As the insurance industry delves deeper into AI, insurance professionals are encountering many new terms. However, many of these terms are not actually new. “Deep learning” is a good example.
Auto insurance policyholders are fleeing their insurers. Recent figures are both alarming and intriguing. It’s true that some auto insurers will lose customers, but most customers will go on to
Bias in auto insurance underwriting is a serious risk. Biased practices can lead to lawsuits and regulatory action. They can also cause some drivers to miss out on good insurance
When insurance underwriters don’t have the full picture regarding an applicant’s risk, they are at a disadvantage. This imbalance – in which the insurance applicant has more knowledge than the
Insurance fraud is a problem that just won’t go away – but could that change? Although bad actors will always try to find ways to cheat the system, artificial intelligence
There are two basic ways to gain market share: through slow but steady growth and through bold moves that take advantage of major shifts in the market. Now, the next
Many auto insurance underwriters aim to separate good, bad, and ugly insurance risks. Theoretically, good risks are safe drivers, bad risks are dangerous drivers, and ugly risks are fraudulent applicants.
An insurer decides to adopt a new underwriting solution that harnesses the power of machine learning. The executive team is super excited about the potential for greater profitability. They are
For every risk, there are countless variables to weigh against the price of insurance to determine if the rate will be adequate. Unfortunately, human underwriters can’t identify all factors and
The property and casualty insurance sector doesn’t have a claims problem. It has an underwriting problem. Although high losses from severe crashes, inflated repair costs and natural disasters have put
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