When it comes to automated underwriting, the sentiment among insurers is one of hopeful skepticism: They’re hopeful that all the data these systems supply will make their underwriters more efficient and accurate, but skeptical that it really will.

“There is certainly a tremendous amount of data for insurers,” says David Capps, an underwriting specialist at property/casualty insurer Liberty Mutual Insurance. “But the problem still lies in aggregating it.”

Making voluminous amounts of data available to underwriters, Capps says, is only helpful if they know what it all means and have the time to think about it. At the same time, he acknowledges that new technologies like Google Maps have revolutionized aspects of underwriting − like the process of insuring a building.

“Before that technology, if I couldn’t actually go to the building because of cost constraints, I’d need to insure it on faith,” he says. “Now I can see it in real time and for free.”

BOOSTING PRODUCTIVITY

For decades, pricing and risk selection were conducted according to best practices and received wisdom passed down from one generation of underwriters to another. Then, as more data sources became available and more affordable analytic tools arrived on the scene, insurance companies looked to gain a competitive advantage by applying the new tools to the newly available data.

Take the example of one regional carrier in California. “In the past, they had underwriters who were unable to work remotely,” says Abhijeet Jhaveri, chief marketing officer at Value Momentum, an insurance software and services provider and the maker of the DealFoundry Underwriting & Portal software used by the carrier.

Bogged down by a process that revolved around paper files, the insurer saw an opportunity to improve productivity by going paperless and automating many of its underwriting processes, which − not coincidentally − gave its underwriters the ability to access and work with files from outside the office.

The effort paid off, and the insurer was able to reduce the time it took to gather information and improve collaboration between its underwriters and agents. The initiative also helped the insurer identify bottlenecks in the underwriting process, which allowed it to boost submission volumes without adding additional personnel, according to Jhaveri. But the biggest payoff was, perhaps, how the new process helped the insurer’s underwriters see the big picture and improve the consistency of their pricing decisions.

Re-engineering underwriting processes to reduce approval times has been another major industry focus. At P&C and specialty insurer XL Group, deploying a new, global underwriting platform led to a 40 percent improvement in underwriting efficiency, reports John Belizaire, CEO of insurance software developer FirstBest, which XL Group adopted for its platform. The new platform makes it easier for U.S. and international teams to collaborate and to incorporate advanced pricing analytics into their decision making, and the carrier’s revised operating model, which is supported by the new system, makes it much easier for the underwriting teams to respond to new business initiatives.

A DISSENTING OPINION

Yet Jerry Burroughs, a principal at Beaverton, Ore.-based West Coast Insurance, questions the nature of what these systems are automating. “It appears to me that we are simply applying more sophisticated technology to transmit data, but have not substantially automated the process of risk profiling and data assembly − especially within commercial lines of business,” he says.

The challenges of underwriting automation, Burroughs notes, depend in part on the size of the insurer. Large carriers, he says, can fund more software development and tend to have more sophisticated applications.

Yet the larger carriers are also more burdened with legacy underwriting systems, which are extremely difficult to integrate with the newer, data-driven applications. In contrast, insurers in the small commercial market extend underwriting guidelines − in the form of program rules and logic − to the point of sale very effectively, Burroughs explains. This helps these smaller carriers increase their win rates without sacrificing risk quality.

“The smaller carriers are more nimble, and the highly specialized carriers can more easily develop software that maximizes automation,” he maintains. An insurer that uses analytics to determine which submissions it wants to underwrite can respond very quickly to agents submitting potential business, observes Celent analyst Donald Light.

For example, he says, insurers specializing in wind perils previously took a first-in-first-out approach to underwriting a submission. Modern underwriting systems, however, use a variety of data and analytical techniques to evaluate submissions, identify the ones with the greatest potential and move them to the head of the queue. Simultaneously, they weed out clearly undesirable risks, saving precious time for both under writer and agent.

Analytics, data models and external third-party data integration are imperative to address the globalization of risk, asserts Karen Pauli, research director at insurance consultancy CEB TowerGroup. “The emerging challenge,” she says, “is how to bring in additional external data to the underwriting process to support the underwriter in a complex decision process.”

According to Pauli, risk complexity has come down-market. It used to be that the complex risks associated with commercial lines only applied to jumbo globe-straddling organizations. Today, however, issues such as terrorism and supply chain risk affect all types of businesses. The proliferation and availability of data can be the salvation of any insurer attempting to manage global risk − or it can be its downfall if the insurer fails to leverage the appropriate technology. “Even small and mid-size business have risks everywhere,” she says. “The complexity of those risks and the proliferation of information” are what define the insurance landscape.

The outlook for underwriting is one of more automated decision-making for the commercial markets, agrees Deb Smallwood, founder of market researcher Strategy Meets Action.

Smallwood notes that the explosion of new data sources will continue to put pressure on manual underwriting processes. Looking ahead, underwriters will need advanced predictive models to make use of all the data. It comes down to this, she says: “Insurers who fail to invest won’t be in a position to compete for scale, growth and profit.”  INN

 

Three Questions for FirstBest CEO John Belizaire

INN: Why the increased emphasis on underwriting automation?

Belizaire: The new attention is driven by a “changing of the guard” at many insurers and new leadership that’s more analytically inclined. We often meet with companies when they have just hired a new chief underwriting officer, CEO or SVP of distribution. Typically, these executives have a mandate to shake things up and find innovative ways to compete in an ever-changing market. They very quickly realize the need for new tools and the need for a strategic front-office platform that allows them to digitize and transform.

In many cases, that platform is an advanced underwriting workstation that leverages data analytics and delivers powerful, real-time and actionable insight right to an underwriter’s desktop. Once an insurer experiences the agility, collaboration and analytics provided by today’s underwriting technology, it’s hard not to pay attention. In fact, the technology tends to energize progressive insurers and encourages them to innovate.

INN: What are insurers hoping to accomplish with these new systems?

Belizaire: Executives are continually under pressure to grow their business fast. So they need underwriting systems to greatly improve the speed and efficiency of their underwriters. For example, in a recent underwriting efficiency survey by FirstBest, we confirmed that many underwriters spend more than 50 percent of their time on administrative tasks and data gathering as opposed to risk analysis. Under- writing executives want systems that automatically and efficiently deliver timely, actionable data directly to their underwriters.

Also, more and more, insurers are emphasizing improved underwriting quality as a key corporate initiative. As a result, underwriting executives are under pressure to design more consistency into their underwriting operations. If they can get every underwriter to assess risk as well as their best underwriters, the company can gain significant competitive advantage and even become best-in-class. So, these executives are looking for their underwriting systems to digitize and extend best practices, streamline collaboration with expert underwriters, and to simplify peer reviews and referrals.

In addition to writing more business, writing the right business is a key imperative. As insurers enter new markets or look to expand in their current markets, there’s an intensified focus on choosing the best risks for the company’s portfolio. Consequently, chief underwriting officers require their underwriting systems to be data-sensitive and analytic-driven, helping them to uncover blind spots and support more advanced pricing models.

INN: What factors are influencing the type of underwriting automation that’s taking place?

Belizaire: The industry is under pressure due to a number of macro trends. First, there’s a tremendous influx of capital from private equity, municipalities and hedge funds. This puts pressure on insurers to use this capital to grow and grow fast.

Second, because there is more capital chasing limited opportunities, there’s increasing pressure on price and therefore on profit. So insurers want assurance that the increasingly complex risks they are taking on have gone through a rigorous assessment and will likely be profitable.

Third, low interest rates have decreased the returns on insurers’ investment portfolios, leading carrier risk managers to demand better performance from underwriting. And finally, insurance is no longer a local business, but a global business − and this is especially true of specialty insurance. U.S. companies are buying international firms, and European and Asian companies are buying U.S. firms. Most companies operate in multiple geographies, making strategic and proficient underwriting automation a global initiative for many insurers.

The combination of exponential increases in the volume of structured and unstructured data, combined with the maturing of modern predictive analytics, sets a new minimum standard for what underwriting “automation” means. Today and for the near future, the performance of insurance companies will be largely determined by how well they can combine data and analytics with underwriting risk analysis to drive profit. Expressed as a simple equation: “Data + Underwriting = Insurance Excellence.”

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