Tag Archives: BI

How to Reimagine Insurance With IoT

In our hyper-connected world, it’s no longer just our phones and computers that are connected to the Internet; our homes, our cars and even our own bodies are, too. Voice-activated smart-home systems, wearable fitness trackers and drones are becoming more and more commonplace, showing the profound impact of the Internet of Things (IoT) on our everyday lives – and our businesses.

With global spending on IoT devices and services expected to reach $1.7 trillion by 2020, digital disruption is infiltrating every vertical market, including the insurance industry. In the wake of this disturbance, we are seeing a dramatic rise in investments in innovative digital insurance startups, also known as “insurtechs.” Just as “fintechs” are disrupting the financial services industry, insuretechs are challenging traditional broker-based insurance business models. Now, to meet the needs of today’s consumers who expect anytime, anywhere service and support, incumbents are faced with two options: digitally transform their organizations or go out of business.

Driving disruption: Insurtechs and IoT behind the wheel

In 2015, insurtech investments more than tripled, from $700 million to $2.5 billion, as venture capitalists embrace creative, new business models that reimagine insurance by leveraging Internet-enabled devices, self-serve technologies and peer-to-peer (P2P) platforms. For example, Sequoia Capital recently provided U.S. P2P startup Lemonade with $13 million in initial funding to offer consumer insurance based on self-serve technology. In addition, some of the world’s largest insurers, such as Aviva and MetLife, have formed their own, internal venture capital funds to invest in startups that could propel their digitization efforts.

See also: Insurance and the Internet of Things  

Despite these efforts, the insurance industry is actually one of the least-prepared for the changes that IoT, sensors, big data sources and other disruptive technologies will bring. In fact, a 2016 survey showed that only 36% of respondents from insurance companies said that their organization can use insights from new data sources to boost company value. The good news is that insurers seem to understand the impact that digitization will bring, and the speed and scope of the disruption. A BI Intelligence survey reports that 75% of insurance executives expect to feel pressure to innovate from new data sources, such as IoT devices, within three to five years.

Unlocking new capabilities, new markets with IoT

Insurers must embrace insurtechs and consider the many ways that IoT can help them differentiate themselves in a rapidly changing landscape. With IoT, insurance companies can leverage big data analytics to better understand and underwrite risk, improve loss prevention and even predict consumer behavior. In the home insurance realm, security systems, video monitors, smoke detectors and other “connected home” appliances allow carriers to obtain significant data to help mitigate homeowner risk. Or, car insurance carriers can provide users with applications that monitor driving habits, allowing them to predict risks based on the collected data (as well as give users discounts for safe driving records). We even see property insurance companies using drones to quickly and accurately assess damages, and simplify their adjusters’ workflows.

In addition, the visibility into risk allotted by IoT and internet-enabled devices allows insurers to tap into opaque and difficult-to-serve markets, like cyber liability insurance. This is great news for both insurers and clients. Still, fewer than 10% of companies have cyber insurance, and just seven insurers control about 80% of the entire market. Instead of relying on questionnaires and limited data for underwriting cyber risk, insurers can use IoT technologies and in-depth threat analytics to perform more detailed assessments – and gain a bigger slice of the market.

The customer experience is still king

All this talk about digitization, self-serve technology and changing customer expectations raises a huge question: Where does the agent fit? Will customers be more inclined to rely solely on mobile technology and new types of devices to conduct business, and forgo traditional, “face-to-face” interactions? Rest assured, that is not the case. Rather, insurers can use digital transformation as a means to develop more personalized, engaging experiences that strengthen customer relationships and serve as a competitive differentiator.

In many situations, insurers in the midst of digital transformation are employing agent and digital business models. With “agent and digital,” consumers have the best of both worlds – quick, convenient access to information and purchase of products through mobile devices and other channels, as well as one-on-one, real-life service when they need it. Moreover, these technologies allow insurers to obtain a 360-degree of the client and use analytics to evaluate their behavior, anticipate their needs and offer the best products with the right price, at the right time. Plus, insurers can better connect customer journeys across channels, from new customer acquisition to on-boarding, to service, to claims and more.

Mobile tools are especially useful for agents working in the field. They can quickly consult their carriers’ experts for real-time advice on complex transactions, and even directly connect the customer with the carrier to help close deals and resolve issues faster. The result is a happier customer and a more informed, productive agent.

See also: How the ‘Internet of Things’ Affects Strategic Planning  

As we embark on a new year, the heat is on for insurers to digitally transform themselves, or they will undoubtedly fall behind. However, bringing their digital strategies to life involves more than simply investing in insurtechs and acquiring new technological capabilities. Successfully implementing digital transformation requires insurers to effectively align those technologies to their business strategies and scale them across their entire enterprise. In the end, the insurers that do so will find themselves with greater market share and, more importantly, happier, lifelong customers.

5 Scary Thoughts on BI, Data Warehouses

With Halloween just past, it seems appropriate to blog about something thematic. Usually, the word “scary” isn’t used to describe insurance writings, but there is a twist to one important question that can be as frightening as things that go bump in the night.

Often, a technology adoption discussion starts out with a question about why an insurer should adopt a specific technology. That’s a good question. But the more telling question may be: What happens if you don’t adopt it?

It’s a scary way to look at technology adoption, perhaps, but it is important to assess the implications of not adopting specific technologies. When it comes to business intelligence (BI) tools and data warehouse modernization, there are some very frightening downsides to not putting these critical components of an enterprise data strategy first.

See also: 4 Benefits From Data Centralization  

  • SMA research shows that 53% of responding insurers believe establishing a data strategy should precede a core technology initiative. That still leaves a good percentage of insurers who see things differently. And simply believing a data-first strategy is the right way to go doesn’t mean that executing it is easy. However, insurers who put off data strategies until after core system choices have been made actually run the risk of choosing the wrong provider (architecturally), relative to a data and warehouse strategy that would work best for their organization.
  • Migrating legacy data to modern technology has kept many an IT and business leader awake at night or has given them a data migration nightmare. In fact, the sheer magnitude of doing a legacy data migration has led many insurers to decide to leave legacy data alone, resulting in a myriad of work-arounds. This will most certainly lead to poor service for both customers and distributors. It can also lead to a great deal of added expense and employees who are frustrated by having to deal with work-arounds. A solid data strategy with BI tools and a modern data warehouse can make the migration of legacy data into the new systems significantly easier.
  • Business leaders are clamoring for analytics. Most of the technology demos we see at SMA address (or at least mention) analytics value in one way or another. However, without a data strategy, there may be a disconnect between the data architecture of the technology and the data structures decided on in a later data initiative. The result: delayed analytics value. Waiting for analytics can make business partners feel they are only getting incremental value from the new technology.
  • Many insurers have accelerated core modernization initiatives because of the pressing need for modern portals and expanded mobile capabilities. However, if customer and distributor data is still fragmented — not centralized in a modern data warehouse and not unified with a common data strategy — the full value of portals and mobile will not be attained. And no insurer can afford to fail at fully delivering in these areas.
  • Across a whole host of technology categories, software with out-of-the-box reporting tools is fairly common. On the surface, this seems to be an answer to a lot of problems. However, while technology-specific reporting tools have value, without an enterprise BI reporting tool an insurer can be creating reporting silos… and no insurer needs more silos. Additionally, while software-specific reporting tools may be useful for a specific category of data, such as operational data (which can be very good), they may not be what insurers need to gain deep insights into all categories of data.

There are a lot of scary things in the world today — besides Halloween — that we can’t control: terrorism, cybercrime and global warming, to mention a few. But all insurers can, and should, take steps to minimize the things that provoke fear. Electing to decide on an enterprise data strategy, business intelligence tools and modern data warehouses — and doing so first — is a way to mitigate other worrisome outcomes. Remember when deciding on an enterprise data strategy, BI tools and warehouses was the scary thing? Fortunately, technology has matured. And modern data management tools can be the key to dealing with the next wave of scary things.

How to Assess Costs of Business Interruption

As a professional loss accountant with more than 20 years of experience with business interruption (BI) valuation, I can understand why policyholders struggle with finding a repeatable, efficient system that produces an accurate measurement of their BI exposure. Over the years, some of my clients recognized the issues with the traditional BI values approach, and decided to make a change. Unfortunately, too many companies continue doing what they have always done, even when there is a better way available.

BI

Consider for a moment, just how important BI information is to your underwriter. The numbers you report give the underwriter the basis for writing coverage and calculating premium. Each renewal provides policyholders the opportunity to present their unique BI exposure. Unfortunately, this opportunity is often squandered because of a misunderstanding of business interruption values and the exposures they represent. The point of this article is to share a proven, alternative approach.

Understanding BI Values

First, there’s the ratable value. It is the “big number” that is calculated for the business as a whole, assuming a 12-month, total shutdown of all revenue-generating operations. This worst-case and often unrealistic scenario is the information requested by the insurance company, usually in the form of a one-page worksheet. Without additional information, the underwriter will use this information to set limits and charge premium.

The ratable value calculated is somewhat meaningless, except that it establishes the base assumption that is used as the BI value in all other scenarios, such as unincurred cost categories. The ratable value is seldom a reflection of your exposures. Better ways to assess your exposures are to examine your maximum foreseeable loss (MFL) and probable maximum loss (PML) scenarios.

What Is Maximum Foreseeable Loss?

The MFL, as the name indicates, is the worst-case scenario. This is not as extreme as the ratable value scenario, but pretty close. The assumptions used here include a complete breakdown of protection and loss mitigating factors while you are hit where it hurts at the worst possible time. An example would be the loss of a unique distribution center to a retailer during the holiday shopping season — say the distribution center that handles online orders goes up in smoke on Cyber Monday.

The factors used to measure the ratable value would be used in this scenario to determine the business interruption value. Certain assumptions may change depending on the duration of the loss scenario. For example, labor expense may be considered completely saved in the ratable value scenario because of the assumption that there is nothing left, but only partly saved in an MFL scenario.

What About the Probable Maximum Loss?

The PML is the same as the MFL, except that loss mitigation efforts and protections work properly. The PML also takes into account pure extra expenses used to retain customers. The PML can help with decision making on purchasing extra expense coverage.

What Happens in Underwriting?

Although I’m not an underwriter, I’ve typically seen insurance companies take an engineer’s approach to MFL and PML scenarios that vary only in duration. This singular perspective does not account for the rest of the pieces of the puzzle. The other pieces are the finer details that actually occur during a claim. In a real claim, topics like seasonality, make-up and outsourcing would surely come up, but you won’t see them on any BI worksheet.

The MFL and PML should be based on realistic loss scenarios and measured as if they were a claim. Simply applying the ratable value to loss-period assumptions produces misleading and inflated numbers. This is precisely why it is in your best interest to develop your own valuation method based on real scenarios.

Why Create Exposure Scenarios?

If BI values are based on assumptions, and you are using the worksheet, then the assumption is a 12-month loss scenario. Can you imagine a scenario in which your operations would only be affected for six months? The worksheet makes a blanket assumption of 12 months whether realistic or not. Coming up with various loss scenarios by location would flesh out a more realistic representation of the impact of each particular loss. The scenarios would also highlight high-risk locations along your supply chain, which could improve your business continuity planning.

An exposure analysis project is not only an accounting project; it’s an integrated business exercise offering multiple benefits to an organization. The goal is to identify and examine loss scenarios and the resulting ripple effects.

It isn’t necessary, nor is it practical, to anticipate every possible loss scenario. It’s better to prioritize by perceived risk and probability. Then, develop a good sampling of loss scenarios from which you can determine the impact to operations and the mitigating actions that would be taken. Depending on the exposure, involve the appropriate internal personnel, e.g., operations, sales, business continuity, IT and accounting. The external experts you may involve are your broker, legal counsel and, of course, a forensic accounting firm that specializes in insurance work. Additionally, your company’s business continuity plan (BCP) and incident response plan should be factored in. However your scenarios play out, the loss accountants can calculate the business interruption as though it were an actual claim.

As you can see, this approach would produce a more accurate BI value by location and overall. It’s the right way to look at business interruption, so make it a part of your approach with underwriters.

How to Develop Plan on Terrorism Risks

Terrorist and other mass violence attacks, which occur with alarming regularity around the world, can threaten your people, operations and assets. Many companies look to insurance — mainly property terrorism and political violence coverage – to help manage the financial impact of these risks, which can include property damage and business interruption losses.

Terrorism Insurance or Political Violence Coverage?

Property terrorism insurance provides coverage for the physical damage and business interruption that can result from acts that are motivated by politics, religion or ideology. Political violence insurance provides coverage related to war, civil war, rebellion, insurrection, coup d’état and other civil disturbances.

Choosing which coverage – or combination – is best for your organization can be tricky. The line between what is considered “terrorism” and what is considered “political violence” is often blurry. For example, should attacks by particular groups be classified as acts of terrorism, or another form of political violence?

To help determine the best insurance program to manage these risks, here are a few things to think about:

  • Ensure the limits of insurance that you buy provide enough protection for multiple loss scenarios.
  • Review the location of your assets to determine the appropriate insurance solution.
  • Understand the policy terms, conditions and limitations of terrorism and political violence insurance.
  • Work with your advisers to understand your property and employee exposures so you can make an informed decision or mitigate potential losses.

Addressing the Risks

Along with insurance considerations, of course, you need to ensure the safety of your employees with integrated and well-practiced crisis and continuity plans in the event of a disaster. Events from terrorist attack to natural catastrophes can cause significant business interruption (BI) losses. Steps to take to manage BI risk include:

  • Develop and test business continuity plans.
  • Conduct scenario testing.
  • Coordinate BI insurance with other coverages, including political violence and terrorism insurance.
  • Be prepared to gather appropriate information in the event of a claim, including recording damage via photographs and video.
  • Maintain separate accounting codes to identify all costs associated with the potential damage.

For more information on these topics, read Marsh’s 2015 Terrorism Risk Insurance Report and our political risk insurance report, Strong Capacity Drives Buyer’s Market for Political Risk Insurance.

7 Ways Your Data Can Hurt You

Your data could be your most valuable asset, and participants in the workers’ compensation industry have loads available because they have been collecting and storing data for decades. Yet few analyze data to improve processes and outcomes or to take action in a timely way.

Analytics (data analysis) is crucial to all businesses today to gain insights into product and service quality and business profitability, and to measure value contributed. But processes need to be examined regarding how data is collected, analyzed and reported. Begin by examining these seven ways data can hurt or help.

1. Data silos

Data silos are common in workers’ compensation. Individual data sets are used within organizations and by their vendors to document claim activity. Without interoperability (the ability of a system to work with other systems without special effort on the part of the user) or data integration, the silos naturally fragment the data, making it difficult to gain full understanding of the claim and its multiple issues. A comprehensive view of a claim includes all its associated data.

2. Unstructured data

Unstructured documentation, in the form of notes, leaves valuable information on the table. Notes sections of systems contain important information that cannot be readily integrated into the business intelligence. The cure is to incorporate data elements such as drop-down lists to describe events, facts and actions taken. Such data elements provide claim knowledge and can be monitored and measured.

3. Errors and omissions

Manual data entry is tedious work and often results in skipped data fields and erroneous content. When users are unsure of what should be entered into a data field, they might make up the input or simply skip the task. Management has a responsibility to hold data entry people accountable for what they add to the system. It matters.

Errors and omissions can also occur when data is extracted by an OCR methodology. Optical character recognition is the recognition of printed or written text characters by a computer. Interpretation should be reviewed regularly for accuracy and to be sure the entire scope of content is being retrieved and added to the data set. Changing business needs may result in new data requirements.

4. Human factors

Other human factors also affect data quality. One is intimidation by IT (information technology). Usually this is not intended, but remember that people in IT are not claims adjusters or case managers. The things of interest and concern to them can be completely different, and they use different language to describe those things.

People in business units often have difficulty describing to IT what they need or want. When IT says a request will be difficult or time-consuming, the best response is to persist.

5. Timeliness

There needs to be timely appropriate reporting of critical information found in current data. The data can often reveal important facts that can be reported automatically and acted upon quickly to minimize damage. Systems should be used to continually monitor the data and report, thereby gaining workflow efficiencies. Time is of the essence.

6. Data fraud

Fraud finds its way into workers’ compensation in many ways, even into its data. The most common data fraud is found in billing—overbilling, misrepresenting diagnoses to justify procedures and duplicate billing are a few of the methods. Bill review companies endeavor to uncover these hoaxes.

Another, less obvious means of fraud is through confusion. A provider may use multiple tax IDs or NPIs (national provider numbers) to obscure the fact that a whole set of bills are coming from the same individual or group. The system will consider the multiple identities as different and not capture the culprit. Providers can achieve the same result by using different names and addresses on bills. Analysis of provider performance is made difficult or impossible when the provider cannot be accurately identified.

7. Data as a work-in-process tool

Data can be used as a work-in-process tool for decision support, workflow analysis, quality measurement and cost assessment, among other initiatives. Timely, actionable information can be applied to work flow and to services to optimize quality performance and cost control.

Accurate and efficient claims data management is critical to quality, outcome and cost management. When data accuracy and integrity is overlooked as an important management responsibility, it will hurt the organization.