Life contingencies (aka, “Cálculo Actuarial”) involves predicting events like death, illness, or retirement, which impact individuals and companies. Traditionally, actuaries have used mortality tables to predict life expectancy based on age, gender, and general health. However, with the rise of big data, technology is reshaping how we approach these predictions.
What is Big Data in Life Contingencies?
Big data refers to the large volumes of information collected from various sources, like medical records, wearable devices, and social media. This data allows actuaries to refine their predictions by looking beyond basic demographics to include factors like lifestyle choices, medical history, and even genetic information.
How Does This Work in Practice?
With access to big data, actuaries can create more accurate predictions. For example, using wearable data, actuaries can see how physical activity affects health risks and adjust life insurance pricing accordingly. Machine learning can also help identify patterns in the data, improving risk models and making predictions more individualized.
Ethical Considerations and Privacy
While big data offers more accuracy, it raises important ethical questions. How do we ensure privacy and fairness when using personal data? For example, using genetic data might help predict life expectancy but could lead to privacy concerns. Actuaries need to ensure that their models are not biased and that data is used responsibly.
The Future of Life Contingencies
Big data is transforming life contingencies by improving predictions and personalizing insurance products. As future actuaries, it’s crucial to stay updated on how these technologies can enhance our work while considering the ethical challenges they present. Embracing these advancements will help us provide more accurate and fair services in the field of actuarial science.