Like in many other sectors, personal data and algorithms are increasingly being used by insurers in their underwriting, claims, and rating practices. Whilst these advances can bring benefits, concerns have been raised about the quality of information sources and the rationale for using algorithms, particularly because insurance practices are high-risk and minority groups could be especially vulnerable to discrimination.
In response to these concerns, Colorado’s General Assembly enacted legislation last year that restricts insurers’ use of ‘external consumer data’, prohibits data, algorithms, or predictive models from unfairly discriminating, and requires insurers to test their systems and demonstrate that they are not biased. Here are 10 things you need to know about this legislation.
1. What practices are prohibited under the legislation?
Insurers are prohibited from unfair discrimination in insurance practices and the use of external customer data and information sources or algorithms and predictive models that unfairly discriminate.
2. What are the requirements?
Insurers are required to i) outline the type of external customer data and information sources used by their algorithms and predictive models; ii) provide an explanation of how the external consumer data and information sources, and algorithms and predictive models are used; iii) establish and maintain a risk management framework designed to determine whether the data or models unfairly discriminate; iv) provide an assessment of the results of the risk management framework and ongoing monitoring; and v) provide an attestation by one or more officers that the risk management framework has been implemented.
3. How does the legislation define an algorithm?
A computational or machine learning process used to inform human decision-making in insurance practices.
4. How does the legislation define a predictive model?
A process of using mathematical and computational methods that examine current or historical datasets for underlying patterns and calculate the probability of an outcome.
5. How does the legislation define external customer data and information sources?
A data or information source that complements an insurance practice or provides lifestyle indicators. Examples of sources include credit scores, social media habits, purchasing habits, home ownership, educational attainment, locations, occupations, licensures, civil judgements, and court records.
6. What does unfair discrimination mean?
Unfair discrimination occurs when external customer data and information sources or algorithms or predictive models correlate with protected characteristics (race, colour, national or ethnic origin, religion, sex, sexual orientation, disability, gender identity or gender expression) and result in a disproportionately negative outcome for these groups that exceeds the reasonable correlation to the underlying insurance practice (in respect to losses and underwriting costs etc.).
7. Does additional data need to be collected?
Insurers are not required to collect data relating to race, color, national or ethnic origin, religion, sex, sexual orientation, disability, gender identity, or gender expression.
8. What are the next steps?
Following a stakeholder engagement process, the Colorado Insurance Commissioner will establish bespoke rules for specific types of insurance and insurance providers, in relation to assessing and providing evidence of whether unfair discrimination is occurring. These rules will also likely establish penalties for non-compliance and a reasonable period of time for insurers to remedy unfair discrimination.
9. Are there any exemptions?
The legislation does not apply to title insurance, bonds executed by qualified surety companies, or insurers issuing commercial insurance policies. It does apply to insurers that issue business owners’ policies or commercial general liability policies if these policies have annual premiums of $10,000 or less.
10. When does this legislation come into effect?
The legislation will come into effect on 1st January 2023 at the earliest.
Holistic AI can help your firm:
- Establish a risk management framework for continuous monitoring of data, algorithms and predictive models
- Examine models and data for bias (unfair discrimination)
- Provide expert evidence for non-discriminatory practices
Get in touch with a member of our team to find out more about how we can support your journey towards compliance.