The age of insurtech has brought a wave of new digital experiences and automation in insurance. From websites that instantaneously compare auto insurance quotes to mobile apps that allow us to submit claims directly by snapping a picture of a damaged window, we continue to benefit from significant improvements to the insured experience.

These improvements in distribution and claims are part of an industry-wide appetite for increased accuracy and efficiency, including in underwriting. Personal lines carriers have already made good strides, and carriers see a similar opportunity to improve loss and expense ratios in commercial lines.

For small business policies that involve a high volume of submissions and lower premiums, the challenge is to enable an efficient, high-throughput underwriting process that complies with exacting standards for quality. In the mid-market, the stakes are even higher for underwriters. They must be diligent about selecting high-quality risk against a backdrop of declining capacity and a tsunami of submissions from brokers who remarket risks in search of better rates.

While the goal of shorter time-to-quote is laudable, and addresses a critical frustration for insureds and brokers, the implementation often overlooks the crucial role that underwriters play. By failing to listen to underwriters' needs and play to their strengths as expert assessors of risk, technology providers and insurers alike continue to achieve sub-optimal underwriting outcomes.

Commercial underwriters are at the forefront of some of the most challenging and important work in the industry. They serve a multi-faceted role: developing and fostering relationships with brokers, exhaustively reviewing submissions, validating an insured's business and property information, analyzing exposures and, eventually, rating, quoting and binding policies. Underwriters must bridge the gap between carriers that set aggressive goals for profitable premium growth and brokers who want a quote "yesterday" -- and often pair incomplete submissions with demands for a rapid turnaround.

When underwriters conduct a thorough investigation of the risk – executing online searches, ordering inspections and asking tough questions, they’re invariably perceived as being too slow, inflexible and uncooperative. If they compromise on thoroughness to increase throughput, or if too many submissions are superficially passed through, their book may grow quickly, but the quality and profitability will suffer. All the while, underwriters want to deliver a comprehensive policy that best addresses the insured’s needs and grows the relationship. Reconciling these often-conflicting priorities is difficult but sets the most effective and experienced underwriters apart.

Data analytics, artificial intelligence and machine learning can make a big difference but, for most insurers, have failed to deliver great value within underwriting.

Improving outcomes requires an approach that combines the best of underwriter judgment with machine intelligence.

See also: The Future of Underwriting

Specialized, AI-powered software can now do much of the heavy lifting for underwriters, while eliminating frustrating activities. Underwriters who experiment with, and embrace, new technologies are already setting themselves apart from their peers. They stand to improve their individual performance and also help to chart the future course of underwriting within their organizations.

For insurtechs to truly deliver on their collective promise, they need to empower those who are actually performing the work of insurance. Automation and machine learning need to be force multipliers for underwriting excellence – not poor substitutes for it. Getting this right will lead to a better experience for the insured and superior outcomes for the industry.

Within the Biden administration's first weeks, the Office of Science and Technology Policy has been elevated to a cabinet-level position. Biden has appointed Alondra Nelson as deputy director. She is a scholar of science, technology and social inequality. In her acceptance speech, Nelson shared, "When we provide inputs to the algorithm, when we program the device, when we design, test and research, we are making human choices." We can expect artificial intelligence (AI) bias, ethics and accountability to be more significant issues under our new president. 

The financial services industry has a long and dark history of redlining and underserving minority communities. Regardless of regulation, insurers must take steps now to address the ethical concerns surrounding AI and data. 

Insurers are investing heavily and increasingly adopting AI and big data to improve business operations. Juniper Research estimates the value of global insurance premiums underwritten by AI will exceed $20 billion by 2024. Allstate considers its cognitive AI agent, Amelia, which has more than 250,000 conversations per month with customers, an essential component of its customer service strategy. Swiss Re Institute analyzed patent databases and found the number of machine-learning patents filed by insurers has increased dramatically from 12 in 2010 to 693 in 2018. 

There is no denying that AI and big data hold a lot of promise to transform insurance. Using AI, underwriters can spot patterns and connections at a scale impossible for a human to do. AI can accelerate risk assessments, improve fraud detection, help predict customer needs, drive lead generation and automate marketing campaigns. 

However, AI can reproduce and amplify historical human and societal biases. Some of us can still remember Microsoft's disastrous unveiling of its new AI chatbot, Tay, on social media site Twitter five years ago. Described as an experiment in "conversational understanding," Tay was supposed to mimic the speaking style of a teenage girl, and entertain 18- to 24-year-old Americans in a positive way. Instead of casual and playful conversations, Tay repeated back the politically incorrect, racist and sexist comments Twitter users hurled her way. In just one day, Twitter had taught Tay to be misogynistic and racist. 

In a study evaluating 189 facial recognition algorithms from more than 99 developers, the U.S. National Institute of Standards and Technology found algorithms developed in the U.S. had trouble recognizing Asian, African-American and Native-American faces. By comparison, algorithms developed in Asian countries could recognize Asian and Caucasian faces equally well.

Apple Card's algorithm sparked an investigation by financial regulators soon after it launched when it appeared to offer wives lower credit lines than their husbands. Goldman Sachs has said its algorithm does not use gender as an input. However, gender-blind algorithms drawing on data that is biased against women can lead to unwanted biases. 

Even when we remove gender and race from algorithm-models, there remains a strong correlation of race and gender with data inputs. ZIP codes, disease predispositions, last names, criminal records, income and job titles have all been identified as proxies for race or gender. Biases creep in this way. 

See also: Despite COVID, Tech Investment Continues

There is another issue: the inexplicability of black-box predictive models. Black-box predictive models, created by machine-learning algorithms from the data inputs we provide, can be highly accurate. However, they are also so complicated that even the programmers themselves cannot explain how these algorithms reach their final predictions, according to an article in the Harvard Data Science Review. Initially developed for low-stakes decisions like online advertising or web searching, these black-box machine-learning techniques are increasingly making high-stakes decisions that affect people's lives. 

Successful AI and data analytics users know not to go where data leads them or fall into the trap of relying on data that are biased against minority and disadvantaged communities. Big data is not always able to capture the granular insights that explain human behaviors, motivations and pain points. 

Consider Infinity Insurance, an auto insurance provider focused on offering non-standard auto insurance to the Hispanic community. Relying on historical data, insurers had for years charged substantially higher prices for drivers with certain risk factors, including new or young drivers, drivers with low or no credit scores or drivers with an unusual driver's license status. 

Infinity recognized that first-generation Latinos, who are not necessarily high-risk drivers, often have these unusual circumstances. Infinity reached out to Hispanic drivers offering affordable non-standard policies, bilingual customer support and sales agents. Infinity has grown to become the second-largest writer of non-standard auto insurance in the U.S. In 2018, Kemper paid $1.6 billion to acquire Infinity. 

Underserved communities offer great opportunities for expansion that are often missed or overlooked when relying solely on data sets and data inputs. 

Insurers must also actively manage AI and data inputs to avoid racial bias and look beyond demographics and race to segment out the best risks and determine the right price. As an industry, we have made significant progress toward removing bias. We cannot allow these fantastic tools and technologies to enable this harmful and unintended discrimination. We must not repeat these mistakes. 

As we reflect on all that occurred during the turbulent and chaotic year that was 2020, one thing stands out: It was a year of innovation. Virtually every business that survived, and most that thrived, innovated in some fashion, whether it was their business models, efficiency improvements or communications.

These innovations, while necessary to survive pandemic-related economic challenges, are all the more remarkable because the coming decade will represent an even bigger innovation challenge to independent agencies — perhaps more than at any other time in industry history.  

Due to the unprecedented volume of owner retirements, consolidations and even startup activity, the composition of the industry is changing rapidly. Agency business models are evolving. Forcing this change are customer demand, new ways of marketing, carrier challenges, talent shortages, a rapidly evolving economy and rapidly evolving technology.  

Evolving Technology Investments

The biggest technology challenge to confront agencies this past year was spurred by the need to isolate workforces and virtualize. Many agencies were forced to make unplanned investments in computers, software for managing a distributed workforce and, in many cases, upgraded cyber protection. For more than a few agencies, these unplanned investments were financially painful.  

It is also possible — even likely — that the useful life of these investments will be measured in months rather than years. This faster evolution of technology tools is likely to represent a new paradigm for agents who want to maintain their competitiveness. Agents have traditionally been conservative when making capital investments, typically expecting many years of service and utility from them. But those who want to stay on the cutting edge will need to adjust their mindset and acknowledge that instead of 10 years of service from a new investment, they may only see three. 

This trend clearly affects an agency’s return on investment, and it will be wise for agents to consider the impact on their bottom line. Agencies will need to grow larger and faster or accept lower margins. One piece of good news is that the technology that agencies need to invest in, whether websites, software or communications technologies, increasingly can be purchased on a per-use basis, or on a software as service basis (SAAS). This trend makes typical capital items, which are fixed costs to the balance sheet, variable expenses to the income statement.

One area where agencies will need to invest significant sums are web portals, websites and web-based communication. With customers demanding self-service capabilities with 24/7/365 communications access, agents can no longer consider a website as just an electronic brochure. Websites must be connected to the agency management system and need to allow customers to serve themselves directly in a variety of ways. 

See also: Does Remote Work Halt Innovation?

To meet these demands, today’s websites are necessarily more robust and need to be rebuilt more frequently than in the past. Where an agency might have gotten five years of effective use out of a website, in some cases even longer, the future will demand website redevelopment projects every two or three years.

Changing Business Models

As agencies grow ever larger due to consolidation and aggregation, the insurance distribution marketplace must grow more competitive. Agents will be forced to offer products, services and access that they may have avoided up until now, or face losing business at the margins to larger, more relevant competitors.  

Again, the choice will be between lower revenue, lower profits due to loss of business or potentially lower margins due to increased investment. This will force agency principals to focus on cost control, efficiency and sound business practices more than ever before. While technology-driven efficiency will lower costs as producers and service employees manage ever larger books of business, agencies will need to acquire new human capital in the form of data scientists, sophisticated business managers and data-driven marketers.  

Many observers expect the number of independent agencies to decrease from roughly 35,000 today to between 20,000 and 25,000 within 10 years. This trend is expected due to the factors discussed here, but also, in some cases, because of an agency’s failure to maintain itself as a going concern. 

Those agencies that meet the challenges and make this transition will be similar in some respects to today's agencies. They will be serving clients who value the relationships they have and the expertise they bring. But the survivors will need to innovate to be nimbler and more cost-efficient than ever before. They will need to make more frequent investment in changing technology and in staff and become better businesspeople than ever before.

Much of North America is seeing lower interest rates across the board, which bodes well for consumers making large purchases but puts the insurance industry under intense scrutiny. Carriers with bond-heavy portfolios may see a decline in returns and, as a result, lower profit margins. Despite the insurance industry’s overall acceleration toward technology in 2020, carriers of all lines of business will need to move much more quickly – or risk falling even further behind their profit margin.

Insurers should cut unit costs, but not corners.

Insurers must cut costs; however, with more consumers requiring personalized attention from their insurance company, insurers must walk a fine line. Reducing expenses may be necessary, but insurance companies must be careful not to lose their existing customers in the process. Automation -- especially a newer form, called cognitive process automation (CPA) -- allows for reducing costs while still providing the service that customers require.

In some departments, such as underwriting and billing, insurance companies should prioritize responsivity for a more convenient customer experience. This can be done by using process automation to streamline communication between the carrier and the policyholder.

In other departments, such as claims, policyholders will appreciate careful and attentive human interaction. While responsiveness is still paramount, customers will have more trust in the company’s claim-handling process when they have access to a dedicated claims adjuster. 

Where resources are scarce, technology is a viable solution.

Even prior to the impact of COVID-19, carriers like Protective Insurance had begun implementing CPA, a more advanced version of robotic process automation (RPA).

Many carriers have at least discussed the features and capabilities of RPA. However, RPA and even intelligent process automation (IPA) products are primarily limited to structured data. 

CPA is the new disruptor in both the insurance and automation industries. Combining the repetitive abilities of traditional RPA with artificial intelligence (AI) and machine learning, CPA relies on bots that capture data and scan documents via optical character recognition (OCR) but that also do much more. The bots can fully automate entire underwriting and claims processes, from start to finish, with minimal human intervention.

See also: 20 Issues to Watch in 2021

As an example, policy underwriting has traditionally been considered a manual undertaking, but CPA has demonstrated that underwriting can be largely automated -- everything from policy submission to risk rating and underwriting to issuing declinations and binders. Using CPA, insurers can write more new business, streamline the renewal process and even detect cases of potential fraud with minimal human supervision.

Claims departments can significantly reduce the manpower needed for largely repetitive processes. Bots programmed with CPA can fully automate the first notice of loss (FNOL) process, fraud investigations, benefits calculations and even payments. In fact, time-consuming processes like claims communications can be automated up to 95%. 

Employees can instead focus on more engaging tasks and provide better service on edge cases.

Increased efficiency is more remunerative than reduced overhead.

In cutting expenses, the matter of efficiency is sometimes overlooked. If time is money, shouldn’t carriers condense time-consuming processes, as well?

Automation saves time and money. Whenever carriers optimize a process by implementing an automation solution, a precious resource has been created: time. 

As the policyholder mindset continues to grow in favor of more personalized experiences, cognitive automation allows insurance carriers to use their best asset – their human workforce – to focus on retention efforts, customer satisfaction and even cross-selling additional lines of business. At its heart, insurance is a people-focused business, and even tech-friendly consumers prefer personalized human interactions.

The takeaway

With lower interest rates threatening profit margins, insurance carriers must target cost reductions – and sooner rather than later. Companies can use new process automation tools, such as RPA and CPA, to cut redundant work often found in underwriting and claims departments. Insurers are then able to reprioritize the focus of their workforce on customer retention, or even scaling for growth.

One of the most clichéd claims made in our industry is that of being a "trusted adviser." Sure, trust is essential. Clients need to trust in your ability to do your job, and they need to trust in your intentions when giving advice.

But is earning trust brag-worthy? Isn't trust a minimum expectation of the advisor-client relationship?

The real goal should be achieving "go-to" status.

What questions do you want your clients to bring you?

More importantly, what questions are they bringing you now? Not to be an alarmist, but if those questions are limited to insurance issues, your client relationship is in danger.

When asked how they wanted to be viewed, one of our clients responded with the following, "I want to be THE partner my clients go to to ask their toughest questions. I want to help my clients accomplish their intentions."

I LOVE that! Notice, it doesn't say their toughest "benefits questions" or even "accomplish their HR intentions." The commitment is to be the partner their clients go to for help with anything challenging their business.

How cool is that?! Or maybe the idea makes you feel a little uncomfortable?

It is increasingly necessary

If you've been in sales for any amount of time, you know it's more challenging than ever to deliver value to a buyer. Heck, if you were selling a year ago, you see how much more difficult it became because of the pandemic.

The increased challenge to deliver value started way before 2020, though. There are many reasons, but one stands out.

Buyers no longer depend on a salesperson to learn about a product or service.

Not only that, buyers don't want to talk to anyone until they decide they're ready. They will self-educate on their own terms and at their own pace.

It's not that they don't eventually want to talk to a salesperson, but buyers are now way further into the buying process before they go to a salesperson with questions. This means the value bar has been raised significantly for salespeople. The further you've advanced on the value spectrum, the more important your eventual conversations will be.

How are you perceived?

If you want to know how prospects/clients perceive and categorize you, look no further than the questions you are asked.

Vendor — "Can you get me a better quote?"

If you are mostly getting price questions, you are viewed as a commodity.

Insightful Seller — "Can you help me effectively communicate my benefits program and deal with compliance issues?"

At this level, salespeople understand the commoditized product offering so well they can help buyers get more value from it than if they bought it from someone else.

Educational path to this level — Instead of studying your products and services' features and benefits, study the problems they solve.

Trusted Adviser — "Can you help me better understand what solutions I should be considering and show me how to use them effectively?"

Salespeople at this level are selling the problems they solve rather than the products. The best at this level aren't even really selling; the buyers trust they can help them make better buying decisions.

Path to this level - Study and implement a consultative selling process that makes the buying process more manageable.

Strategic Adviser — At this level, questions start to become, as you might guess, strategic. "You seem to understand our industry and the current business environment; what can we be doing to compete more effectively?"

These advisers bring a new perspective to the buyer and help them see things they hadn't seen before, like environmental challenges and opportunities.

Path to this level — Study a specific industry or the business environment, in general.

Go-to Adviser — At this level, clients pull back their curtain and share their most vulnerable self. You know you've arrived in the relationship when asked, "We have some internal growth pains. Can we talk about suggestions you would have to get past them?"

Go-to advisers have proven their ability to address the challenges and opportunities a buyer faces internally, challenges that buyers don't see on their own even though they are surrounded by them daily. Even if buyers do see the challenges, they don't know how to address them.

Path to this level — Study business operations: marketing, finance, strategy, processes, everything it takes to run a successful business.

Challenge yourself to pursue the various educational paths along this value progression. By doing so, you will put yourself in a position to be that go-to relationship for your clients. Talk about a game changer!

See also: 3 Tips for Increasing Customer Engagement

You don't have to have all the answers

If the idea of being "the partner your clients go to with their toughest questions" makes you uncomfortable, it shouldn't. Just because they come to you with their toughest questions, it doesn't mean they expect you to have all the answers.

To become a Go-to adviser, you only need to be willing to participate in conversations that lead to the answers.

I suspect you already take this approach in a much narrower way. If you are a benefits producer, you may find yourself in compliance conversations that reach your knowledge limit. At that point, you bring in a compliance specialist. Or perhaps you find yourself deeper in HR topics than you can handle, but you are comfortable because you know where to pass the baton.

A problem-solving framework

If you follow the educational paths mentioned earlier, you'll create a foundation that can support a Go-to relationship. With that knowledge foundation in place, the following framework will be an effective way to help your prospects/clients think through any challenge they bring you.

1. Define the goal by asking, "If we were sitting here celebrating a successful resolution, what are some of the specifics we would be celebrating?"

This question will provide clarity as to what they want/need to accomplish.

2. "What are the PEOPLE issues you need to deal with to achieve a resolution?"

Maybe they have toxic people on the team; perhaps they need new people, or maybe they need to train those they have.

3. "What PRODUCT/SERVICE issues need to be addressed?"

Maybe there is a deliverable to be created, upgraded or even abandoned.

4. "Are there PROCESS issues standing in your way?"

It could be they have the answers they need but aren't operating in a consistent, process-driven manner.

Will the complete answer be apparent with these questions? Probably not. However, by defining the goal and evaluating the people, product and process issues that determine success, you will help the prospect/client find clarity about what needs to happen next.

Your role as a Go-to advisor isn't so much to give specific answers; it's more about asking additional questions to reveal the path leading to the answer.

Is all this necessary?

You could make an argument that this type of progression isn't necessary. I wouldn't agree with you, but you could make the argument. After all, you will win the occasional deal based on price alone. Don't fall into that "easy" trap.

It does take hard work to progress. However, every level you advance toward Go-to status provides exceptional ROI:

1. It reduces the amount of competition.
2. The buyer becomes less sensitive to price.
3. You shorten the sales cycle.
4. Your retention rate increases.
5. You will find it easier to access decision-makers.
6. The level of credibility you bring to the conversation will grow exponentially.

So, I'll ask you a "not tough" question. Is it worth it to become a Go-to adviser?

Seems like a no-brainer to me.

This article was originally published here.

Open insurance is about sharing vast and ever-growing volumes of structured data in a digital ecosystem to stimulate the creation of innovative insurance-related propositions for consumers. When customers are made the focal point of new digital business models, new opportunities continuously arise for cross-sectoral partnerships, platforms or collaborative efforts. 

This means that it is crucial for insurance companies to allow third parties (e.g. banks, fintech, aggregators, mobility providers, etc.) to access their data, products and services, and also for them to be present – and relevant – in their customers’ digital ecosystems. Like open banking, open insurance initiatives drive API-enabled access to insurance data, products and services. 

The Open Insurance Monitor presents how the insurance industry is developing towards open APIs

A rich API portfolio supports the best service provision toward customers and partners within third-party platforms. It is also important for insurers to offer a good developer experience to create the optimal environment for collaborative partnerships and innovation. INNOPAY, a consultancy, has launched the Open Insurance Monitor (OIM) to continuously measure and benchmark this functional scope of APIs and developer experience offered in the insurance landscape (see figure 1). OIM considers organizations around the world that publish insurance APIs via developer portals, including insurers, insurtechs and banks. 

Three key insights from the Open Insurance Monitor

1. Lack of focus on developer experience

The OIM reveals that insurers’ first efforts are mostly aimed at establishing a rich API portfolio with insurance-related functionality, with minimal focus on the developer experience.

The top left corner of Figure 2 shows several insurers leading the way as innovators of functionality. AXA offers a wide variety of functionality in most components of the insurance value chain and for multiple types of insurance products. These services include quoting and selling insurance, claims management and service-provider support during the execution of services to clients. Cover Genius also offers services in multiple components of the value chain, including services for product origination as well as claims management. Health insurer Humana provides a wide variety of API services such as enrollment in medical care programs, retrieval of medical information and supporting functionality for medical professionals during the execution of services. 

Analysis reveals that insurers are still only in the early stages in terms of creating the developer experience. Although most insurers have taken initial steps in providing API documentation, there is a strong focus on the technical aspect or specifications of APIs. The developer experience could often be further improved by increasing developer usability (e.g. tools, tutorials) and engaging with the community to spur collaboration and innovation.

See also: Designing a Digital Insurance Ecosystem

2. Banks are making inroads, too

Unsurprisingly, the banks included in the OIM offer a more advanced developer experience due to their open banking efforts and investments. Extending their API portfolios with insurance services would further boost their bancassurance models. 

The OIM identified a small group of banks that offer insurance services through APIs. This is the next wave of bancassurance and is an interesting revenue model for open banking. Thanks to their open banking capabilities, the banks included all have a solid basis in terms of API documentation and developer usability. Standard Chartered sets itself apart through features for community development such as regularly posting news articles and organizing hackathons and other types of events. OCBC emerges as a good all-round player in all components of developer experience, while Citi stands out in terms of developer usability by supporting fast onboarding and providing instruction guides for calling APIs, authentication and the sandbox environment. However, the scope of insurance-related functionality at these banks is still limited. If they decide to extend their API portfolios with related services, they will move toward becoming masters in openness, which will boost their bancassurance models.

3. Insurers are lagging behind in openness

Benchmarking against the masters in openness (e.g., National Bank of Greece and Deutsche Bank) reveals that insurers still have a long way to go in terms of openness. In fact, out of all the parties analyzed, only one is currently a master in openness: the U.S.-based insurance company Nationwide, thanks to offering a variety of insurance APIs plus enhancing the developer experience through clear documentation and good developer usability.

Nationwide’s extensive API portfolio currently consists of a variety of services for information retrieval, insurance quoting and issuing policies as well as APIs aimed at policy servicing. Portfolio extension could be achieved by including API services for managing claims and supporting service providers. Besides providing clear technical API documentation, Nationwide sets itself apart from other developer portals by emphasizing the business potential of its APIs through feature display and use cases, as well as offering good developer usability. 

No overall winner

As with open banking, there is currently no overall winner in the open insurance landscape based on the developer portal capability model, as depicted in Figure 3.

See also: 2021: The Great Reset in Insurance

For more details on the monitor and how to get access to digital ecosystems, please visit the website.

Surprising Lack of Innovation Plans Paul Carroll, Editor-in-Chief of ITL The 2020 Global Concerns Survey of insurance leaders by the International Insurance Society contains two major surprises. (I got an early look because ITL collaborated on this latest annual survey.) The smaller surprise is that COVID-19 ranks only second among the most important issues the executives identified. I had expected that the pandemic would be the top concern, given that 2.4 million people have died worldwide, that economies have been devastated and that insurers face exposure, especially given the recent decision by the U.K. Supreme Court that business-interruption insurance should cover pandemic-related claims. The bigger surprise is that, while innovation is the top concern, only 35% of respondents said they have an active, comprehensive plan — meaning that two-thirds do not... continue reading > SIX THINGS 4 Connectivity Trends to Watch in 2021 by Dave Acker In a business defined by relationships, connecting well on a virtual basis will be more than a change — it will be a requirement. Read More The Intersection of IoT and Ecosystems by Matteo Carbone Insurers can build a sort of digital twin of the customer, then tailor their offerings and improve the customer experience. Read More Let’s Do More Than Create Faster Horses by Tim Kershaw COVID-19 has accelerated adoption of e-trading and smashed paradigms. There is an opening for something fundamentally new. Read More How AI Can Transform Insurance Correspondence sponsored by Messagepoint Focusing on customer experience is a winning strategy as digital transformation efforts accelerate into 2021. Learn how AI-based tools are helping industries modernize their systems, optimize their content, and manage customer communications intelligently. Watch Now Closing the Protection Gap by Simon Young With climate risk on the rise and exposure growing, parametric insurance can plug the gaps left by traditional insurance. Read More Why CX Must Trump Efficiency by Renaud Million Companies talk about improving customer experience but focus too much on saving money. Customer process automation does both. Read More CISOs, Risk Managers: Better Together by Charles Pruzinsky In most large firms, risk managers buy cyber insurance--but are rarely expert in network security and may not fully understand the risk profile. Read More MORE FROM ITL February's Topic: Blockchain While the pandemic has greatly accelerated the digitization of the insurance industry — turning years into months — it has also shown us how very far we still have to go. As a rule of thumb, I’ve heard consultants say that 50% of the operating costs need to be driven out of the industry in the next five years. Blockchain has held out this promise for some time now. It’s lost a bit of its shine because it’s been identified as a hot technology of the year for so many years in a row. But it may be coming into its own, with some uses starting to move into production. Take Me There The Future of Blockchain Series Episode 3 Usage in Life & Annuities Having explored the possibilities for blockchain in personal lines and commercial lines in P&C, we conclude our webinar series on the technology by taking a look at two use cases in life and annuities that are close to moving into production.  Watch Now GET INVOLVED Write for Us Our authors are what set Insurance Thought Leadership apart. Get Started Partner with Us We’d love to talk to you about how we can improve your marketing ROI. Learn More SPREAD THE WORD Share Share Tweet SUBSCRIBE TO SIX THINGS

Is it myth or reality that remote work is going to halt innovation and collaboration in our workplaces?

We've heard lots of insurers express concern about the possibility, especially because they depend on collaboration to help their organizations build deeper and wider relationships with their agents and brokers to develop more business. Deciding whether the concern is a myth or a reality is tricky, because it's really up to the company and their organization.

Certainly, remote work can make innovation and collaboration more challenging. It removes easy access to that organic, unstructured “white space” where conversations naturally happen: grabbing a cup of coffee, passing in the hallway or chatting and building ideas after a meeting.

Remote work also makes innovation and collaboration even more important. Numerous studies have shown that companies that focused on innovation, both during and after a crisis, financially outperform the companies that do not, both during the crisis and far into the future.

So, it really is important that we do what we can to make sure the concern about remote work stays a myth. 

A silver lining is that the decades-long investments in digital transformation (which, frankly, have happened largely outside of the insurance space) have enabled us to remain connected rather than isolated. We have been able to use tools like Microsoft Teams, Zoom and Slack and online collaboration platforms like Miro to work together while we are apart. The added benefit is that we can tap into the best resources for the topic, project or relationship, regardless of location.

That said, it's not enough just to have the tools available. We also need to create an environment that encourages innovation. The fastest way to derail innovation efforts is to have a fear- or shame-based culture in which teams and employees are too afraid of making mistakes to offer new ideas. A courageous and specifically inclusive approach to ideation and doing business is really crucial – one where risk-taking (including the inevitable failures along the way to success) is rewarded. That's how we get the best ideas and bring them into action.  

Finally, we must make up for the gap in organic connection through a tried-and-true method of driving innovation – creating Networked Improvement Communities.

This approach is widespread outside the insurance space, but it's something we should deploy here for our benefit and that of our organizations, staff and customers. The objective is to create a community within your organization that is specifically dedicated to solving an identified problem. It can be outside the usual structures, teams and siloes. That community works independently on that problem but collaborates in sharing and building on one another’s solutions and ideas, driving innovation and creating deeper relationships across your organization. A great example is the global innovation effort in the scientific, medical and pharma community to develop a vaccine for COVID-19, which has resulted in the fastest vaccine to market by leaps and bounds.  

See also: Tapping Cloud’s Ability to Drive Innovation

Call to Action:

Here are three elements each company can use to ensure that remote work is NOT the end of innovation and collaboration in your organization:  

One: Assess your culture and eliminate any roadblocks to innovation. Reward risk-taking and curiosity. Make sure that you've got an inclusive environment where people are encouraged to challenge the status quo, try new ideas and speak up (even at the risk of failure) to make sure that the best solutions for the situation are sourced and selected. 

Two: Continue to use the many digital tools available for connection to make sure that we don't stay isolated, even in a remote work environment.

Three: Get explicit about creating Networked Improvement Communities to connect your organization’s employees and leaders across siloes to solve a specific problem. They can work independently but collaboratively to amplify solutions. That will create ripple effects, deepening those relationships beyond that specific project and allowing new ideas to form. (This step might be the most important in insurance.) 

If we take these steps, we can ensure that innovation and collaboration continue in workplaces in 2021. Those are the workplaces we all want to join.   

 

According to Willis Towers Watson, more than two-thirds of insurers credit predictive analytics with reducing issues and underwriting expenses, and 60% say the resulting data has helped increase sales and profitability.

That figure is expected to grow significantly over the next year, as the inherent value of predictive analytics in insurance is showing itself in myriad applications.

Predictive analytics tools can now collect data from a variety of sources – both internal and external – to better understand and predict the behavior of insureds. Property and casualty insurance companies are collecting data from telematics, agent interactions, customer interactions, smart homes and even social media to better understand and manage their relationships, claims and underwriting.

Another closely related tool is predictive modeling in insurance, such as using “what-if” modeling, which allows insurers to prepare for the underwriting workload, produce data for filings and evaluate the impact of a change on an insurer’s book of business. The COVID-19 crisis has shown insurers that the ability to predict change is invaluable, and “what-if” modeling is a great tool for carriers that know they need to make changes but want to ensure they are doing it accurately. The right predictive modeling in insurance software can help define and deliver rate changes and new products more efficiently.

Using the plethora of data now available, here are 11 ways predictive analytics in P&C insurance will change the game in 2021.

Pricing and Risk Selection

This isn’t exactly a new use for predictive analytics in insurance, but pricing and risk selection will see improvement thanks to better data insights in 2021. Given the increased variety and sophistication of data sources, information collected by insurers will be more actionable.

Why do these data sets help predictive analytics improve pricing and risk selection? Because they are largely composed of first-hand information. Data and feedback collected from social media, smart devices and interactions between claims specialists and customers is straight from the source. Data that isn’t harvested through outside channels (such as the typical demographic material used in the past, like criminal records, credit history, etc.) is more direct and can provide valuable insights for P&C insurers.

But just how much data are insurers collecting from IoT-enabled devices? Some reports estimate it’s approximately 10 megabytes of data per household, per day, and that figure is expected to increase.

Identifying Customers at Risk of Cancellation

Predictive analytics in P&C insurance is going to help carriers identify many customers who require unique attention – for example, those likely to cancel or lower coverage. More advanced data insights will help insurers identify customers who may be unhappy with their coverage or their carrier.

Having this knowledge in hand will put carriers ahead of the game and allow them to reach out and provide personalized attention to alleviate potential issues. Without predictive analytics, insurers could miss credible warning signs and lose valuable time that could be used to remedy any issues.

Identifying Risk of Fraud

P&C insurance companies are always battling various instances of fraud and oftentimes aren’t as successful as they would like. The Coalition of Insurance Fraud estimates that $80 billion is lost annually from fraudulent claims in the U.S. alone. Additionally, fraud makes up 5% to 10% of claims costs for insurers in the U.S. and Canada.

Using predictive analytics, carriers can identify and prevent fraud or retroactively pursue corrective measures. Many insurers turn to social media for signs of fraudulent behavior, using data gathered after a claim is settled to monitor insureds’ online activity for red flags.

Insurers are also relying on insurance predictive modeling for fraud detection. “Where humans fail, big data and predictive modeling can identify mismatches between the insured party, third parties involved in the claim (e.g. repair shops) and even the insured party’s social media accounts and online activity,” according to SmartDataCollective.

See also: What Predictive Analytics Is Reshaping

Triaging Claims

Customers are always looking for fast, personalized service. In the P&C insurance industry, that can sometimes present a challenge. But with good predictive analytics systems, carriers will be able to prioritize certain claims to save time, money and resources – not to mention retain business and increase customer satisfaction.

Predictive analytics tools can anticipate an insured’s needs, alleviating their concerns and improving their relationship with their carrier. It can also contribute to tighter management of budgets by employing forecasted data regarding claims, giving insurers a strategic advantage.

Focusing on Customer Loyalty

Brand loyalty is important, no matter the product, and now insurers can use predictive analytics to focus on the history and behavior of loyal customers and anticipate what their needs may be. How important is brand loyalty? About half of customers have left a company for a competitor that better suited their needs. Also, this data can help insurers modify their current process or products.

Identifying Outlier Claims

Predictive analytics in insurance can help identify claims that unexpectedly become high-cost losses — often referred to as outlier claims. With proper analytics tools, P&C insurers can review previous claims for similarities – and send alerts to claims specialists – automatically. Advanced notice of potential losses or related complications can help insurers cut down on these outlier claims.

Predictive analytics for outlier claims don’t have to come into play only after a claim has been filed, either; insurance companies can also use lessons learned from outlier claim data preemptively to create plans for handling similar claims in the future.

Transforming the Claims Process

With predictive analytics, insurers can use data to determine events, information or other factors that could affect the outcome of claims. This can streamline the process – which traditionally took weeks and even months – and help the claims department mitigate risks. This also allows insurers to analyze their claims processes based on historical data and make informed decisions to enhance efficiency.

Advancements in artificial intelligence and other analytical tools have also become increasingly important in the claims process and are transforming how carriers do business.

Data Management and Modeling

Data is one of the most valuable assets an insurer can have, and predictive analytics have been helping businesses make the most of that data. From forecasting customer behavior to supporting underwriting processes, predictive analytics and data have been working together to provide valuable insights to insurers for years now.

However, making the most of your data is only possible with excellent data management and modeling capabilities. If data is scattered across disparate systems and there isn’t a strategic plan in place, all of that data is wasted. With data management solutions, predictive analytics tools can build a robust customer profile, provide cross-sell and upsell opportunities or even forecast potential customer profitability. And with insurance data models, insurers can deliver on-demand services to their customers via the cloud, using the data-driven insights gathered from their data management platforms.

Identifying Potential Markets

Predictive analytics in insurance can help insurers identify and target potential markets. Data can reveal behavior patterns and common demographics and characteristics, so insurers know where to target their marketing efforts.

Because there are 3.2 billion people on social media around the world, these platforms have become increasingly important when it comes to identifying potential markets. The platforms also influenced customer service: about 60% of Americans say that social media has made it easier to obtain answers and resolve problems.

Gain a 360-Degree View of Customers

TechTarget defines the 360-degree view of a customer as “the idea that companies can get a complete view of customers by aggregating data from the various touch points that a customer may use to contact a company to purchase products and receive service and support.”

Using predictive analytics, insurers can quickly and accurately consolidate data and generate insights that paint a more complete picture of a customer. What are their buying habits? What is their risk profile? How apt are they to buy new or expanded coverage? Before predictive analytics, insurers could estimate or take guesses at these questions, but now they are able to accurately and effectively service customers, which ultimately results in happier customers and increased revenue.

See also: How Analytics Can Tame ‘Social Inflation’

Providing a Personalized Experience

Many consumers value a customized experience – even when it comes to shopping for insurance. Predictive analytics in insurance provides the capability to comb through IoT-enabled data to understand the needs, desires and advice of their customers.

More and more insurers will use predictive analytics to help forecast events and gain actionable insights into all aspects of their businesses. Doing so provides a competitive advantage that saves time, money and resources, while helping carriers more effectively plan for a future defined by change. After all, data is only a strategic asset when you can actually put it to work.

The 2020 Global Concerns Survey of insurance leaders by the International Insurance Society contains two major surprises. (I got an early look because ITL collaborated on this latest annual survey.)

The smaller surprise is that COVID-19 ranks only second among the most important issues the executives identified. I had expected that the pandemic would be the top concern, given that 2.4 million people have died worldwide, that economies have been devastated and that insurers face exposure, especially given the recent decision by the U.K. Supreme Court that business-interruption insurance should cover pandemic-related claims.

The bigger surprise is that, while innovation is the top concern, only 35% of respondents said they have an active, comprehensive plan -- meaning that two-thirds do not. A further 12% said their firms are preparing to implement a plan, but that still leaves more than half with little innovation activity.

"I believe the health crisis has actually highlighted the need for innovation." said Josh Landau, president of the IIS. "The pandemic has exposed areas of weakness in how companies connected with clients and staff and managed data."

Maybe I'm taking the lack of innovation planning personally, given how much we stress the need for digital transformation at Insurance Thought Leadership and how many pieces we've published that try to give companies a starting point for innovation efforts.

It's true that not all promises related to innovation have been borne out -- the peer-to-peer model didn't work, on-demand insurance has proved tricky, too many have claimed "transformation," etc. -- but I still see the industry as a good five to seven years into a wave of technology-driven innovation, and I'd think that just about every company would at least have a plan in place.

I suppose the good news is that those of you who have laid the groundwork for substantive innovation have stolen a march on those who have yet to get going. If you've begun reinventing and speeding up your claims processes, are already incorporating lots of unstructured data into your increasingly digital underwriting operations, are experimenting with chatbots, robotic process automation and other tools to take a whack at your operating costs, are exploring how to use technology to reimagine the customer experience from scratch... well, I predict you will be rewarded for your prescience.

In the meantime, we at ITL will redouble our efforts both to sell the industry on the need to emphasize innovation and to help people and companies get started.

Stay safe.

Paul

P.S. Here is a link to the press release on the study and to a white paper based on it. In addition to ITL, the Pacific Insurance Conference collaborated with IIS on the survey. All three entities are affiliates of The Institutes.

P.P.S. Here are the six articles I'd like to highlight from the past week:

4 Connectivity Trends to Watch in 2021

In a business defined by relationships, connecting well on a virtual basis will be more than a change — it will be a requirement.

The Intersection of IoT and Ecosystems

Insurers can build a sort of digital twin of the customer, then tailor their offerings and improve the customer experience.

Let’s Do More Than Create Faster Horses

COVID-19 has accelerated adoption of e-trading and smashed paradigms. There is an opening for something fundamentally new.

Closing the Protection Gap

With climate risk on the rise and exposure growing, parametric insurance can plug the gaps left by traditional insurance.

Why CX Must Trump Efficiency

Companies talk about improving customer experience but focus too much on saving money. Customer process automation does both.

CISOs, Risk Managers: Better Together

In most large firms, risk managers buy cyber insurance--but are rarely expert in network security and may not fully understand the risk profile.