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AI Underwriting Assistants and
How They Help Underwriting

Melding artificial intelligence (AI) with insurance underwriting will revolutionize our understanding of risk and enhance our current decision-making processes. The use of AI technology in underwriting is new, but significant advancements have already been made. AI-powered algorithms are at the forefront of some companies, driving improvements in risk assessment and resulting in precision premiums and automated decision-making. This is just the beginning. AI’s full potential in underwriting is not yet fully realized, and we can anticipate further developments that will reshape the industry.

Many underwriters see AI as the Voldemort of our industry—an evil entity casting a death spell on the profession.

Don’t panic. AI isn’t about replacing human underwriters but rather enhancing their capabilities. AI is a valuable tool (like ChatGPT or Claude) and serves more as a copilot in the underwriting process, working with human expertise to create a more robust and efficient underwriting process. Here, we delve deeper into the ethical dilemmas that can arise as AI becomes part of the insurance industry.

Fairness and Bias Mitigation:

Much of humanity’s big data today is biased. Insurance is no different, and we understand this. To eliminate bias, we must recognize it in our underwriting processes. Appropriately trained AI copilots can play a crucial role in promoting fair underwriting decisions.

How so?

Identifying bias: AI can analyze data to detect bias patterns and flag instances of unfair treatment.
Analyzing language: It can scan documents for discriminatory language, ensuring neutral communication in underwriting.
Fair decisions: It can prompt underwriters to reconsider biased decisions, fostering objectivity.
Continuous tracking of patterns: AI continuously monitors outcomes, identifies biased trends, and prompts underwriters to take corrective actions.
Enhancing Competitiveness: Proactive AI in underwriting attracts diverse customers, maintains a positive reputation, and could improve bottom line risk mitigation.

It’s time the insurance industry started viewing AI as Dumbledore—one of the good guys.

That’s great, but do we really know how it does all that?

AI provides transparency in underwriting by not only providing recommendations but also explaining the rationale behind them. This transparency coupled with interpretable machine learning models (which include decision trees, linear regression, and rule-based systems) offers insight into the decision-making process, while building trust with both customers and regulators.

Ok, but does it learn like a human?

It does, through something called continuous machine learning, but that’s a topic for another blog post.

AI’s integration into underwriting is transforming the industry, but ethical considerations loom large. By addressing bias, fostering transparency, and emphasizing the collaboration between AI and human underwriters, the industry can harness AI’s potential to improve the customer experience and help underwriters advance their careers.