Risk assessment has always been one of the most challenging and time-consuming pieces of the underwriting process, but with the help of machine learning, natural language understanding (NLU) and other techniques, underwriting is becoming more accurate and efficient.

It’s important to note that when we talk about machine learning and artificial intelligence, we’re not talking about replacing underwriters with algorithms. Instead, by pairing underwriters with machine learning tools that analyze mass quantities of data, we can create much more accurate risk evaluations. This allows underwriters to work at a higher level, use more data to make accurate assessments and become better at their jobs.