, belonging to 38 families, 58 genera with 47.4 % trees, 36.8 % shrubs and 15.8 % herbs. Family Rosaceae dominate the list of families by 23 species, followed by Rhamnaceae 9 species and Moraceae 7 species. Family Berberidaceae represents highest values for FIV (47.7 %). The maximum utilized plant part(s) is fruit used in raw form (47 %), 53 species are categorized for food and medicinal purpose, 33 species for Join/Body aches, 53 species for digestive disorders and 39 species of WEFs are specifically used in respiratory complaints. Mean FIC was (0.25) indicates low agreement of respondents for disease categories, FIC for Joint/body aches was highest (0.72), digestive disorders (0.5) and Respiratory complaints (0.4). Use value suggests high relative importance for Punica granatum (0.6), followed by Juglans regia (0.05). The average mean percentages on use reports was (18 %) for each species. Traditional knowledge is prevailing in the region, found more in people of old ages as compared to young ones. Many of the WEFs documented have multiple uses, and a single fruit species for many tenacities. The study encompasses the need to conserve the traditional knowledge and carry out future phytochemical investigations to appraise important minerals, nutrients, antioxidant potential and toxic effects of WEFs. The study will serve as a reference data for nutritionists, particularly in food chemistry, health and industry. In addition, ways and means are needed to preserve and use natural reserve in a maintainable way.