As the wave of digitization continues to disrupt how insurance agents, brokers, MGAs, and carriers do business, many organizations are looking for new ways to leverage existing technology to enable their producers and increase efficiency. According to Digital Insurance, of the biggest emerging trends in the insurance industry is the leveraging of Artificial Intelligence. It’s common today, even expected, to visit an agent or insurer’s website and be greeted by a friendly chatbot offering up answers to FAQs and providing self-service resources. However, chatbots are only the beginning of how Artificial Intelligence can be leveraged to change how we do business.
In this article, we’ll explore a few ways your organization can implement Salesforce Einstein Next Best Action to provide insights that make insurance agents more productive and help underwriters grow profitable books of business.
How Salesforce Einstein Next Best Action Works
Before we jump into all the great use cases for Einstein Next Best Action, let’s talk a little about the feature itself and how it works. Einstein Next Best Action is a powerful Salesforce AI tool that displays pertinent information and actionable recommendations to your users based on business criteria and logic that you set.
First, you create a reservoir of possible Recommendations. Examples of Recommendations are things like “This customer may be eligible for a rate discount” or “Most insureds with this profile need additional coverage, consider offering XYZ.” Then, you use the Strategy Builder to automate and funnel the suitable recommendations based on the criteria you set. For instance, you would set the tool to recognize that if a particular insured property is in the state of Florida, it should find the recommendation for offering Wind and Hail coverage. Lastly, you choose how and where to display this valuable information to your users. You can display Recommendations on Home Pages, Lightning Record Pages, Visualforce pages, in Communities, and almost anywhere your users would need visibility of the recommended insights.
Insurance Industry Use Case
Now that you have an idea of what Salesforce Einstein Next Best Action is and how it works, I’m sure you’re starting to see the insurance possibilities. For insurance producers, this feature unlocks powerful insights to help them better serve their insureds.
While on an insured’s record page in Salesforce, Einstein can readily identify if that customer may be eligible for rate discounts, be great candidates for additional coverage lines, or is more likely to have a claim and benefit from risk management services. It could also provide insights into which customers are most expected to shop their policies or cancel.
This feature is also powerful for underwriters, who heavily rely on experience and instinct to make underwriting decisions. With Einstein Next Best Action’s intelligence, underwriters can leverage Recommendations to make better decisions about what risks to write, coverages to offer, and endorsements to apply. Your organization can also set criteria for recommendations that advise an underwriter if a policy meets the basis for nonrenewal or cancellation. What’s more, is that the recommendations are reportable and trackable, so you can keep an eye on which recommendations are being surfaced, if they’re being leveraged, and what impacts these recommendations are having on your business.
The possibilities for Einstein Next Best Action are endless!
Join the Insurance Tech Revolution
What’s more, is that the power of Einstein is included with most Salesforce licenses, is usage-based, and is a feature Sikich can work with your organization to leverage today. As the insurance industry’s digital revolution continues, your business can take full advantage of Salesforce’s native features and keep up with the latest technological advancements that add value for your business. Together with Sikich, you can continue moving into the #insurtech era with Salesforce’s Einstein Analytics and Einstein Next Best Action!
Ready to get started? Contact us today.
