Ryan Thomas ryanbthomas

Rsvr

This is document is an attempt to define the minimum viable product for a data structure which reserving methodologies can be built off of. The final section has some ideas about the API for rsvr.

tri_df (triangle dataframe)

A tabular data structure (a subset of tibble), used to hold historical claim data that is an input to reserving analysis. It has the following columns:

cohort: (integer or string) [required] A variable that groups claims, or policies together whose development is tracked over time. For example, this might be accident year or underwriting quarter.

	library(microbenchmark)
	library(purrr)
	library(tibble)

	num_sims <- 1000

	lambda <- 0.15
	mu <- 7
	sigma <- 2

	---
	title: "R Notebook"
	output: html_notebook
	---

	```{r}
	# setup
	library(readr)
	library(dplyr)
	library(forcats)

	# Rules
	library(purrr)
	library(dplyr)
	library(tibble)

	dat <- tibble(x = 1:3, y = 4:6)

	f1 <- function(tbl) {

	mutate(tbl, z = x*y) %>% select(z)

	x <- rnorm(1000, 7, 2)
	noise <- rnorm(1000)

	y <- 5 + 2 * x + noise

	df <- data.frame(x = x, y = y)

	test_idx <- sample(1000, 100)

	test_df <- df[test_idx, ]

	Missouri DOI allows you to request zip code level aggregated datasets for several lines of business. This has to be requested via email.
	If combined with Census Information on income/race it could be used as a monitor for redlining.
	https://insurance.mo.gov/reports/