Posts Tagged ‘underwriting’

Determining Apartment Building Risk

Ideally we all would like to know the amount of risk involved before making a decision.

That’s why we evaluate the side-effects before trying out a new medication, check online reviews before eating at a restaurant or check a vehicle’s motor history before purchasing a used car. It’s safe to say that knowing certain information pertaining to risk helps us to understand what we’re really getting ourselves into, especially as it pertains to investing in rental property.

Knowing the true risk of a rental property reduces losses even when unexpected events occur. Historically, commercial underwriters have approached the problem of assessing risk with a mixture of tactics such as: Examining prior losses, reviewing ownership information, and weighing historical property characteristics in addition to other external risk factors that may play a role, such as local crime rates.

An underwriter may review the property using an internet search for pictures of the property and by obtaining residents’ reviews or complaints about property management. Underwriters may also issue a loss control inspection to review the roof, property maintenance and other potential hazards to assist in the overall property risk assessment.

However, without incorporating resident data into the underwriting process, it’s hard to paint a comprehensive picture. That said, insurers can gain valuable insight to assess the risk for every property by using predictive analytics. Here are some tips to consider during the underwriting process.

The Current Process

Some insurers will manually review rental rates to determine the quality of the resident risk. However, rental rates do not give a clear picture because they can vary significantly by region and do not precisely assess the residents’ overall risk profile. Reliance on benchmark pricing to determine an overall rate also requires understanding an area’s price points.

Next Steps

Today’s habitational insurance market is similar to the 1980s homeowners’ market when the industry relied on property characteristics and inspections for pricing and underwriting information. The homeowners’ industry learned that one of the most important underwriting factors, the resident owner, was missing from their pricing and underwriting process. As a result, the industry made huge segmentation gains from the creation of insurance scores based on the resident (or owner’s) credit.

New technology and real-time resident data can help commercial residential insurers aggregate information such as the occupants’ ages, the age distribution for the entire property and the average occupant tenure. Then, a tenure distribution can be performed to identify residents at a given address, enabling commercial underwriters to obtain a single aggregated risk profile of the residents. Now the insurer has the entire picture, which includes a risk score, average age and tenure to weigh into the model.

Determining Insurance Risk

A property usually displays a complex combination of insurance risks. A multi-resident property can include good insurance risks, poor insurance risks, or any mix of the two. Unlike personal credit lines that rely on a single report, the system must account for the overall mix of residents in determining the insurance risk. For example, 90% of the residents in an apartment building could have excellent credit-based insurance scores and 10% could have poor credit-based insurance scores compared to a property where all residents produce average scores. When comparing the risk factors for both, the question becomes – which of these apartments is riskier? A habitational risk score can segment these two different properties and provide a clear assessment of the insurance risk.

Based upon an internal analysis, policies scoring in the riskiest 10% score group have loss ratios approximately 50% higher than an average loss ratio, and they are two to three times higher than policies scoring in the best 10% score segment. The loss ratio results will vary by region and carrier depending on their overall rate adequacy and loss peril mix.

A habitational risk score is most effective at pricing for what appears to be similar properties on the outside but have wholly different risk factors on the inside.

An Example Of Hidden Risk

While the apartments pictured on the previous page appear to be very similar in age, construction and rental value, they present very different risks based on the resident data. The apartment that scored 840 has the best risk and could qualify for the best rate. If all three apartments were rated about the same, the insurer using the habitational risk score would be able to better price these risks, particularly if the benchmark pricing was being used previously. The insurer not using the habitational risk would write the insurance for the poor insurer scores, resulting in adverse selection.

How often do scores change? For renewal scores, three in four properties do not change radically year over year. The properties that are more likely to be subject to changes in scores are generally smaller properties.

A Comprehensive Picture Of Risk

Commercial residential property insurers have attempted to use loss control inspections as a means to assess risk caused by the behavior of occupants, but inspections are ineffective at measuring the total insurance loss potential. Residential data, flowing from improved technology tools, has a significant impact in the commercial residential market, in line with the impact that insurance scores had on personal lines in an earlier era. This trend allows insurers to more accurately price commercial risk, a substantial win for the industry and the customers they serve.


Source: Property Casualty 360

Underwriters Get Ready For Crewless Ships

Autonomous ships are being explored by the cargo industry, giving marine insurers about five years to determine the costs of covering a crewless ship for risks that can occur at sea.

And the lack of historical data typical of any new technology is complicating the process of underwriting the risks of unmanned ships.

“As insurers, we need to get data,” said Andrew Kinsey, a former ship’s captain and now a New York-based senior marine consultant at Allianz Global Corporate & Specialty S.E. “We need a method to safely and effectively implement unmanned vessels and get the data we need.”

He suggested a convoy scenario, where several unmanned vessels would be chaperoned by a manned vessel, “riding herd, like a sheepdog,” he said. An autonomous vessel would be best suited to replace dry-bulk carriers that operate in intercontinental trade, according to three-year research project Maritime Unmanned Navigation through Intelligence Networks, as these ships travel slowly, transporting cargo such as timber or steel in long, uninterrupted ocean voyages.

“The insurance industry has been at the forefront of most pioneering projects now covering drones, satellite launches, satellites in orbit, test flights, remotely controlled underwater vehicles and a number of other automated products,” Sean Woollerson, London-based senior partner at JLT Specialty Ltd., said in an email. “But a vessel being operated remotely from onshore will bring unique challenges in the developing of a fully automated complex key component for the supply chain.”

Those challenges include pirates, a fire at sea and the time involved to reach the ship if a computer malfunctions. Alan Jervis, founder of Marine, Transportation and Energy Insurance Experts, a consultant to the worldwide insurance, risk management, shipping and transportation industries based in Toronto, points out that a ship is different than other vehicles that may operate autonomously. For one, a cargo ship will be isolated on the ocean.

“One of the duties of the crew is to ensure the cargo is inspected, that it doesn’t leak or break through and cause a fire,” Mr. Jervis said.

Shipping services provider Clarkson P.L.C. puts the number of cargo ships operating now at 9,600. Though none are unmanned, crewless smaller vessels are expected to be in use in three to five years, with larger merchant ships, those carrying oil and heavier cargo, arriving in 10 to 15 years, according to the Royal Institute of Naval Architects, a London-based professional organization whose members work in the design, construction, maintenance and operation of marine vessels and structures.

Europe is prime territory for their use, facing issues such as increased cargo volume and environmental requirements and a decline in the number of sailors. So the Europe Commission funded the three-year MUNIN research project to investigate the possibilities of unmanned ships. MUNIN, completed in August 2015, used 10 years of global manned ship data to compare risks of manned ships to those of unmanned ships and projected that an unmanned ship would have one-tenth of the risk of a manned ship in foundering and collision, in which human error often plays a role. The analysis also predicted a savings of $7 million over a 25-year period per ship in fuel use and crew supplies and salaries.

“This is less about pros and cons of a crew and more about how insurers can analyze risk,” Tom Hoad, London-based head of innovation at Tokio Marine Kiln Group Ltd., said in an email. “Undoubtedly one of the benefits is that better informatics means that insurers might be in a better position to calculate risk. Risk managers use advanced modeling tools to determine risk. Perhaps one of the downsides, though, is the question of what new risk emerges from not having a crew.”

To Mr. Jervis, liability and a credible backup plan if something goes wrong at sea would be paramount to cover the millions of dollars of cargo generally on ships.

“There wouldn’t be anyone there if there was a breakdown of the computer systems,” Mr. Jervis said. “You could have a train break down in the city of Chicago and a crew could come in minutes, but the Atlantic can be a one-week voyage and the Pacific two to three weeks.

“When it comes to drone technology in any line of transportation, there is no one-size-fits-all approach. Insurers have to look at every risk on a case-by-case basis and decide what the individual threats are,” Mr. Hoad said. “Typically insurers calculate risk by comparing the known volatility of a similar class to the new one. For example, light aircraft gave the industry more data about unmanned aerial vehicles. But vessels have unique risks, such as pirates.

Although the Royal Institute of Naval Architects considers pirates to be “virtually a nonissue for fully unmanned ships, it cites the lack of crew to take hostage and the ease of creating control systems that cannot be operated by nonauthorized personnel.

“Pirates would need an ocean-going tug to steal the ship or cargo,” the Royal Institute of Naval Architects said in a January statement.

With 23 years in the Merchant Marines, including 13 as captain of five vessels, Mr. Kinsey disputes that, saying an unmanned vessel at sea would be at higher risk of piracy.

Speaking from experience with pirates, Mr. Kinsey said: “I believe that a human presence on board with active piracy measures in place is an effective deterrent to a pirate boarding.”


Source: Hellenics Shipping News