Underwriting systems have long provided a competitive advantage to the carriers that heavily invested in these systems. However, that advantage is in danger of slipping away.
Recent advances in speed and efficiency, and increased compatibility with other technology throughout the enterprise, are lowering the cost of adoption, quickly making the systems ubiquitous. In fact, all lines of business are increasing their focus and IT spend by at least 3 percent over last year on improving underwriting, according to insurance consultancy and research firm Strategy Meets Action (SMA).
As insurers look to provide underwriting systems with an extra boost to realize new competitive advantages, CIOs can anticipate more fluent, pervasive integration of predictive modeling and analytics.
The combination of underwriting with sophisticated analytics improves pricing models and enables insurers to go beyond portfolio-level thinking and evaluate a potential policy at an individual level by running analyses on what could happen with the risk.
But implementing and supporting these systems presents various data challenges.
Injured Workers Insurance Fund (IWIF) took it on, searching for an underwriting system that would enable it to react quickly to market changes by updating risk profiles and automation controls.
The insurer recently selected FirstBest's Underwriting Management System and Agent Portal, to be implemented and in use by spring 2013. With the new system in place, IWIF expects to streamline its operations and give its underwriters more time to analyze data rather than only gathering it.
Paige Beck, CFO, IWIF, explains the type of flexibility they're after: "If we determine that we need an additional field, or if we have an underwriting rule today that we want to look different next week because something has alerted us to an issue that we need to put in front of the underwriter, we see FirstBest as facilitating a quick turn-around time when making those changes, adapting to those changes, so the organization can adapt to the changing marketplace."
With such configurability at insurers' fingertips, companies can also go beyond portfolio-level thinking when investigating a risk and evaluate a proposed policy at an individual level by running analyses on what's going to happen if you take it on. Thus, an insurer can continually re-evaluate its overall portfolio based on potential individual risks before taking them on.
"A predictive model can help you rank, say, all flower shops applying for coverage," says Julian Pelenur, FirstBest CTO. "You can stack them according to risk. In this format, you can price them accordingly, from highest to lowest risk."
The benefits here are twofold: The carrier can potentially lower its loss ratio by charging more for the riskiest policies, and also maintain a high level of competitiveness by providing cheap rates for less risky policies.
As top-tier insurers perfect automation and the ability to pump out policies, that type of adaptability will continue to provide lower- and mid-tier insurers with an underwriting edge. And, to remain competitive in today's market, that underwriting edge is necessary.
"You can no longer say one-size-fits-all," Pelenur says. "In the past, not knowing more about a risk may have caused carriers to lump risks into bigger buckets, and that creates pricing inefficiency. This type of technology enables insurers to have many more buckets and to create more specialized products."
Indeed, the bar is being raised in terms of not only internal efficiencies, such as precise monitoring of risk and profitability, but also in terms of pricing and product offerings. According to SMA, the area of the business where big data was cited as most likely to be a game changer was pricing models.
Developing a Knack for Niche
Simon Bell, COO of LOGiQ3, a consulting and outsourced services provider, acknowledges that optimizing risk and product portfolios may not be as important as speed and efficiency, particularly for large personal lines insurers going after volume. However, the rest of the market is increasing its ability to underwrite more accurately by taking advantage of the growing access to data and the advancing sophistication of modeling.
"The smaller, medium-sized players are trying to look at their data differently and saying, 'These are the niches we should be in; what can we do that one of the big guys can't do?'" says Bell. He goes on to emphasize that, in the near future, insurers should have the ability to look at a book of business, point to what they're doing well, get rid of business that seemed like a good idea 10 years ago and move into the most suitable market.
Even at a company such as IWIF, which specializes in providing workers' compensation coverage in Maryland, segmentation, a trickle-down benefit of advanced data and analytics practices, is considered vital to future growth.
"The underwriter also has the ability to pull information based on different selection criteria," Paige says. "For instance by geography, by pricing tier, by credits given-there's multiple metrics they can use to evaluate their book. An important element is the loss ratio, which is shown by all those different variations, so they can see where they're performing better or worse."
With backlogs of customer data and profitability performance waiting to be accessed and analyzed, this is where insurers can reap competitive advantages if IT and business are on the same page in terms of how they want to react to insights. According to Jim Rourke, SVP of Sales and Marketing at InsPro Technologies, a provider of group and individual policy administration software, we're beginning to see the effects of such efforts already in the form of specialized products and segmentation, much like Bell was outlining.
"We're starting to see more hybrid products coming out today. It goes back to how an insurance company differentiates itself, either with its distribution channels or with its insurance," Rourke says. "They can get more up-to-date data, then the faster you put it in their hands and the better tools they're given, the better they're going to be able to adapt their business."
All of this begs the question, where do underwriters fit into this rapidly evolving web of business processes? If underwriting is becoming more a fulcrum for data-driven business development and less a simple matter of risk assessment, does this mean underwriters have been right all along to resent the inevitable tides of change that technology has represented for them?
Not Disappearing, Just Evolving
While the business case for automation and analytics may have initially involved overhead saved from staff reductions, ROI has since been found elsewhere. As the byproducts of tech-enabled decisioning become increasingly self-evident-precise monitoring of loss ratio and profitability to begin with, and most importantly, increased scalability-staff numbers are more commonly headed in the opposite direction.
In fact, if you haven't beefed up your underwriting staff yet, be prepared to.
"If you look back, underwriters may have been more focused on incremental efficiency through traditional initiatives such as outsourcing, document management and data cleansing," FirstBest's Pelenur says. "Looking forward, those things are solved. The focus now lies with higher sophistication and analysis that enables more business."
No matter what vertical an insurer resides in, the future of underwriting is policies processed with more accuracy and at a faster rate. This means that thanks to the aforementioned scalability that automation and data supplementation have enabled, and contrary to the cultural backlash from underwriters performing their centuries-old trade, underwriting staffs are generally experiencing increases.
However, this doesn't mean that the position won't need to also evolve along with the technology.
"In our own underwriting shop, we have seasoned, 30-year-plus underwriters who, as they're providing knowledge to junior underwriters about what it means to underwrite, they're picking up how to use an iPad, and how to go about getting the data they need," says Bell. "It's not always ideal, but that's the kind of relationship that will evolve. Both sides of the demographic have something to lend each other."
Beyond new technology, underwriters are also likely to face decisions that affect and manage information that comes from various parts of the enterprise. Such is the case with Chubb Insurance, according to Chubb's Personal Lines CIO, Nicole Brouillard, who says her company continually reinforces training and support as they integrate new tools.
"As we're changing underwriting, we're probably changing the way our customer service reps do their work and how it ultimately is impacting our agents or our customer. So there is always an impact on the whole," says Brouillard. "[The method of processing the ongoing transformations] is a constant evolution of new solutions, training, adapting, feedback, then bringing that feedback back into our solution. It's a whole echo system."
Creating a cyclical training process such as Chubb's, as well as balancing the polished underwriting instinct of seasoned veterans and the tech-deftness of fresher talent, appear to be unrelenting HR challenges of the future.
Unstructured Data: A Tough Nut to Crack
Regardless of operational or business goals, the tech challenge of the future regarding underwriting is tapping into as much siloed, unstructured data as possible.
As the integration of structured data-in the form of third-party sources via the Web and internal, clean data such as online analytics-into underwriting processes is becoming more fine-tuned and prevalent, unstructured data. And, the technology solution providers that are making an effort to work through the integration with the insurer are becoming more attractive. Yet, as Chubb and many insurers are finding out, the process remains a difficult nut to crack.
"We have rich transactional data, but it's very siloed," laments Chubb's Brouillard. "For example, whether it's our customers and agents who call us or transact with us on the Web, throughout all of these silos of data, the issue we face, as well as the industry in general, is mastering all these data sets to then get the insights we need."
The problem is that more advanced tools are needed to convert former methods of retention-paper document, voice recordings, etc.-to structured, clean data that can be integrated into an enterprise network and dispersed accordingly. For example, insurers have been waiting a long time to be able to scan documents in a way that automatically interprets and sorts the resulting file based on the text it contains. Subsequent systems that facilitate such stores of data and integrate it into underwriting and enterprise operations are the stuff of IT insurance professionals' dreams.
"We're in touch with insurance C-level execs and entrepreneurs, and there's a general feeling that there's got to be a better way to do these things, but nobody's cracked it yet," says LOGiQ3's Bell. "They're waiting for someone to take these new technologies-social media, big data and all the other things buzzing around-and come up with a real value proposition. They're waiting for someone to say 'We're going to write 20-, 30-, 50-percent more business because we've figured out how to blend these things into underwriting in a way that nobody else has.' Once that happens, everyone will wake up and say, 'It's here, and we need to copy these guys.' But nobody has done that yet."
Big data promises to enhance underwriting in just about every way-efficiency, scalability, reliability and so on. Nevertheless, while insurers wait for a way to sort and integrate unstructured reserves, they must remain vigilant in preparing internal operations and processes for the agility that will be required to take full advantage of such rich expanses of data when it becomes available.
"The biggest challenge will be turning it into action," says Chubb's Brouillard. "Whether your systems have the right agility and the right flexibility to change behavior depending on the information, that will be Chubb's, and probably the industry's, biggest challenge."
