Companies that may be challenged by user have several resolution options, namely, a friendly negotiation, trade-off or withdrawal, or, by using court services. In the latter case, the company may let the decision defend itself, or hire attorneys to defend it. The process of choosing to hire attorneys or not is often subjective, fuzzy, unscientific, and case specific. In this use case, we illustrate how machine learning can help insurance companies assess the relevance of hiring an attorney to defend their decisions to minimize attorney services costs, make better decisions that are likely to be irrefutable by customers, and judges otherwise.
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