Posts

KNOWING BIG DATA VALUE HELPS IMPROVE BUSINESS INTELLIGENCE

Insurance firms have a lot of content to deal with, both present and past. There’s things to consider like ancient archives, current backups and all the live information that comes pouring into the corporate infrastructure on a daily basis. Yet simply allowing these records to rotate through the data management lifecycle isn’t the best way to make use of them. For that, firms need business intelligence solutions.

In the business intelligence landscape, there are ways to harvest insights from past content and apply them to current situations. There are also methods for projecting future outcomes based on past events. Both of these circumstances require that general professional liability firms are making use of the best storage infrastructure and positive enterprise storage solutions.

Building business

As Insurance Tech Online stated, “understanding the value of these resources is a good first step toward ensuring that companies are making the most of their inherent and in-house resources. There are much better ways to run current operations than what most large organizations in the general professional liability scene are implementing at present.”

Specifically, the best business intelligence tools are able to help companies:

•Improve response time
•Reduce financial liabilities
•Boost retention rates

Such opportunities are appealing to insurers, but the ways to achieve these outcomes aren’t always intuitive. These results don’t come up with all the opportunities that businesses have to offer, thereby stunting the growth of organizations.

It’s important to be open to everything that companies can do with their industry options. Lack of effective use is a common problem among insurance providers, as these corporations are very fixated on final outcomes rather than long-term results.

These kinds of ideas can help increase the effectiveness of short-term productivity, but they’re not always useful in situations where firms want to be successful in the following years or decade. While business intelligence can help companies save money, this isn’t the only outcome that corporations can aim for with their corporate insight resources. It’s much better to think about why cost savings occur and how to better enhance these returns in the future.

Improving responsiveness

Producing a positive business intelligence plan requires organizations to think about these long-term outcomes, rather than just concerning themselves with what’s right around the corner. To do that, firms should consider the variety of services and solutions currently impacting their operations, as big data can have a strong impact on all of these solutions.

Information Management Online stated that “there are considerable concerns about how companies can manage their data in the age of the Internet of Things. People are able to link to corporate information services from anywhere and at any time, resulting in stronger flows of content in enterprise servers. While this is beneficial to creating business intelligence results, it can also easily overwhelm general professional liability service providers.”

Leveraging more content is easy when the volume of information available to a firm is always on the rise. In some instances, there’s a four-fold resource for enhancing the level of insight and availability of these services, as the source noted. Such insight depth makes it easy to pick out content necessary for improving responsiveness and business intelligence, thereby ensuring that there’s required content for short-term and long-term projections alike.

The more widespread these insights become, the easier it is for corporations to hone in on the information that is most specific to their needs. “Right now”, Information Management stated, “there’s a growing need for analytics, as the big data inundation has yet to cease. With all that content continuing to be born and transferred on a regular basis, it’s necessary to have tools in place that can handle this rolling information deluge in a way that’s easy to commute to business intelligence computing.”

BUSINESS ANALYTICS DRIVEN BY 3 TRENDS, 1 MAJOR CHALLENGE

Within the insurance industry, the constant evolution of processes is driving growth and a need for improved tools. Underwriting practices have been growing in popularity and some firms are seeing a rise in claims fraud, increasing the need for high-end claims management software. These cases present opportunities to evolve by investing in powerful business analytics solutions and discovering the hidden potential that lies within these processes.

According to Voice & Data, the need for business analytics is being driven by three specific use cases: data trends, technology trends and business trends. Understanding these three areas and how they are affecting an insurance provider’s operations will allow that company to optimize it’s tools and workflow to it’s own unique needs and drive the largest ROI when implementing a business intelligence platform.

The right tech

Utilizing the right technology for business processes in general is becoming a critical consideration for every business in any industry. This is no less true for professional liability insurance providers, and in order to optimize workflow, the right IT infrastructure and analytical architecture are needed. According to the news source, this means finding a solution that increases a firm’s processing power- it’s ability to harness and utilize data faster.

Predictive analytics solutions offer the optimized balance between speed and power that helps providers use more data sooner in order to detect and eliminate fraudulent claims and other risks. Through this method of analytics, firms can optimize the foundation for data usage across the board and their overall BI strategy to reflect the current industry climate more accurately.

Evolving business strategies

When considering new analytics solutions, firms also have to take into account the evolution of their overall business strategies. No company remains the same forever, and for insurance providers, the key to constantly improving service and growing is to ensure that those strategies focus on providing stronger, faster service. A high-end business intelligence solution that helps identify and eliminate fraud sooner in underwriting and claims assessing processes will help firms achieve this goal swiftly.

Use more data

The big data trend is becoming increasingly frustrating for companies that haven’t already adopted the analytics strategies necessary to manage the volume and velocity of information. Predictive analytics will allow firms to organize, sort and use structured, unstructured and real-time data equally well. Optimally, an insurer will be able to incorporate this use in every aspect of operations, but ensuring that it’s benefits affect underwriting and claims management is key.

The big data trend is perhaps the most essential for any insurer to consider when exploring predictive analytics opportunities. According to Claims Journal, the big data and analytics trends present the largest opportunities to gain a stronger position on claims fraud. By being able to examine and put data to use faster and more efficiently, providers are able to consolidate data points and gain real-time, accurate results rather than relying on “judgement-heavy” methodologies that require more time and effort.

Being able to catch fraudulent claims faster doesn’t just reduce the risk of loss for a firm- it optimizes overall customer service by ensuring that honest clients get more attention. Ultimately, this will provide increased returns, boosting ROI from analytics adoption.

These trends and the constant threat that claims fraud presents don’t just provide a firm reason to invest in predictive analytics-based business intelligence solutions. They provide a clear advantage that can be gained by being able to create more thorough reports, assess data faster and move on more efficiently in everyday operations for any provider.

PREDICTIVE ANALYTICS GROWING INTO MORE CLAIMS MANAGEMENT APPLICATIONS

Keeping up with enterprise demands in the claims management landscape requires a bit of clairvoyance these days. Predictive analytics is providing the bridge between these kinds of needs and present protocols, increasing market insights and business effectiveness.

However, it’s not as easy to make use of predictive analytics as some companies may think. It takes more than just a wealth of data points or a good grasp of industry standards. As technology continues to evolve, user demands change and enterprise apps grant greater insight into the lives and strategies of businesses and consumers alike, there’s more to learn about these sources than ever before.

Gaining a grasp

Knowing what to anticipate in future months in terms of policy management, claims filings and business needs can help companies in the professional liability landscape plan more effectively for these periods. By tapping into the depths of client, corporate and market information already available to a firm, it’s much easier to understand how these factors add into future events.

The trouble is, not all professional liability and insurance providers can grasp how this process works. As Modern Healthcare Online reported, even when companies have access to reams and depths of data points, it’s possible to come up empty handed in strategic planning reviews.

Predictive analytics is a shifty agent, the source noted. It requires that a firm is able to classify its data points, identify trends, limit the number of factors impacting business intelligence calculations, and create a narrow outcome, specific to the firm manufacturing the results.

In this way, strategic and predictive analysis can help a single medical professional liability firm determine the likely actions of its own patients, but it may not take all outside factors into account. Still, Modern Healthcare noted, the results are more reliable than what companies can expect otherwise from some of their medical clients. According to the source, only about 20 percent of voluntarily submitted customer information was actually accurate. By creating predictive analytics based on trends in consumer usage and public information, it’s much easier for organizations to effectively adjust rates and protect themselves from abuse.

“It’s enabling strategic resource allocation among the total population,” said clinical information specialist Rishi Sikka. “If you really want to move the entire population … you need to work on the entire population, not just the most expensive.”

Pushing ahead

Even with a shaky grasp on predictive analytics, it’s possible for general professional liability practices to anticipate general trends in their user bases and come up with likely scenarios for the coming months and years. As iHealthBeat reported, this technological capability to somewhat tell the future, based on empirical data, may be in its infancy, but it’s also evolving as the more claims management and policy administrators use it.

Scalability and complexity of business infrastructure remain two of the biggest obstacles, a recent report showed. However, as iHealthBeat added, there are also problems like redundancy and compliance issues to deal with.

Still, firms are making major inroads into proper predictive analytics and business intelligence by pioneering programs that evaluate risk, integrate real-time application feedback, and come up with smarter sources for data acquisition and oversight. Electronic health records requirements are assisting professional liability organizations in gaining greater access to pertinent medical information and filing trends, thereby furthering their research and enhancing their understanding of overall market factors.

Such enhancements will hopefully help insurance agencies protect themselves- while better serving their clients. When firms are able to understand what’s likely to come next in the care of a customer, it’s easier to offer targeted referrals and superior coverage to consumers while also protecting corporate liability.

GREATER INSIGHT WITH BUSINESS INTELLIGENCE IMPROVES POLICY CONTROL

As the complexity of modern enterprise tools continues to grow, organizations should exploit the vast pools of information such resources amass. The presence of business intelligence solutions in the insurance and professional liability spheres shows how useful it can be to combine technology with ingenuity to form a better understanding of market factors.

Companies need to ensure first, that they’re using the best resources for their particular industries. They also must be certain that data storage, infrastructure management and user devices are all in line with the practices and principles necessary to properly perform analytic reviews. With these elements in mind, acquiring and updating IT assets to fit a more intelligent enterprise design can be easy.

Futuristic information

The availability of smarter and more intuitive business systems is helping companies increase the effectiveness with which they handle claims and communicate with consumers. At the same time, things on the back end of operations are also getting a major upgrade, through computer systems that can think for themselves and can perform more complex, accurate and valuable analytic and business intelligence protocols.

While not every company can afford a supercomputer as of yet, IBM’s Watson is showing off what can be done for organizations that can. On a smaller scale, other organizations can harness similar powers through cloud computing and integrated business solutions, gaining access to intelligent analytics on a somewhat less powerful scale.

But in this case, Technology Review reported, the American Society of Clinical Oncology is getting the real deal- a full supercomputing device named Watson, IBM’s flagship intelligent device. The organization will use the IT innovation to increase understanding of certain cancers and hopefully propel research by leaps and bounds with the help of an always-on, super-smart technology assistant.

Applying the case

IBM is also hopeful that this kind of computing power can be spread more ubiquitously and affordably to other medical providers and companies in need of such expertise. Different versions of Watson have already been issued and implemented in other businesses, with the idea being; a more targeted deployment could provide superior assistance in the environments in which it is executed.

For insurance and claims management, that would entail a smart device that provides business intelligence regarding consumer demands, filing trends and policy expectations. Such ideas are already present in the general professional liability landscape, but with a supercomputing boost, it may be more manageable for organizations of all kinds to increase their policy proficiencies with these kinds of IT assistants.

Technology trends

There are already a few instances where insurance organizations and coverage providers are making use of similar tools. According to Insurance & Technology Online, the ability to mine and refine data has created a fervor of activity online, where business intelligence and corporate analytics software are helping companies find the underlying value in the wealth of files they already own.

Innovative and dynamic data management is helping insurers understand financial markets, lending trends and expected monetary tactics. Other deployments focus on tracking user endpoint interests, expediting market penetration and promoting business intelligence throughout all operations. Risk management and infrastructure control are also prominent features in this environment, as having the right tools for the predicted tasks at hand can have a huge impact in how well organizations meet these challenges.

As business intelligence continues to improve, insurance organizations and claims management techniques are also growing in complexity and responsiveness. The end result is a more intuitive and proactive professional liability landscape that requires growing technology assets in order to analyze information and adequately meet consumer needs with greater accuracy and agility.

 

DEMANDS OF ANALYTICS CHANGING BUSINESS INTELLIGENCE LANDSCAPE

Advanced business analytics solutions are helping companies in every sector optimize their workflow and ability to drive value from big data. However, as these tools are adopted they are influencing business intelligence architecture, changing the demand placed on systems and data storage, as well as the personnel in charge of these resources. According to TechTarget, these trends are changing the face of business intelligence across the board and influencing new deployments as well as an evolving mindset in analytics operations.

Data warehouses: a center of operations

In the traditional office environment, the water-cooler, or coffee maker, is often the “center” of workflow. Breaks, gossip and collaborative work takes place around it as employees meet on on their breaks. For predictive analytics software, the water-cooler is the data warehouse. All aspects of a business intelligence platform center on where data is stored and managed, making it critical to support the data warehouse as other investments increase. Whenever a firm adopts new analytics solutions, it should ensure that its storage solutions can keep up with the demand being put on them.

Data management determines efficiency

While one major benefit of an advanced analytics solution is the ability to handle raw data more effectively, improving data management resources to “refine” that information can still be advantageous. Speeding up analytics and helping staff assess their data sets more efficiently will drive workflow and expedite business intelligence processes to keep these processes running smoothly even as data volumes increase and analytics grow in power.

The future of insight

With predictive analytics leading the way forward with data insights and value, insurers can already begin to see where the future of business intelligence is headed. Predicting trends isn’t the same as the future, however, and as new tools continue to be developed firms have to be prepared for anything. Investing in high-quality analytics means setting the foundation for that growth and ensuring that operations are prepared for the inevitable exploration and experimentation that comes along with new BI solutions.

Ultimately, analytics has already significantly changed the course of the future of business intelligence. As firms continue to evolve, their needs will expand, and having the right infrastructure in place to cope will be critical, not just for maintaining speed, but preparing for the next step in the evolution of insurance analytics.

OPTIMIZING UNDERWRITING WITH ADVANCED ANALYTICS

Predictive analytics provide numerous advantages, but for insurance providers looking to quickly and efficiently leverage data for growth, it is important to lay out specific benefits that can be harnessed for the fastest returns. From improving workflow to enabling stronger data management, these tools meet the needs of the modern insurer. This is caused primarily by enhancing underwriting processes- critical for forward momentum in professional liability and other sectors.

The key to enhancing underwriting is helping professionals increase their attention to fine details through enhanced metrics and insights from business analytics solutions. The main advantage that predictive analytics provides is swiftly identifying potential problems and errors within data sets, allowing firms to enact loss prevention and risk management efforts sooner, resolving the issues before they fully form. This is achieved by taking big data, feeding it through the business intelligence platform, selecting key processes and determining the most likely path they will take in the future. When integrated with underwriting, this will continuously deliver actionable insights in the background that can be used to expedite claims management software in the face of fraud and other risks.

In order to truly leverage predictive analytics within underwriting and general insurer operations, firms need to focus on several specific benefits that can be derived from advanced analytics:

Fraud detection

At the core of predictive analytics in underwriting is swifter fraud detection. By catching key data points that can indicate fraudulent claims and exploring those sets in depth, companies are able to optimize workflow around being more efficient with these practices. This, in turn, will help streamline claims management software, leading to swifter claims resolution.

Claims resolution

Following from enhanced fraud detection, insurers that optimize their business intelligence solution will be able to address and resolve claims faster, enhancing client service and improving overall workflow. This will help them react and resolve problems more effectively while still offering top-quality service to legitimate clients.

Process optimization

General underwriting processes benefit from both of these previous enhancements, ensuring that overall workflow is improved through general employee efficiency. By increasing fraud detection and claims resolution, firms will be able to simultaneously resolve issues while opening new claims and streamline operations around the needs of the individual underwriter to optimize personal workflow.

Enhanced reports

The clarity and insight found in data reports will be directly improved by updating business analytics solutions, helping firms deliver higher-quality analytics across the board. Underwriting, as well as policy management and other areas of operation will benefit from this change, while optimizing data management and how a firm handles big data.

As advanced analytics and underwriting becomes more integrated into overall operations, insurers need to ensure that they are investing in the top solutions for their needs. The right analytics platform will deliver quality insights and faster results, allowing the provider to turn around and optimize its own processes around improved data usage and underwriting. Ultimately, this will deliver the ROI firms expect from any technology investment.

 

TECHNOLOGY, REGULATIONS AT ODDS, CHANGING HOW INSURERS HAVE TO LOOK AT DATA

Both industry regulations and technology are evolving rapidly for insurers, and keeping up means looking in two directions at once. For many providers, the biggest change will come in the form of how they approach data and optimize their business intelligence solution for compliance in the coming IT storm.

The need for data overshadowed by compliance

Insurance underwriting and claims management rely on data for success. The more data an insurer can throw at these processes, the better they can perform given the right tools and enough time. However, increasing expectations for swift value from clients, and new regulations, are forcing insurance providers to reconsider their approach to data management and these core processes from an IT standpoint.

According to Insurance & Technology, IT itself can create a bottleneck in insurer operations if they aren’t careful. First, IT teams have to realize that they need to prioritize the needs of their colleagues, as every team that comes to them will be a “top-priority” issue. Second, business requirements are going to continue to evolve, making repeat changes, at times, necessary in order to continue maintaining compliance. Keeping these two issues in mind will help ensure proper adoption of new tools and integration with workflow in a way that delivers the results needed for progress.

Of course, the evolving regulations regarding data usage, IT compliance and business analytics solutions will continue to make these efforts difficult. And, the more technology that firms use, the more the regulations are going to change. This catch-22 can result in confusion and reduced productivity because the systems that firms are using get overloaded.

Insurance & Technology recently reported that a study by EY, foundthat 88 percent of insurers use technology for even the most basic functions, including tracking new regulations.

“(However, what’s missing is an) advanced, integrated technology solution designed to meet specific needs, although some of the CCOs are in the process of building such a solution,” noted Thomas Ward, EY Partner. “There’s more and more reporting that is coming up through the CCO. We think the use of technology will evolve with it and improve the overall integration with the risk practices and the audit practices.”

Using technology to leverage regulations

In order to maintain compliance, continue evolving along with underwriting and claims management needs, and not overwhelm IT and general operations, insurers need to examine the tools they are using. Advanced analytics solutions, such as predictive analytics, can deliver swift and reliable insights more effectively while staying within compliance standards for data usage. Furthermore, the right tools will advance the value of underwriting, an area that most insurers need to focus on. To break the “bottleneck” in IT- and ensure forward momentum, firms have to focus on investing in technology that doesn’t just support current operation needs, but future ones as well- while leveraging the opportunities presented by these solutions to maintain a high standard of quality at all times.

PREDICTIVE ANALYTICS FOR PERSONALIZATION IN POLICY MANAGEMENT

For insurance providers, one of the biggest operational challenges is connecting with clients and improving the customer experience. The emergence of predictive analytics helps providers optimize their use of big data to give their workflow a more personal touch, targeting clients’ individual needs more effectively and offering them the policies and claims management services needed to get the most out of their insurance.

According to Econsultancy, the effects of personalization are much broader than optimized policy management. Even simple things like getting a client’s gender wrong on paperwork can affect his or her experience and reduce overall satisfaction with service- something the provider wants to avoid at all costs.

“Send duplicate catalogs to a customer, get their gender wrong, or try to sell them lawn mowers when they live in an apartment, and you’ll soon compromise your marketing ROI,” Dominique Levin, an industry expert, told the news source.

The trick is to utilize all of the available information regarding a claim or policy and use it properly to maximize service quality during every interaction with that client. As data grows more sophisticated, firms will need to use a high-end business intelligence platform to continue improving and delivering the insights necessary to meet customer expectations.

Within the sphere of insurance analytics, the need doesn’t lie in customer service, however, it affects every area of operations. Underwriting, claims management software, even basic information management, can all be improved by deploying predictive analytics to streamline data usage and enhance the ability of employees to assess and report on trends. This will allow them to shift through data faster and ensure they are meeting customer needs on a personal level, while promoting overall growth throughout operations.

According to the Huffington Post, predictive analytics helps bring a personal touch to business intelligence because it helps produce more timely, actionable reports on information, ensuring that trends are acted on when they are still relevant, rather than missing an opportunity- or worse, a risk. This change is particularly advantageous in the health care professional liability field, where claims fraud and other risks continue to grow.

Beyond the general improvement that taking data usage personal with predictive analytics provides, the medical industry is advancing by leaps and bounds because of advanced business analytics solutions. These tools provide a framework, according to the news source, which aligns the evolving needs of healthcare staff with the capabilities of the insurance provider, minimizing risks and eliminating fraudulent claims in order to enhance the quality of service that firms are able to offer legitimate clients. This shifts the focus of insurer operations from risk management to risk prevention, allowing for more time spent on the claims and policies that need it.

Of course, providers will need to consider the data they are using as well. A high-quality predictive analytics strategy is nothing without the data to fuel it, and firms will need to ensure they are optimizing their data gathering and management solutions as well. This will ensure a more well-rounded approach to analytics practices and data-related operations as a whole.

The best thing an insurance provider can do to enhance its opportunities for growth, and minimize the risks that big data presents, is to invest in a business intelligence solution now and streamline its operations around providing higher-quality service to its clients moving forward. Such a change will support future demands and reduce the chances for loss as the insurance industry continues to evolve.

DON’T BE CONFUSED BY BIG DATA

The big data movement has caused quite a bit of confusion in its wake, but insurance providers need to overcome the misinformation and chaos by leveraging advanced business analytics solutions and focusing on the potential that new data can bring. While the big data trend has stunted business intelligence solution adoption in the past, it’s time for firms to start adopting in the tools that will deliver them from big data confusion.

According to Channelnomics, the business intelligence market is growing slow, but the potential for much bigger gains is there, waiting to be unleashed. Gartner’s study of the market found that the BI and analytics market grew by 8 percent in 2013, reaching $14.4 billion. However, the growth could be much stronger.

“Overall, just like (2012), the market is shifting gears, which is keeping growth in the single digits,” said Dan Sommer, the research director on the Gartner report. “Confusion still reigns around how to best leverage analytics on Big Data. Much Big Data investment happened outside traditional BI in experimental silos, infrastructure and services. No region in the world grew faster than 12 percent, which breaks the strategic assumption that many of the large vendors have held for years- that emerging markets are growing at a much faster rate.”

In order to start achieving bigger gains and avoiding the chaos that big data can bring, insurance providers can deploy more adaptive, flexible analytics strategies, which will allow them to harness larger data pools more effectively and streamline their insight processes. From underwriting to claims management software, predictive analytics solutions may provide the leverage that insurers need to turn this trend around.

“Paradoxically, we’re at the cusp of a series of tipping points which will facilitate unprecedented interest and adoption of analytics,” Sommer also noted. “As the market shifts gear, we saw a series of tipping points in 2014 that will accelerate adoption. These tipping points are that half of BI and analytics spending will be business driven, half of new license spending will be driven by data discovery requirements, and half of organizations will consider deploying BI in the cloud, at least tactically.”

By furthering business intelligence efforts, insurers will be able to better leverage big data and promote stronger underwriting processes- an area of operations proven to deliver results to firms that properly utilize it. With many companies reporting struggles with underwriting despite potential gains, optimizing these operations through predictive analytics software can be invaluable.

The right technology often helps businesses promote stronger data-related practices, and an advanced business intelligence platform is at the pinnacle of this potential. Rather than struggling, insurers need to invest in the right tools for the task at hand, be it improving policy management or advancing underwriting to enhance fraud detection efforts. Ultimately, these efforts will all help to achieve greater results across operations in order to improve a firm’s technological stance in the modern era.

LIABILITY FOR CYBER THREATS RISING

With considerable changes coming in technology, especially data and cloud-related solutions for businesses, cyber professional liability insurance is a must for enterprises. However, few understand the need or value of these solutions, with a mere 5 percent of companies reporting they have coverage, according to Insurance Business America.

In fact, 39 percent of businesses believe cyber threats are covered under their commercial general liability policies, but this is a misconception caused by some specific overlaps between the two types of coverage. Too many firms think that their CGL coverage will protect them from liability from cyber attacks.

“This is certainly not the case, as a CGL policy has many gaps as it relates to cyber risk and was not written to cover cyber events,” Christine Marciano, president of Cyber Data-Risk Managers in New York, told the news source. “Several breaches within recent years have been battled out in court with insurers versus CGL policyholders.”

As many industries continue to be heavily affected by evolving technologies, particularly the cloud, the need to optimize their liability coverage increases. As such, insurers should consider improving their own strategies to increase awareness of the need for high-end coverage.

Beyond cyber liability coverage, general professional liability insurance will become critical moving forward, especially in healthcare-related fields. Medical centers will be utilizing data and expanding technology just as much as the next firm, and proper protection from cyber risks will be crucial for care providers.

The evolution of data storage and use will impact insurers just as much as it does the businesses they offer service to. By investing a high-quality business intelligence platform, firms will be able to leverage new solutions and increasing volumes of data more effectively for whatever purpose they need, whether it’s to increase claims management efficiency or broadening their client base through improved service awareness. The end result is the same in either instance- stronger data use through predictive analytics and other advanced tools.

Furthermore, the threats to operational integrity, for firms increasing their reliance on data and related technologies, are only going to continue. Nicolas Christin, a researcher with Carnegie Mellon, told the news source that, following the breach of security at Target, two dozen other attacks have been reported, but on a smaller scale.

“You’re going to see more and more people trying this,” Christin told The Washington Post “If you just saw your neighbor win the lottery, even if you weren’t interested in the lottery before, you may go out and buy a ticket.”

Ultimately, the deployment of higher-quality business analytics solutions will help insurers anticipate the types of risks presented by these scenarios, and optimize their coverage around them, while better protecting themselves from the inherent challenges of professional liability coverage. To this end, their clients will benefit from the improved service and the cost of coverage will even out, even as the threats remain at large.