Tag Archives: chatbots

What’s After COVID for Call Center Reps?

When the coronavirus really started to bite at the start of 2020 and businesses and individuals were forced into lockdown, there was a collective holding of breath in the U.K. as we waited to see if the insurance industry could respond effectively.

On the whole, the industry did a superb job of shifting its call center operations from centralized offices to thousands of homes up and down the U.K. A few early hiccups aside, the industry’s tech stood up to the test and proved that we can work differently.

But what we have been doing for a year now is a temporary patch. The systems and business structures weren’t designed to operate like this on a permanent basis.

Negotiating the turn to digitization

Our current reliance on individual internet connections, the ambiance of various home environments and unreliable access to the policy, billing and claims systems mean that consistency and efficiency are a hope rather than a guaranteed deliverable for interactions with customers.

While remote working should result in vastly reduced real estate costs for most businesses, that shift has to be done in a way that doesn’t compromise on the customer experience or quality of conversation.

There is really only one way to provide a personal experience, delivered at scale but in a decentralized way: through the use of conversation process automation or, as it is commonly known, employing expert chatbots.

By using intelligent, effective and responsive chatbots, insurers can deliver the necessary consistency of service to an increasingly digital-first customer base while easing the pressure on remote (or office-based) call handlers. That will allow them to focus on the more complex or higher-value customer interactions that require less immediacy and less efficiency but a high-value human touch.     

Customer-facing process digitization requires automation

Of course, digitally triaging incoming customers is nothing new. It’s why webforms exist. They were designed to capture basic information, which is then fed automatically into the insurance system, creating an event for the call handler to progress.

But webforms lack one key element necessary to support call handlers in recreating the call center experience in a remote working world. They lack the ability to converse in real time with the user, to exchange valuable pieces of information.

Customers still want to have productive conversations, even in a digital-first world, and that is a want insurers will have to provide remotely. They could simply hire more call handlers, but it is logistically complicated while not being viable for the business — with every addition of a remote call handler, the insurer moves further and further away from the guarantee of a consistent customer experience. And more call handlers, of course, mean more cost.

See also: Lessons on Reaching Customers Remotely

With expert chatbots, the consistency of experience can be delivered on a consistent basis without necessarily recruiting more call handlers.

And rather than replace the human call handler, expert chatbots assist in a way that webforms can’t by creating a natural, unseen bridge between the digital and the human touch. Anything that frees call handlers for productive conversations has to be embraced. Using their time to gather basic, repetitive data is a waste of their expertise and a waste of the customer’s time. Call handlers will always be required to solve complex problems and queries that automation can’t solve.

Often, the leap of faith is a small step in the right direction

What we are talking about here is taking another leap of faith, the same leap of faith that insurers were forced to take in response to the coronavirus. But the opportunity facing insurers now is to take that leap before they are compelled to by market forces or consumer demand.

The industry has taken the first, bold step toward an entirely new way of working and servicing customers, and it deserves a huge amount of credit for that. But we are entering another breath-holding moment as we wait to see if insurance has learned the lessons of lockdown and is willing to take the next, natural step in this digital and automation revolution to secure the productivity that has escaped them for so long.

Beware the Dark Side of AI

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. 

Chatbot, Your Time Is Now!

The lasting impact of COVID‑19 on commerce and trading is an issue for the future. While old routines may quickly resume as restrictions lift, there may be lasting changes to the ways we get things done.

The pandemic showed the importance of remote access to get information and to conduct transactions differently. Customers became self-servers using automated solutions that replicated or replaced some face-to-face interactions.

It’s hard to imagine a lockdown without online and do-it-yourself services enabled by technology solutions. The experience we’ve had as an industry has helped businesses understand what tech solutions work well or less well. Meanwhile, one outcome is that newly enfranchised consumers may prefer to remain empowered. Chatbots have been around for a while, so could this be their moment? And if so, what does this technology offer and can more insurers benefit?

Spixii is a technology company providing this type of customer-facing, automated-insurance solution to life/health and P&C insurance companies. To find out more, I spoke with Spixii founder and CEO Renaud Million.

RC: How does a chatbot operate?

RM: A chatbot is essentially a software program with a conversational interface that is usable by either a voice or by typing using a keyboard. A chatbot works best when it has a defined goal and can guide a user toward reaching this target.

RC: What makes a chatbot “intelligent”?

RM: With a chatbot, and systems with AI solutions more generally, intelligence refers to the ability to achieve these goals. The goals are defined by the chatbot owner, and the machine’s ability to achieve them is based on anything from a simple set of rules to highly complex algorithms.

RC: What type of advanced analytics and conversation insights make a successful chatbot?

RM: Chatbots generate a lot of data, much more than traditional digital tools — such as web forms, which rarely capture the user interaction between screens separated by the “next” and “submit” buttons. The data generated by chatbots are related to the execution of the underlying process and how likely it is going to reach the defined goal. More granular data is generated for the conversation itself, such as where people are stuck, at what point they drop the conversation, on which questions people edit their answers, where more information might be needed and where questions are not clear.

RC: What are the prerequisites of an enterprise-ready chatbot?

RM: An organization just embarking on digital transformation starts with the desire to improve a single process, or even to create one from scratch. Once settled on a process, the chatbot needs to be integrated into middle- and back-office systems. This is a prerequisite for an enterprise-ready chatbot to deliver value. Capturing, validating and transmitting the data in a secure way to core insurance systems will deliver savings and efficiencies at enterprise level.

RC: Where in their processes can life and health insurers deploy chatbot technology effectively, and what is the business case for doing so?

RM: A chatbot can assist with many processes; for example, quote and buy, policy administration, submitting a claim or asking for a pre-authorization in a health product. The process of buying is complex and, as a result, often carried out over the phone. While these analogue conversations are great, they’re just not scalable. Online digital web forms are too rigid and lack the conversational aspect. Additionally, despite existing tools becoming less effective and the ever-increasing costs of expanding call-center capacity, the focus is always on the top line. This may explain why some insurers struggle with digital transformation by not prioritizing it in the short term. Chatbots are helping solve this conundrum from both a technical and regulatory perspective because they can be deployed rapidly and audited.

See also: Integrating Chatbots, Policy-Handling Apps

RC: Do you think people’s response of embracing remoteness during the pandemic furthers the argument for using chatbots?

RM: People were already accustomed to doing things by self-serving online. Pandemic restrictions simply accelerated this — across all industries. Remote working also forced more people to go online for their insurance needs. As more people travel less, the need to physically meet with an agent is disappearing. Consumers are trying first to see if they can do what they need online and then call an agent. On the other hand, while insurers want to do more and be more efficient, remote working doesn’t automatically equate with service resilience if a surge in demand occurs. Offering digital-first communication tools — such as a chatbot — can bring both efficiency and resiliency.

RC: What is the next technical development for your chatbot technology?

RM: We have already helped several companies integrate chatbot technologies to their quote and buy, policy administration and claims submission processes. We are now refining these for specific lines of business to help them to grow their portfolios. We also realize that business reporting is critically needed for various departments — ranging from IT, marketing and distribution to operations and claims — but the precise data needs vary for each one. So we built an automated reporting function to bring the relevant data to the correct operational area at the right time. We believe this helps individual units make better-informed decisions for the whole business. From a tech perspective, we aim to extend the front-end integration of our chatbot, including more channels and platforms, making the configuration of the chatbot even more accessible and friendly. Also, Spixii has achieved accredited ISO 27001 certification for information security, and our work has been recognized by analysts from Gartner, Forrester and Business Insider.

RC: Will you share some working examples?

RM: We have worked with Zurich Insurance group in the U.K. since 2018, and, together, we automated the first notice of loss for home and motor insurance, helping them to win the British Claims Awards in 2018 for best use of technology. We also worked on the quote and buy processes with both the U.K. Post Office on travel insurance and Bupa’s private medical insurance. To be honest, it is an honor to work on processes that bring a better customer experience and generate a positive impact on operations.

RC: Finally, what is the next step for chatbot technology in your opinion?

RM: Although adoption started some years back, many implementations are yet to come. A lot of companies recognized the operational limitations of call centers, but only a few companies recognized the limitation of web forms. The ones that did recognize these two points also understood that these two channels should be supported by a third one that keeps the conversational aspect and yet manages to codify it in a digital way. We see a strong appetite for serving the customer better with the digital experience they expect. Digital functions are gaining more authority within insurance companies.

Both forces should lead to more and more successful use cases for chatbots to support the digital transformation of insurance companies. From the technological perspective, chatbots are needed for growing more sophisticated in the analysis of data collected — with a particular focus on psychometric and customer behavior analysis — but also they need to build a stronger understanding of obligations and duties to keep data protected and anonymized, which is an intriguing challenge for this new wave of data collection.

You can find this article originally published on Genre.com.

Despite COVID, Tech Investment Continues

Insurers will continue to experiment with emerging technology in 2021, despite the challenges of 2020. When the COVID-19 pandemic hit, many insurers paused their 2020 innovation plans, emphasizing digital workflows and cost control at the expense of emerging technology pilots. Heading into 2021, technology priorities for many insurers, especially those in the property/casualty space, are similar to those of 2019.

The U.S. is still in the midst of the pandemic, and some insurers are anticipating lower premium revenues for the coming year. In spite of this, insurers are investing in technologies like artificial intelligence and big data, though some are narrowing the scope of their innovation efforts for the coming year.  

Understanding Emerging Technology Today

Insurers typically take a few main approaches to emerging technologies. Early adopters experiment with the technology, typically via a limited pilot. If the technology creates value, it’s moved into wider production. Insurers that have taken a “wait-and-see” approach may launch pilots of their own.

Novarica’s insights on insurers’ plans for emerging technology are drawn from our annual Research Council study, where CIOs from more than 100 insurers indicate their plans for new technologies in the coming year.

No insurer can test-drive every leading-edge technology at once, and every insurer’s priority is a result of its overall strategy and immediate pressures. Still, at a high level, several industry-wide trends are apparent:

There is big growth in RPA; chatbots continue to expand. More than half of all insurers have now deployed robotic process automation (RPA), compared with less than a quarter in 2018. Chatbots are less widely deployed but on a similar trajectory: from one in 10 in 2018 to one in four today.

AI and big data continue to receive significant investment. These technologies take time to mature, but it’s clear insurers believe in the value they can provide. More than one in five insurers have current or planned pilot programs in these areas for 2021.

Half of insurers have low-/no-code capabilities or pilots. These types of platforms are relatively new but have achieved substantial penetration in a short time. Early signs indicate they could become a durable tool for facilitating better collaboration between IT and business experts.

Despite continued tech investment, 2021 might be a more difficult year for innovation. Insurers’ technology priorities have generally reverted to the mean — more so for property/casualty than for life/annuity insurers — and technology budgets for 2021 are within historical norms. Still, some insurers are paring down pilot activity in less proven technologies, like wearables, to maintain their focus on areas like AI and big data. Technologies with substantial up-front costs, like telematics, may be harder to kick off in 2021. 

See also: Technology and the Agent of the Future

How Emerging Technology Grows

Emerging technologies have widely varying rates of experimentation, deployment and growth within the insurance sector. Their growth rates boil down to a few key related factors:

  • How easily the technology is understood.
  • How readily it can be deployed and integrated with existing processes.
  • How clearly the value it creates can be measured and communicated.

At one end of the spectrum are technologies like RPA and chatbots. These technologies create clear value, are readily added to existing processes and are relatively easy to deploy. As a result, insurers have adopted them rapidly.

Artificial intelligence and big data technologies require longer learning periods; sometimes, they require business processes to be completely reengineered. The technologies create value for insurers but have grown more slowly because they take time to understand and integrate.

Drones, the Internet of Things (IoT) and telematics can create new kinds of insurance products or collect new kinds of information. These can also create value, but their growth remains slow because developing these technologies may require orchestration across several functional areas, and they can be costly to ramp up.

On the far end of the spectrum are technologies like augmented and virtual reality, blockchain, smart assistants and wearables. Most of these technologies don’t yet have established use cases that demonstrate clear value, so it remains to be seen whether they will be adopted more widely.

Using Emerging Technology

One key insight from Novarica’s study is that technologies that integrate readily to existing processes can grow more rapidly than technologies that require new workflows to fully use. This observation comes with a few caveats for both insurers and technology vendors.

Insurers sometimes fall into the trap of “repaving the cowpath” — they adopt new technologies but integrate them into their existing (inefficient) business processes. Doing so means they can’t get maximum value from their investment. Ironically, it’s usually the shortcomings of legacy technology that have made these processes cumbersome in the first place.

It’s easy to understand the value that technology creates when it integrates with an existing process and can be measured with the same key performance indicators (KPIs). It’s much harder to create a new process enabled by new capabilities, train employees to execute it and demonstrate that the new way is better than the old way. Yet getting the most out of emerging technologies often requires rethinking how business might be done.

See also: 2021’s Key Technology Trends

For their part, vendors should focus on the value their products create and the problems they solve, aligning them to insurer needs. It’s not enough to use a new technology for its own sake, and using new tools sub-optimally may make them seem less effective. Vendors should coach their insurer clients through best practices and help them understand how their tools can ease, change or make obsolete existing processes.

At its core, insurance is a simple industry focused on connecting those exposed to risk to capital that can defray potential losses. At the center of that value chain are insurers, that continue to explore new technologies to better understand their risks, sell more and operate more efficiently. Even in uncertain times, insurers are innovating.

3 Must-Haves for a Self-Service Portal

Today, human support is steadily losing ground to self-service in the insurance industry. For one thing, clients have grown tech-savvy and self-reliant and are willing to solve issues on their own, without waiting to reach a live agent. What is more, as the pandemic interrupted the conventional face-to-face service and support delivery, even the most reluctant customers became favorable toward online channels. Against this backdrop, insurers are implementing out-of-the-box self-service portals or developing custom insurance software

Companies should prioritize the particular needs and expectations of their customer base rather than follow the examples of other self-service portals. Insurance customers, as shown by Accenture in its 2019 Global FS Consumer Study, do not feel comfortable resorting to self-service in every case. The majority would rely on digital channels for tasks like looking up information or submitting personal data. Yet, when it comes to complex financial decisions — purchasing a policy or changing the terms of a contract — over half of the respondents admitted they can’t do without human assistance. 

Given these customer behavior patterns, insurers need to invest in providing exhaustive information, features for handling non-critical issues and account management as self-service options, but refrain from trying to automate all customer interactions. Below, we explore the self-service features that suit the set tasks most.  

A knowledge base 

The idea of customer education meets skeptical attitudes from the majority of insurers. According to Deloitte, 33% of surveyed executives believe that clear product information is a decisive factor for new customers, yet only 16% see it helping retain customers. 

In fact, a detailed and consistent knowledge base is not only an essential self-service channel but also a powerful driver of customer satisfaction. Building a centralized repository of relevant insights, like policy comparisons, legal terms glossary, claims application guides and so on, you give customers an opportunity to find answers and solutions quickly and at any time. 

Through relevant and innovative content, a company can also reach a wider audience and build a reputation as a niche expert. What is more, by analyzing the knowledge base activity, insurers can discern customers’ common needs and challenges and come up with solutions.  

For such a knowledge base to prove authoritative and helpful, the content needs to be of high quality but clear and comprehensible to an average customer, free of complicated terms and industry jargon. What is more, the materials need to be reviewed and updated regularly to remain relevant in the face of your evolving service offer and changes in the insurance industry. Therefore, when choosing your knowledge base format, make certain you have sufficient resources to maintain it at a proper level. 

See also: Self-Service Portals Improve CX

AI chatbots

Conversational AI has taken the business world by storm, becoming a staple of customer relations strategy. What is more, customers have come to appreciate chatbots for their efficiency and increasingly prefer to seek their assistance first. These facts, coupled with the opportunity to cut customer service costs, make AI chatbots a self-servicing option worthy of adoption.  

Implemented in your insurance portal, chatbots can tirelessly handle numerous customer queries and come up with relevant advice in each case. Through simple message commands, users can ask the bot to describe or compare insurance plans, find policies matching certain criteria or help address any current insurance policy concern. Unlike human agents, the technology can provide answers and take actions in real time, driving customer satisfaction up. 

Beyond this, chatbots can be programmed to analyze a customer’s profile information and engagement history and supply personalized product and service recommendations or even craft bespoke insurance policies and quotes. 

Yet chatbots are not without limitations. They are not geared toward making independent decisions and can only perform actions defined by the algorithm. This means that complex issues and requests need to be escalated to human service representatives. Moreover, chatbots are still bad at gauging human emotions and expressing sentiment appropriate to the situation, which can unnerve an already distressed customer. 

Claims management

Traditionally, claims management is one of the most cumbersome and confusing journeys for the insured. The customer fills out forms, gathers a lot of paperwork and photo evidence and submits it all in person for the company to process and reach a conclusion. 

But the digital age has altered customers’ expectations in this regard. They want a simple, speedy and transparent process that can be handled remotely in real time. By integrating a claims management engine into your self-service portal, you can meet this demand. 

The solution should allow a customer to make the first notice of loss to the insurer and then fill out and submit the official claim together with all the necessary photo or video evidence. As the information is processed and checked for fraud, the damage is appraised and the settlement is offered, the policyholder has full visibility into the claim status without the need to contact company representatives.     

Inevitably, there can be complex claims that require the agent’s on-site damage assessment or the personal presence of the insured. But for many other cases where fully digital handling is possible, self-servicing offers customers the freedom to manage their claims anywhere, anytime and allows them to control the process. The solution proves beneficial to insurance companies, as well, as it frees agents’ time spent on customer communication and paperwork in favor of other tasks, while minimizing human errors in the submitted claims.   

See also: Time to Try Being an Entrepreneur?

Summing up: The balance is vital

Despite the extensive reliance on self-service, insurance customers are not yet ready to accept it as the only alternative. As long as there are people who appreciate human touch over convenience and speed, traditional customer support will remain in demand.

Therefore, a hybrid approach to customer service appears to be the most appropriate strategy for insurers. Smartly balancing self-service and human support features and ensuring intuitive access to them all, an insurance company can meet the shifting customer needs and offer an outstandingly rich and dynamic support experience.