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Women have noticeably better behaviour on insurance and credit

It is generally accepted that financial inclusion is essential for creating a society where everyone has equal opportunity. As such, now and again, it is prudent to provide a fact-based perspective that sheds light on how men and women manage their finances in key areas like insurance and credit. Intriguingly, data indicates that women exhibit measurably better risk behaviour in these areas, through better mortality rates in life insurance, lower short-term insurance risk, and better credit behaviour.

Insurance

When it comes to life insurance, women have far better risk behaviour.

This considers the fact women in South Africa have a 65-year life expectancy at birth compared to 59 for men according to Statistics SA (note the estimates dropped by average of 3.5 years due to Covid-19). Much of this is attributable to elevated health risk in men, but the difference in accidental death rates is startling, with females in their 20s having a six-times lower accidental death rate.

The difference reduces as age increases, mainly due to male rates dropping, but women remain 3-to-4 times less likely to suffer accidental death than males in their 40s and 50s. These statistics are also impacted by driving behaviour.

In terms of short-term insurance such as car insurance, while women make up roughly half of drivers, international statistics indicate that over 70% of vehicle claims are from men, with men outnumbering women 3:1 for speeding offences and are almost double as likely to have high-speed accidents.

On the FNB base, short-term risk for women is significantly lower than for men at the age of 20, but risk for both men and women reduce with age, basically converging from around 45 years onwards. The impact of this is that life and short-term insurance for women are significantly less expensive on average because women are at lower risk than men.

Credit

In general, credit scoring models do not consider gender, so these statistics are purely for behavioural purposes. Interestingly, statistics suggest that men are significantly more likely to apply for and obtain credit for credit cards (30% more likely), loans (50% more likely), and vehicle financing (60% more likely), whereas the likelihood of men and women obtaining a mortgage is roughly even.

In contrast, our estimates indicate that 46% of women fall into the lowest two credit risk categories, indicating that they have the best credit profiles, compared to only 38% of men. There are also significantly fewer women in the highest credit risk categories, with only 14% of women rating as high credit risk compared to 21% of men.

While the purpose of this analysis is to provide a behavioural overview of gender risk outcomes, it also demonstrates the role of data on financial prospects and outcomes, in these examples clearly showing better risk in females. We conclude by commenting that data is a powerful resource for society to address inequality by measuring progress in areas such as financial inclusion.

Christoph Nieuwoudt is FNB’s chief data and analytics officer.


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