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Auto Claims: Future May Belong to Bots

Despite a decade of prominence, the Age of the App may be over. The future of auto claims could belong to the chatbots.

Equipped with AI and machine learning capabilities, these computer software programs can conduct natural language-like conversations with customers in real time. Already, Amazon’s Alexa and Apple’s Siri are working as personal assistants and shoppers, while others serve as bankers, officer managers, HR administrators, concierges and more.

And it won’t be long before chatbots quickly expand throughout the insurance sector. They are already starting.

Compared With Chatbots, Apps Are a Nuisance

Because the insurance industry is traditionally slow to adopt new technology, apps are still considered “cutting-edge” by many insurance carriers. Compared with chatbots, though, mobile self-service apps may shortly be seen as the customer-service equivalent of a horse and buggy. According to Gartner, 20% of all brands will abandon their mobile apps by 2019. By contrast, Gartner forecasts that, by 2020, AI bots will power 85% of all customer service interactions.

What’s behind this warp-speed transition from apps to bots?

Speed, convenience and user-friendliness.

See also: Much Higher Bar for Customer Service  

While mobile self-service apps do represent a great leap forward for some policyholders, even those who love them were never thrilled about the time and patience required to download and install them and learn to use them. And many people have grown weary of their cell phone real estate being occupied by one-time apps. For every 10 apps downloaded by consumers, seven are uninstalled after just two weeks without ever being used.

Interacting with a chatbot involves no user’s manual. Customers can message (24/7) to converse with an intelligent chatbot that, for all practical purposes, behaves like a human – one fully equipped to handle all their auto insurance concerns.

In fact, chatbot-powered customer service could be even better than the “traditional” variety for mundane questions. For example, customers will no longer have to endure a menu of phone prompts before they’re connected with the appropriate person. Instead, the bot will be able to answer most questions or guide them through the steps needed to achieve the desired outcome in the format we’ve become accustomed to, text messaging.

Improving the Customer Experience

Imagine a self-service claim in which the vehicle owner interacts with a chatbot. The customer starts by verifying his identity and is then orally or text-guided through a series of steps to complete the entire process.

The chatbot asks questions. The customer answers. The customer submits photos or videos of the damaged vehicle, and the chatbot either responds with additional questions or walks the policyholder through the next steps. Once the process is finished, the bot transmits the details of the transaction to the carrier, which determines the right outcome for the claim – e.g., whether an estimate needs to be written by a human, through an AI photo estimating solution or through having the owner bring the car to a repair facility.

At some point, policyholders will even receive auto claim payments through the chatbot, further streamlining the claims process. This is already happening in some areas of insurance.

And because chatbots can learn and acquire more knowledge with every transaction, they will make the customer experience better as they continually collect and process vast amounts of data.

For customers, dealing with a chatbot for assessing vehicle damage will be like having an appraisal assistant standing right next to them. Of course, many people will realize that they are not, in fact, talking with another person, but communications will be so seamless and natural that they may eventually forget this.

For insurers, chatbots will lower costs by allowing companies to replace many customer service personnel. For example, customers have a tendency to call their insurers multiple times to inquire about their claims and ask basic questions. Such interactions could be easily automated using a chatbot.

See also: Hate Buying? Chatbots Can Help  

Incorporating Chatbots into the Claims Department

While chatbots have many applications, by no means is technology the right solution in every customer service interaction. There are many times when the human factor is far superior. Chatbots are one more tool in the toolbox. Here are two smart uses for them in a claims department:

1. Guiding customers, step-by-step, through the claims process using structured questions and answers. For example, if you want a vehicle owner to complete a mobile self-service claim, you could employ a chatbot to guide them through the verification process, as well as the submission of photos/videos and other documentation of the damage. Once this is done, the bot might transmit the claim to your company and an auto repair facility. An added benefit is that you will be collecting lots of data to help process not just this one claim but to enhance the customer service experience on all future claims.

2. Answering an array of FAQs submitted by policyholders – FAQs for which carriers currently deploy vast CS resources. Creating a human-like experience for managing thousands of customer inquiries could dramatically lower your customer service costs.

Ironically, the biggest benefit of chatbots is enhancing the customer experience by providing services that are faster and more personalized – a machine-made level of personalization.

So while apps still have a place in the insurance industry – for now – it’s likely that some of them will be out of a job, thanks to the rise of the chatbot.

The 2 Types of Claims Managers

In an industry buffeted by escalating vehicle complexity, accident severity and repair costs, companies wishing to improve customer satisfaction and their bottom lines must increasingly rely on modern technology to achieve more with less — to be more efficient with a smaller workforce.

Unfortunately, not all claims supervisors and managers recognize this fact. Even those who do sometimes prefer the “path of least resistance” to a journey outside their comfort zones.

Two types of claims managers

Today’s claims managers tend to fall into one of two categories: Innovative Visionary or Status Quo Preserver.

1. Innovative visionaries are forward-thinkers who see the big picture. They focus on process improvement, cost-efficiencies and customer satisfaction. They incorporate and leverage new technologies to optimize workflow processes and drive higher performance. They understand that results are the ultimate benchmark of success. At the same time, they understand that enhancing their companies’ image to acquire and retain good customers is vital to future earnings.

2. By contrast, status quo preservers are driven by the mindset of “this is the way we’ve always done things, so why change?” Though they may not be conscious of it, they encourage fragmentation and inefficiency to promote job security. The more problems they create, the more they position themselves as solution-providers.

See also: Power of ‘Claims Advocacy’  

These managers are fearful of making decisions — even easy decisions — that could improve the company’s performance and processes because they worry they’ll be made obsolete. They also cling to established vendor relationships, even when the companies do a poor job. Whether it’s that safe, “fuzzy” feeling managers get from dealing with “devils they know” or because of the pride they take in “empire building,” such managers always choose what’s best for themselves instead of what’s best for the company and the customers.

Careers are at stake

An orientation toward process improvement is vital for the future. If you’re a “status quo preserver,” you’re not just putting your company’s future in jeopardy, you’re also putting your job and your career in jeopardy — maybe not tomorrow but three or four years from now.

New and Improved

While it’s true that the words “new” and “improved” don’t always go together, much of the legacy software and status quo processes we’ve encountered are grossly inefficient.

Not long ago, for example, we began working with a client that was using so many un-integrated vendors to handle different parts of the claims process (salvage, parts, DRP, etc.) that the adjusters had to keep eight different browsers open on their computers to do their jobs. And many tasks had to be performed manually.

It doesn’t have to be that way.

Forward-thinking carriers are quickly adopting process-improvement strategies and tactics. They realize that in a fast-changing claims environment, doing nothing risks losing customers to more agile, efficient and customer-centric competitors.

Too much hassle?

Some “status quo preservers” do have a valid point when it comes to the hassle of moving to new software. Instead of providing clients with scalable, easy-to-use software that helps managers and employees alleviate stress and become more productive, some vendors sell their products and walk away. IT departments and employees are left to figure out how to integrate and operate the new system. The best tech-solution providers don’t do that. Nor do good service providers, such as ACD.

See also: The One Thing to Do to Innovate on Claims  

Of course, making the transition to new software is never seamless. There’s a learning curve associated with anything new. But in today’s supercharged competitive environment, the risks of doing nothing far outweigh the hassles of adopting more integrated, more efficient tech platforms.

With each passing day, the definition of “status quo” keeps moving forward. So the claims manager who tries to preserve the status quo is actually traveling backward relative to the competition — and that’s a place no insurance company can afford to stay for long.

Cars That Self-Assess Accidents

“Star Trek” fans love to point out that, over the last five decades, many of the show’s futuristic technologies have gone from science fiction to fact. Mobile communicators (cell phones), non-invasive surgery (focused ultrasound surgery), food replicators (3D printers) and phasers (now being tested by the U.S. military) are but a few examples.

But in its own way, a show in the 1980s was just as prescient: “Knight Rider”– a show about the exploits of Michael Knight (David Hasselhoff) and his car KITT, a talking, thinking and feeling car is nearly spot on.

In the show, this highly autonomous vehicle could map locations, conduct video calls and talk much like Apple’s Siri system. In reality that’s headed our way, automobiles that feel and virtually think will be made possible by technologies that include augmented reality, microscopic sensors and mini-microprocessors. These technologies will enable vehicles to perform a variety of tasks now done by humans – from assessing the damage caused by accidents and ordering replacement parts to booking rental cars and assessing liability.

Tomorrow’s vehicles will, in part, assume the roles of insurance adjusters, collision-repair technicians and drivers. And “tomorrow” may not be too far off.

“Smart Skin”

Already, engineers at the British defense, security and aerospace company BAE are developing a “smart skin” – a thin surface that could be embedded with thousands of micro-sensors (aka “motes”). The company says that when this layer is applied to an aircraft, it will gain the ability to sense wind speed, temperature, physical strain and movement with a high degree of accuracy.

According to several articles, the micro-sensors could be as small as dust particles and could be sprayed on the surface of the aircraft (and on a car or truck). The motes would have their own power source and, when paired with the right software, communicate in much the same way that human skin communicates with the brain.

Once sensory and virtual-reality technologies have evolved to the point where our vehicles can genuinely “feel” and evaluate changes to themselves and their environment, the main thing needed to complete this automotive Internet of  Things will be data – lots of real-time data that is freely exchanged between car owners, insurance companies, auto repair shops and auto manufacturers. Achieving a consensus among consumers and corporations about when, what and how much data should be exchanged may be a sticking point, but, once that agreement is reached, it will be just a matter of time before self-diagnosing cars start hitting the roads.

The Car of Tomorrow

Imagine a future in which your car is covered with an intelligent “skin” that monitors every component and function – from the engine to the exterior sheet metal.

Now imagine the moment your car gets into an accident. The car will instantly calculate how much damage has been done, where it was done and what needs to be repaired or replaced. This information will be quickly ascertained and collected by the vehicle’s computer. From there, it will be transmitted to the cloud, where it can be downloaded by a repair facility or insurance company. By viewing a three-dimensional virtual-reality image of the automobile, the repair technician and insurance adjuster could literally “see” – and almost feel and touch – the damage.

Imagine a time when all that damage is self-assessed by the vehicle. It diagnoses itself, feeds the information into estimating software and tells the collision-repair shop what needs to be done. The vehicle also determines how long repairs should take and even orders parts by automatically sourcing suppliers. All this ensures that your vehicle is fixed ASAP. In addition, your hyper-smart car can order a rental, so you’ll have alternative transportation while the claim is being processed.

All the information regarding your accident – the speed at which you were traveling, location, direction of travel, etc. – will be instantly transmitted to your insurer, enabling the adjuster to make more educated decisions. Think of all that information being fed to a predictive, cognitive claims system that can make intelligent recommendations, helping consumers receive the best possible outcome on every claim.

This is the future – an era when data, sensor and cognitive computing technology are meshed to create a seamless auto claims process that speeds repairs, handles claims more efficiently and provides an amazing customer experience.

Training the Future Claims Adjuster

Unless you’ve been frozen in carbonite for the past 15 years, you’re probably aware that the insurance industry is facing two imminent HR crises:

  1. A Brain Drain– Twenty-five percent of the industry workforce is expected to retire by 2018, according to Insurance Business America. But wait! It gets better. In addition to filling vacancies caused by attrition, companies will have to recruit workers to staff the 200,000 new jobs the Bureau of Labor Statistics expects the industry to create by 2022.
  1. An Enthusiasm Gap– Even today, the industry is struggling to attract young talent. According to a 2012 study by the Griffith Insurance Education Foundation, only 5% of Millennial students describe themselves as “very interested” in working in the insurance industry. When it comes to considering a career as a claims adjuster, the “Y” in Generation Y stands for “yawn.”

Two Problems, One Solution

I believe new and emerging information technologies will play a critical role in overcoming both the Brain Drain and Enthusiasm Gap.

Many young people would rather view an endless loop of piano-playing cat videos on YouTube than work as a claims adjuster. Or so they think

With the imminent arrival of usage-based insurance, there is a lot of excitement developing in the underwriting sector, and I believe the same level of enthusiasm will also attach to technologies such as cognitive analytic computing. These new technologies are innovative. They’re challenging. They’re fun.

More important: Technologies like cognitive computing will change the very nature of the claims adjuster’s job – from one that requires a fair amount of dull administrative tasks to one that places much more emphasis on analysis, creative problem-solving and people skills.

Skills Will Trump Experience

In the future, we’ll see fewer claims adjusters in the workforce, but this smaller pool of talent will be trained in a different ways and in different skillsets than previous generations. Tomorrow’s adjuster will not possess – and will not need – the wealth of experience, knowledge and (to some extent) skills as today’s adjuster. Instead, new technologies will provide them with the tools to instantaneously obtain that knowledge, experience and skill.

The future adjuster won’t be trained in many of the manual and repetitive tasks his predecessor had to learn. Tasks with little or no value will be automated. Rather, the adjuster will have to be tech-savvy. She will have to know how to analyze information because, even with the help of cognitive computing, she’ll still need to analyze reams of information – data related to vehicles, collision-avoidance technology and event data recorders.

She will also have to be familiar with product liability issues. When self-driving cars become commonplace, adjusters may not be dealing with losses involving driver fault. Instead, they may encounter instances in which the vehicles malfunctioned – product-liability claims – and will have to know how to process claims with vehicle manufacturers and the suppliers of advanced collision-avoidance systems. Future adjusters will need to tap skills and knowledge that their forbears never dreamed of.

Tech-Savvy and People-Savvy

Future adjusters will have to be much more tech-savvy, even though they’ll be responsible for performing fewer tasks. At the same time, they’ll need superior people skills to ensure that customer service isn’t lost amid increasingly automated processes. Although the industry will automate many tasks, and many customers will be pleased with this development, customers are already demanding higher levels of customer service. The “personal touch” isn’t just a side benefit: It’s often the main driver behind a consumer’s decision to choose one carrier over another.

So adjusters of the future will be people who are very customer-oriented, very tech-savvy, very intelligent and very skilled at interpreting mountains of data. They won’t have to perform a lot of clerical and administrative tasks. Automation will virtually eliminate that work. But they will have to know how to optimize new technologies to deliver superior customer service and the best possible outcome to every claim.

We in the claims industry have to find ways to inspire, energize and interest young people in careers as claims adjusters. Currently, this isn’t a vocation many Millennials seek. With the help of new and emerging technologies, however, we can be seen as a fun, innovative and inventive sector that adds value to the lives of ordinary people. After all, getting into accidents causes a great deal of stress for most vehicle owners. For that reason, our industry needs adjusters who are adept at a wide variety of claims-processing and customer-service challenges.

Solution to Brain Drain in Insurance?

What was once science fiction is fast becoming a fact of today’s business world. Computers that mimic the human brain are already entering the workforce in the healthcare, financial services and retail sectors, among others.

Like humans, cognitive analytic computers can understand “natural” language (such as English) and learn lessons from the data they analyze, as well as from the users who “mentor” them. In other words, the machines possess an artificial intelligence more powerful than anything seen before.

Unlike humans, cognitive analytic systems can process, analyze and store enormous volumes of data at Internet speed. In addition to tapping conventional databases for the information needed to aid in decision-making, the machines are capable of scanning myriad emails, reports, articles, books and other sources of knowledge to deliver recommendations and reach conclusions beyond the ability of any one person or team of people.

In a 2014 white paper on cognitive analytics, Rajeev Ronanki and David Steier of Deloitte Consulting note that in the healthcare industry, “[cognitive analytic] systems are being used to improve the quality of patient outcomes. A wide range of structured inputs, such as claims records, patient files and outbreak statistics are coupled with unstructured inputs such as medical journals and textbooks, clinician notes and social media feeds. Patient diagnoses can incorporate new medical evidence and individual patient histories, removing economic and geographic constraints that can prevent access to leading medical knowledge.”

In financial services, cognitive analytics is used to recommend and execute trades and to also assist in fraud detection and risk underwriting.

Many of us are familiar with less advanced forms of cognitive analytics. In the consumer electronics realm, examples include Apple’s Siri voice recognition software and the oral command interface used in the Xbox video game system.

Virtual Decision-Making Assistance

It doesn’t take much imagination or intelligence (human or artificial) to envision how cognitive analytics could revolutionize auto insurance, especially the claims sector.

Cognitive analytic computing could be of enormous benefit to an industry that will see fewer claims adjusters in the near future, thanks to the number of veteran adjusters who are retiring or planning to retire. Cognitive analytics could empower the remaining adjusters with decision-making assistance that was previously inconceivable – decision-making based on huge volumes of data drawn from a near-infinite pool of sources.

Not long from now, computers will be able to scan photos of accident damage and instantly retrieve historical data on how similar claims were assessed and settled in the past. For example, a computer could analyze a person’s injuries relative to where they were sitting when the accident occurred and how the injury was sustained.

The systems could also be used in first notice of loss (FNOL). Imagine an intelligent learning system that can reference every text related to previous claims and outcomes, as well as every law and vehicle code from all 50 states, to deliver settlement information in milliseconds.

Let’s say a customer submits an FNOL. “I was in a parking lot, but when I backed out of my space I hit someone driving past.” Based on the information provided, the machine could determine liability and assign fault. It could also decide whether the claim is best processed with the help of a human adjuster or via self-service. If a customer reports an accident that leaves a small scratch on the car and no injuries, the computer would automatically send a self-service text to the claimant’s cell phone so she could take photos of the damage and transmit them back to the computer. The machine would then analyze the photos and develop an assessment.

Yes, the computing system could be that advanced – so advanced that it removes much of the human element from the process.

‘Brain Gain’ Instead of ‘Brain Drain’

Many adjusters in their 50s and 60s are retiring, which means a lot of valuable expertise and experience is leaving the industry. In fact, I’m probably a member of the last generation that remembers widespread use of full-service, multi-skilled adjusters – people who know every aspect of the business. Younger adjusters frequently work in silos. These compartmentalized workers are very skilled in certain things but don’t have the “Renaissance man” backgrounds that allowed their predecessors to wear “multiple hats” when the situations called for it.

Thanks to the new technology, however, the older generation’s experience and know-how doesn’t have to be lost forever. That information and wisdom can be transferred to complex cognitive computing systems that instantly retrieve the data on every one of their past settlements. This will let the remaining adjusters use the machines as virtual assistants, calling on them to provide the most logical settlement paths to the best possible outcomes.

If achieving the best outcomes to claims is the goal, then cognitive computing systems will prove to be an invaluable tool. With access to a virtual universe of prior decision-making (good and bad), cognitive analytics has the potential to help adjusters find the right solution to each and every auto claims case.