The topic of price-discrimination in insurance pricing has been a significant concern in the insurance industry, especially with the advent of Big Data and the increasing use of advanced algorithms. Let us delve into the details:
1. Background:
- Insurance discrimination issues have been relevant for decades, but they have evolved due to insurers’ extensive utilization of Big Data.
- The growing capacity of computers, innovative data sources, and powerful algorithms has enabled insurers to detect patterns in insurance activities that were previously unknown.
- While fundamental issues of insurance discrimination remain consistent, privacy concerns and the use of algorithmic substitutes have gained prominence.
2. Regulation and Fair treatment:
- Direct discrimination is explicitly prohibited, but hidden unfairness using substitutes or complex algorithms lacks clear specifications or assessments.
- Various numbers-based fair treatment measures have emerged in the computer learning field, especially with the growth of smart technology).
3. Research and Models:
At the 2022 All-Actuaries Summit, Dr. Fei Huang and Xi Xin presented joint work on anti-discrimination insurance pricing. Their study aimed to:
Moreover, review anti-discrimination laws and rules across different officials or governments, focusing on hidden unfairness in the general insurance industry.
Subsequently, summarize fairness criteria applicable to insurance pricing and align them with anti-discrimination rules.
Consequently, implement these criteria into existing and newly proposed anti-discrimination insurance pricing models.
4. Indirect Discrimination:
For more detailed insights, you can explore the full paper via SSRN here1. Dr Fei Huang presented these findings at the 2022 All-Actuaries Summit.
- Some officials or governments(e.g., officials or governments and the EU) define hidden unfairness, but its restrictions for insurance remain unclear.
- The use of big data analytics by insurance companies has blurred the lines, leading to a regulatory uncertain zone.
