Generating model points

This notebook generates the sample model points used by the BasicTerm_S and BasicTerm_M models, by using random numbers. BasicTerm_S and BasicTerm_M are new business models, so no duration information is included.

Columns:

• point_id: Model point identifier

• age_at_entry: Issue age. The samples are distributed uniformly from 20 to 59.

• sex: “M” or “F” to indicate policy holder’s sex. Not used by default.

• policy_term: Policy term in years. The samples are evenly distriubted among 10, 15 and 20.

• policy_count: The number of policies. Not used by default.

• sum_assured: Sum assured. The samples are uniformly distributed from 10,000 to 1,000,000.

Number of model points:

• 10000

import numpy as np
from numpy.random import default_rng  # Requires NumPy 1.17 or newer

rng = default_rng(12345)

# Number of Model Points
MPCount = 10000

# Issue Age (Integer): 20 - 59 year old

age_at_entry = rng.integers(low=20, high=60, size=MPCount)

# Sex (Char)

Sex = [
    "M",
    "F"
]

sex = np.fromiter(map(lambda i: Sex[i], rng.integers(low=0, high=len(Sex), size=MPCount)), np.dtype('<U1'))

# Policy Term (Integer): 10, 15, 20

policy_term = rng.integers(low=0, high=3, size=MPCount) * 5 + 10

# Policy Count (Integer): 1

policy_count = [1] * MPCount

# Sum Assured (Float): 10000 - 1000000

sum_assured = np.round((1000000 - 10000) * rng.random(size=MPCount) + 10000, -3)

import pandas as pd

attrs = [
    "age_at_entry",
    "sex",
    "policy_term",
    "policy_count",
    "sum_assured"
]

data = [
    age_at_entry,
    sex,
    policy_term,
    policy_count,
    sum_assured
]

model_point_table = pd.DataFrame(dict(zip(attrs, data)), index=range(1, MPCount+1))
model_point_table.index.name = "policy_id"
model_point_table

	age_at_entry	sex	policy_term	policy_count	sum_assured
policy_id
1	47	M	10	1	622000.0
2	29	M	20	1	752000.0
3	51	F	10	1	799000.0
4	32	F	20	1	422000.0
5	28	M	15	1	605000.0
...	...	...	...	...	...
9996	47	M	20	1	827000.0
9997	30	M	15	1	826000.0
9998	45	F	20	1	783000.0
9999	39	M	20	1	302000.0
10000	22	F	15	1	576000.0

10000 rows × 5 columns

model_point_table.to_excel("model_point_table.xlsx")

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