actuarial_math

Usage example:

The code below creates a term-life insurance model for an insured age x=30 at issue with 30-year term, with benefit of 1000 payable at end year of insured’s death. We calculate the APV by termlife.calculate_apv(). We can also calculate the level premium such that the expected loss is zero, by termlife.minimum_level_premium().

import actuarydesk.financial_math as fm
import actuarydesk.actuarial_tables as at
import actuarydesk.actuarial_math as am

int_rate = fm.InterestRate(0, 0.04, 'annual')
table = at.table_dictionary['UK_ONS_2016_to_2018_male']

x = 30; term = 30
benefits = [am.Benefit(i, 1000) for i in range(x+1, x+term+1)]

termlife = am.TermLifeInsurance(x, term, benefits, [int_rate], table)

apv = termlife.calculate_apv()
minimum_premium = termlife.minimum_level_premium()

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The code below shows an example of generating a cashflow for a particular model: insured age 50 with a 15-year term life insurance, the benefit amount is 10000 payable at the end year of death. The level-premium are paid at beginning of each year until term ends or as long as survival.

import actuarydesk.financial_math as fm
import actuarydesk.actuarial_tables as at
import actuarydesk.actuarial_math as am

table = at.UK_ONS_2016_to_2018_male
int_rate = [fm.InterestRate(0, 0.05, 'annual')]
x = 50; term = 15;

benefits = [am.Benefit(i, 10000) for i in range(x+1, x+term+1)]
ins_model = am.TermLifeInsurance(x, term, benefits, int_rate, table)

model = am.ActuarialModel(ins_model, ['due', 'annual'], 2020)
reserves = model.reserves_dynamics_df(0.5, 70)
cashflow = model.cashflow_df(65)