The processing and payment of insurance claims is the moment of truth between property and casualty insurers and their customers. The speed, ease, and accuracy of these key interactions set the tone for the customer relationship - and has proven to be the key to brand building, customer retention, and referrals in this increasingly competitive market characterized by intense competition, pricing pressure, customer churn, and increasing incidents of fraud.

The claims adjuster sits at the center of the adjustment process, charged with the singular task of marrying the art and science of claims adjusting and loss control. But with fewer professionals seeking to take on these jobs, property and casualty insurers are having difficulty filling these critical roles. According to the U.S. Bureau of Labor Statistics, employment of claims adjusters, appraisers, examiners and investigators is projected to grow at 3% percent through 2022, slower than average for all professions1. At the same time, rising medical costs and increasing product complexity are compounding the challenge of processing and paying claims efficiently and effectively.

Today, new technologies can reduce much of the administrative burden that has encumbered the claims adjuster. These tools can streamline processes and increase capacity. For tasks that can’t be automated, carriers can take advantage of global talent to tackle both routine and complex tasks. They can source routine data entry in lower-cost locations and access an abundance of more skilled workers to perform higher-end tasks such as utilization management.

In addition, a wealth of data is captured when a property and casualty loss is reported, and by applying advanced analytics to that data, insurers can arm their adjusters with proven insights rather than gut feelings to predict optimal claims outcomes consistently. While the talent required to produce such data-driven predictions may be in short supply in the U.S., there are large populations of analytics professionals in countries such as India.

Thanks to these automation options, global processing capabilities, and analytical systems and talent, insurers can improve the quality of claims service, improve claims accuracy, reduce claims leakage and incidents of fraud, and improve investment returns. These new tools and partners can change the game for property and casualty insurers. But to take advantage of these advances, insurers must invest in five areas:

  1. New digitization and automation tools
  2. A global partner ecosystem
  3. An enterprise-wide analytics strategy and utility for advanced analytics and insight generation
  4. A robust data-capture system capable of incorporating external sources of data that will increase exponentially as a result of digitization and Internet of Things technology
  5. A clear execution strategy for transforming the claims administration process.

An outmoded manual, instinct-driven process

Property and casualty insurers are facing fierce competition, pricing pressures, reduced returns, customer churn, increasing fraud, and an aging claims adjustor workforce. In this already fragile industry, in which one natural disaster or catastrophe can wipe out a company’s bottom line, the status quo will no longer do. Industry watchers agree that insurers must innovate to succeed.

Competition has been increasing due to the entry of alternative capital providers, especially those pouring cash into the reinsurance business. Pricing pressures will make organic growth more difficult in coming years. This will make efficiency improvements a competitive advantage. Indeed, driving operational efficiency and flexibility, risk management, and reducing expense ratios and total cost-to-serve are among the top challenges facing insurers today, according to technology analyst firm HfS Research.

Fraudulent claims – estimated at 10% of all property and casualty insurance claims -- lead to industry-wide losses of $32 billion a year, according to the Insurance Information Institute. One survey found that 32% of insurers said the portion of falsified claims is as high as 20%.2 And the problem has been increasing. Questionable insurance claims rose by 16% from 2011 to 2012 alone, according to the National Insurance Crime Bureau (NICB).

Experienced adjusters — who could, perhaps, recognize such fallacious claims intuitively — are nearing retirement while younger employees struggle to close claims in a timely manner4. Meanwhile, the adjuster workforce remains mired in mundane tasks, from data entry and correspondence to records management and basic research that eat away at the time they could be spending applying their skills to the high-value work of adjudication, negotiation, fraud identification, and collaboration.

Claims payments and related loss adjustment expenses constitute the single largest expense for property and casualty insurers. The net-loss ratio (total losses paid in the form of claims) for property and casualty insurers worsened by almost 2% to 69% in 2014, according to the National Association of Insurance Commissioners5, further squeezing margins. Yet many insurers rely on manual processes, inflexible business rules, and — worst of all — intuitive decision making throughout the claims management lifecycle.

Digitization and automation can reduce the administrative burden on the claims adjuster and increase capacity. Just as importantly, there is abundant unstructured and structured data generated throughout the claims lifecycle that could be analyzed to create more effective, reliable, and less costly claims management processes.

However, the accessibility and quality of the data, much of it residing in aging legacy systems, has made its use extremely difficult. Until recently, the technology to store and process that data was neither readily available to many insurers nor cost effective to retrieve. In addition, recruiting professionals who understand both insurance industry processes and advanced analytics has been difficult. And few property and casualty insurers have developed a clear strategy for implementing automation and analytics for claims management.

Thanks to technology advances, insurers today can reassess their standard operating systems and processes in order to make fundamental changes in the claims adjustment process.

New options for increasing claims adjustor capacity

Today, carriers can decouple the non- core tasks of the claims adjuster from his core work and embed digitization and automation into the claims process.

In addition, more robust inter-business networks and communication tools now make global process partnerships an attractive option for carriers that need to increase claims management capacity at a lower cost.

Freed from having to deal with information gathering, scheduling, bill handling, collections, medical reviews, audits, reporting, and correspondence, adjusters can focus on adjudication.

By working with global service providers, insurers can also access the kind of professionals in short supply in their local markets, from certified medical professionals to top analytics talent. Unlike old-school outsourcing largely built upon labor arbitrage, these more advanced service options enable insurers to plug gaps in capacity in a way that makes it feel like the work is being done locally.

Technology platforms capable of handling the end-to-end claims process have been around for some time, but due to their expense, complexity, and implementation challenges, such systems have typically only been viable options for very large insurance carriers. However, small- to mid- size companies face the same issues as their larger counterparts.

Fortunately, there are new options for those companies that had previously been priced out of claims administrative platform implementations. They can take advantage of self-contained niche applications that can digitize very specific areas of claims management such as medical documentation, subrogation, and the first notice of loss. Insurers can take advantage of these more self-contained technology options practically right out of the box.

By partnering with an insurance process service provider, they can hand off each of these business processes in their entirety, ridding themselves of that complexity and putting their businesses on an equal footing with their much larger rivals. Thanks to outcomes-based pricing, they can create these partnerships with confidence.

Analytics come of age

From the moment a customer notifies an insurance company of a loss, there is valuable data created that insurers can use to build models to predict the severity of the claim. There are claim characteristics, insured characteristics, call transcripts, pictures, and environmental factors that can feed these models. Property and casualty insurers can use advanced systems to analyze that data when the claim comes in and also leverage complex event processing systems to parse the additional information that comes in throughout the adjudication process, in real-time, to infer and predict events and patterns. Such in-the-moment data analysis can enable carriers to take the right action at the right time to improve outcomes.

Imagine a physical therapist and chiropractor are added as new medical providers on an existing personal injury claim. That could be flagged automatically as such a combination has been shown to increase the likelihood of overtreatment, also known as soft fraud. The introduction of such new information in conjunction with certain other circumstances could also trigger an immediate independent medical examination that might prevent mounting and unnecessary medical bills. A robust analytics model may monitor up to 30 variables that will automatically trigger a reevaluation of a claim’s fraud potential if any of those factors changes over time. These models enable insurers to address potential loss-making claims issues proactively.

Insurers can also use a variety of structured and unstructured data to predict the frequency of certain types of claims (general liability, workers compensation, and bodily injury, for example), how long the claim will take to pay out, the risk of subrogation or litigation, and the chance that a claim will close without payment.

Applying advanced analytics throughout the claims management lifecycle has a direct impact on the bottom line. By predicting the frequency and severity of certain types of claims, and the likelihood that a claim will close without payment, insurers can better manage their cash reserves, improve investment outcomes, and more rationally align the resources dedicated to a claim with its value to the company. By having more accurate forecasting of the risks of subrogation, litigation, and fraud, insurers can identify those at-risk claims earlier and manage them more effectively. Finally, carriers can feed this claims intelligence back to the underwriting team in order to improve their actuarial models. In fact, insurers who leverage analytics technologies to make sense of the growing amount of internal and market data available ultimately will gain competitive advantage, according to a report released by PriceWaterhouseCoopers.

Divining better outcomes with data

By using advanced analytics throughout a claims lifecycle, property and casualty insurers can introduce a number of new processes to optimize claims adjudication from the first notice of loss all the way through payout.

A top five U.S.-based property and casualty carrier built a predictive model to better understand the key drivers of claims severity. It then used this intelligence to inform a new operational process for automatically routing a new claim to the best adjuster according to the specifics of the case. Along with routing the claim, the system also delivered a set of next-best actions for the claims adjuster to optimize loss ratios, adjustment expenses, and customer satisfaction. By getting the right claims to the right handler at the right time, this carrier also improved claims handler retention.

Another leading insurance carrier was able to predict which claimants would be most likely to sue. Litigation costs constitute to be the greatest expense associated with general liability claims. Early indicators of potential legal action can help insurers better manage and reduce the associated costs. By flagging claims likely to wind up in court early in the adjudication process, the company was more likely either to prevent the legal action or settle more quickly, as well as more accurately reserve the cash required for legal expenses. The analysis also helped the insurer better understand the factors that result in legal action on a claim.

Similarly, another U.S.-based property and casualty insurer (which had one-third of its claims in litigation at any given point in time) wanted to rationalize its massive investment in attorney time. Using data related to claims characteristics, legal expense drivers, and attorney skills, the company built a model that could predict and litigation duration to most effectively manage litigation costs. Using key data about claim characteristics, legal-expense drivers and attorney skills and expertise, the model predicted the best option for reining in legal costs without compromising (and, in some cases, actually improving) outcomes. And this more effective allocation of counsel led to faster and less-expensive claim resolutions. Ultimately, the carrier realized annual savings more than $100 million in legal expenses.

The cost of auto personal injury protection coverage in no-fault U.S. states has been skyrocketing due to increased medical costs, excessive treatment, fraud, and significant litigation. One U.S.-based auto insurance company analyzed medical billing, claims, legal and policy information to improve the handling of these claims and identify suspicious cases early in the process. The insurer was able to predict how such claims would progress over their lifetimes, thereby helping claims adjusters flag and handle suspicious cases. The company was also able to provide underwriting and product teams with intelligence about how specific attributes affected the total costs of these claims in order to better align pricing with risk. By analyzing unstructured data in adjuster notes, the carrier identified several factors (number of household relatives, age, gender, pre-existing medical conditions and occupation) that could affect risk. Now the insurer is considering collecting that information in a structured, digital format to determine future product pricing.

In many cases, the insight of medical professionals may be helpful during claims adjustment. Exactly how beneficial it was used to be anyone’s guess. One leading property and casualty insurer wanted to measure the impact of assigning a nurse to its potentially severe no-fault, first- party auto claims. The company created a model to predict the impact of nurse involvement on medical payouts, arbitration and litigation, and more accurate cash reserving. They discovered that in cases with certain attributes nurse involvement led those involved in the claim to return to work sooner, thus lowering payouts. Another U.S.-based property and casualty carrier developed an early warning system to predict claimants in no-fault states like New York and New Jersey likely to use costly ambulatory surgical centers for treatment. By assigning a nurse and case manager to those claims, the company was able to save $2 million a year on medical coverage.

General liability insurance claims usually turn out in one of two ways—a huge payout or no payout at all. One insurer saw the majority of its general liability claims close without payment. However, the resolution of those claims took several years during which the carrier was forced to set aside large reserves, negatively affecting working capital. To better manage the costs associated with these no-pay claims and better manage its cash reserves, the insurer built a model that would predict whether a claim was likely to close without pay. Today, the company is able to assign the appropriate level of claims handling to these no-pay cases and free up cash previously reserved for their payout.

While there are instances of hard fraud (purely fabricated loss claims) in the property and casualty industry, the majority cases involve soft fraud. A claimant may exaggerate the details of an accident or file for additional injuries not experienced. Medical providers can pad their bills. Even adjusters can pad or invent claims.

Because fraud is dynamic, past fraud patterns are often ineffective in predicting future fraud. Insurers today are using machine-learning techniques capable of recognizing non-linear patterns in the most recent unstructured claims notes to predict fraud. Carriers can also take advantage of new sources of digital data they never had access to before, such as claimants’ social media activity. If, for instance, the insured has filed a workers’ compensation claim but is also posting photos of his latest ski trip on Facebook, that behavioral data can help inform the claims management process.

By identifying potential fraud more quickly, the insurer can route the suspect claim to an investigator before expenses pile up or the claim is paid. For example, the early prescription of opiates, along with overlapping treatments by chiropractors, physical therapists and massage therapists, when combined with other claim attributes, may trigger a fraud referral. One leading U.S.-based property and casualty insurer used advanced analytics to identify potentially fraudulent auto and workers’ compensation cases earlier in the claims administration process. By flagging an additional 15% to 18% of questionable claims sooner —allowing for more targeted mitigation efforts — the company was able to save $12 million to $14 million a year.

Leading carriers are creating fraud- detection systems that continue to re-evaluate fraud potential every time data is added or changed on the claim. Such ongoing reassessment outside of a regularly scheduled fraud rescoring process enables adjusters to view, prioritize and address claims to drive the best outcomes.

Digitization, analytics, globalization: the new competitive differentiators

In today’s property and casualty insurance environment, the integration of automation and analytics into the claims adjudication process is no longer a luxury; it is a necessity. It will be one of the key drivers of sustainability in a highly competitive marketplace. But by forging partnership with global service providers who not only provide these new systems but the scarce talent to make the most of them, carriers can rework their outdated claims management processes.

The carriers on the cutting edge of such technology innovation will reap meaningful bottom- and top-line benefits. They will not simply cut costs but will improve the customer experience.

In order to take full advantage of these technological tools and analytics capabilities, insurers must:

  • Create digitization, analytical, and globalization awareness at both the leadership levels and the front line, from headquarters to the field, by providing education
  • Focus on the quality and the scalability of potential solutions and service providers
  • Increase data digitization and integrate automation tools into operations
  • Invest in data management talent
  • Invest in leading-edge analytics technologies capable of accessing and using a variety structured and unstructured data
  • Develop strategic partnerships with insurance process providers to access both new tools and talent
  • Create a new culture devoted to data- driven rather than instinct-based decision making
  • Refine and enhance both methods and strategy in an ever-changing technology environment.

And do so with all prudent dispatch. Your industry will not wait for you.


  1. financial/claims-adjusters-appraisers- examiners-and-investigators.htm
  5. report.pdf

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