Incorporating Big Data analytics into the underwriting process can be evolutionary for life insurance carriers and their customers. In my previous post, I shared that Big Data analytics have been transformative for other industries, and that those transformative capabilities can easily be applied to the life insurance sector as well. Now I’ll tell you specifically where and how you can unlock opportunities for greater efficiency and business growth by integrating Big Data analytics into your underwriting process.

Offer a less invasive, more responsive customer experience
Today’s competitive market environment requires insurance carriers to be fast, accurate, consistent and nimble. Big Data analytics infuse the underwriting function with all these characteristics by automatically processing vast amounts of data from a variety of resources—quickly, effectively, time after time and in real- or near-real time. Big Data analytics can also create predictive models about an individual based on a wide array of criteria, which can minimize the need to gather additional information from the proposed insured. These capabilities not only shave days or weeks off of processing time, but they also ensure quality data that doesn’t come at the expense of customer convenience. And they can be less invasive to a customer compared to traditional underwriting processes—data that helps you make better, more risk-tolerable individualized decisions.

Manage vast data for a more comprehensive understanding
Interviews and medical exams are the tools of the traditional underwriting process. Not only are they very time consuming, but they also don’t provide the complete picture Big Data analysis delivers. Big Data solutions enable independent verification and advance linking technology that connect a carrier’s system to outside resources, providing a single view of an individual, utilizing various different data sources, literally in sub-seconds. Big Data provides a view that might otherwise be impossible to obtain.

Work smarter, not harder
With ever-shrinking budgets, underwriters are struggling to be more productive. Repetitive, mundane tasks often compete with more complex risks for the typical underwriter’s time and attention. Big Data analytics automate those repetitive, mundane tasks―boosting productivity. In fact, as the future underwriting resource pool shrinks due to attrition, Big Data analytics are expected to play a more expanded role in the underwriting process—contributing to both greater efficiency and additional cost savings.

Attract new business
The speed, convenience, and opportunity for the more individualized rates Big Data analytics promise contribute to an improved customer experience―and that translates to business growth. Additionally, Big Data analytics are helping insurers better understand risks―facilitating expansion into new markets (such as the un- or under-insureds).

If you’re convinced that leveraging Big Data analytics is the right direction for your underwriting function (and I hope you are), in my next post, you’ll find some tips on integrating Big Data analytics into your business.