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Traditional commercial insurance underwriting is an extremely time-consuming, hands-on process. (Quality Stock Arts/Adobe Stock)

The term underwriting is credited to renowned Lloyd’s of London. In the early days of Lloyd’s, this term meant an acceptance of a part or entire risk of an event in exchange for a premium.

Since then, the term has evolved with ever-changing circumstances. Insurance underwriting has always relied on data to make decisions. To be in sync with today’s fast-paced and volatile world, underwriting is once again on the cusp of change. The entire insurance industry—customer expectations, products, competition, distribution channels, analytics and data technology—is rapidly changing. The most impactful shift in the industry has been the move into the digital age as information has become publicly available via online sources. In order to walk hand in glove with clients, carriers need to develop at a faster rate than their customers.

AI is the answer

Underwriters are regularly thrown vast amounts of data to inspect, which eats up their time and leaves room for human error. Today’s highly commoditized market, pricing and service are the only differentiators that help underwriters come out ahead of their competition, so they need to be quick.

Moreover, traditional commercial insurance underwriting is an extremely time-consuming, hands-on process. Business owners looking to purchase insurance may not be completely forthcoming about their associated risk, leaving insurance providers in the dark. That saddles the underwriter with the detective work; underwriters are forced to leverage nonsense resources to paint an accurate depiction of risk.

Another layer of complication for underwriters is our world of instant gratification where people are used to immediate answers from tech giants like Google and Amazon. This expectation translates to business, too, in that data is expected to be complete, accurate and provided in real time. To remain competitive, underwriters need to respond quickly while maintaining their diligent level of accuracy.

There are many resources that can be used to verify data, but it’s unreasonable to perform these validations without an automated process. All these pressures can weigh on underwriters, causing burnout, low morale or worse, resignations.

Empowering underwriters

Before that pressure becomes insurmountable, companies must spark a change. As an industry, we need to be empowering underwriters with artificial intelligence (AI) that will find the relevant information they then review. Not only does this reduce human error; it enhances fraud detection and enables higher accuracy profiling.

For example, Plank’s artificial intelligence solution accurately captures billions of data points from online sources and organizes it into actionable insights using machine learning, with simply a business name and address. Machine learning is also able to uncover new risk factors and insights such as the material that was used for flooring by a restaurant from analyzing a new photo uploaded on social media. This insight creates efficiency and a robust predictive capability that offers carriers a significant advantage, allowing them to pick and choose prospects based on their custom risk appetite.

Underwriting brings with it a multifold approach to a variety of tasks that AI can assist with every step of the way, including:

  • Customer acquisition: Customer relations are the core of any business and with AI, underwriters have more time to focus on cultivating and maintaining these relationships without being knee deep in paperwork. Technology helps create lead segments for targeted outreach, increase conversion rates which ultimately improves agent and customer experiences.
  • Automated submissions: Underwriters can spend hours on data entry but solutions like prefill policy application data and one-click submission-to-quote backed by AI, help streamline the quoting process.
  • Streamlined policy monitoring: Real-time data helps update, enrich and maintain portfolio data as well as assesses new risk and underwriting insights which keeps the process smooth and supports faster premium and policy auditing.
  • Simplified renewals: Underwriters can leverage real-time risk profiles and minimize the back and forth between underwriting teams and agents.

With these supports in place, underwriters spend less time per account as well as less time quoting bad leads. This allows them to better service more accounts and write more new business.

The path to underwriting success

It is also imperative to point out that AI is a tool created with the purpose of enabling underwriters a clearer path to success. As with any new technology, companies will need to address the benefits during the implementation stage. Making sure underwriters see the technology as support instead of a threat can smooth over any trepidations of introducing a new methodology. AI does not do the actual underwriting but rather automates the gathering and validating of data and streamlines processes. If there is an anomaly, the underwriter is further empowered to explore as only underwriters can.

Maintaining a determined drive to foster change throughout an organization helps in deploying new technology when it becomes available. With only a few days of focused training, underwriters have been able to adopt these technologies for their benefit.

The outcome of properly embracing AI in the insurance process is increasing submission-to-quote speed, reducing loss rations, creating better pricing models and more. This benefit is passed onto the end customer as faster and more competitive quotes paired with accurate claims to detect risk and help prevent or cover it.

At the end of the day, it affords underwriters the power to work faster, armed with all the information they need at their fingertips.

Planck CEO and Co-Founder Elad Tsur is a serial entrepreneur who is passionate about bridging the gap between technology and business. These opinions are the author’s own.

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