Driving AI-led growth in Insurance & Healthcare

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According to a recent McKinsey’s Industry Digitization Maturity Index, pharmaceutical and healthcare remained at the bottom of a list of industries ranked on technological adoption. Still, at the same time, venture funding in digital health has increased each year by an average of 30%. Within the overall HealthTech market, funding estimates rose to $28Bn in 2020, including leading providers such as Verily, Oscar, and Bright Health

Still, the world has to move to further digitization.  McKinsey expects that 25% of the insurance industry will be fully automated by 2025.

COVID-19 has made its presence felt across the healthcare sector and, in particular, health insurance, with claims rising and insurance providers struggling to manage customer relations with reduced workforces. However, out of this chaos has emerged a renewed interest in automation. 

Lemonade Inc., IPOed in July 2020, has today a valuation of $9Bn. Since its inception, it has been using AI-fueled chatbots to handle claims and sign-up policyholders, a move many veteran insurance companies like Geico and Allstate have also been quick to employ. Like Youse in Latin America and Ergo’s Nexible in Europe, others have used a similar approach digitizing the entire insurance engagement. Going one step further, a venture I met recently as part of my evaluation of the Global AI ecosystem includes Artificial. Artificial’s mission is to make insurance frictionless within the commercial insurance space – from quote, bind, issuance. The company helps providers generate digital contracts for their commercial insurance customers using a machine-learning algorithm to calculate risk, optimize profit, accelerate contract bind, transparency, and reduce operating costs for managing each contract. 

That’s not all. From fraud prevention to customer service, AI has been quietly transforming both insurance and healthcare. While many of these applications have been focused on internal operations, they have completely changed how health insurance companies interact with their customers to deliver an optimal experience. The focus is on quick, personalized interactions that feel natural and organic, despite their digital underpinnings.

Competition is stiff. The surest way for legacy market players to survive is to be keenly aware of newly available ecosystems and adapt to compete with digitized entrants. The kinds of innovative customer journeys that drive real growth can be achieved by leveraging AI and other digital technologies, ensuring digital integration across systems, and adopting appropriate operating models. 

1: It begins with customer data

The explosion of data collected by wearables and sensors enables organizations across sectors to develop AI-led algorithms to understand their customers better, profile them, and segment them more accurately to offer more customized offers. 

As Trevor Maynard, Head of Innovation at Lloyd’s Lab shares:

I think that one of the most exciting developments to come in the next decade is that we will have this incredible depth of knowledge about the world around us.

The data is vast, but it means little if it can’t correctly and quickly be interpreted. Interpreting that data is where artificial intelligence comes in. Algorithms can help healthcare providers and insurance companies make sense of the enormous amount of information generated by their customers, informing decisions on policy premiums and servicing preferences to claim settlement. 

The same data can be used to generate highly personalized friction-free interactions and solutions. By tailoring product offerings against particular customer segments, insurance companies can improve their NPS scores, drive customer satisfaction and, ultimately, generate more revenue. The need to securely store, process, utilize and render all this new customer data can be mee through various technology components: from cloud computing environments, the simple mobile-first platform, robotic automation to blockchain or digital twin technologies.

New entrants helping the sector range from cargo insurance startup Parsyl uses the internet of things (IoT) to let shipping providers know if a product has been damaged before delivery. SME-focused InsurTechs such as Layr, Slice Labs, Next Insurance, Tapoly use artificial intelligence and machine learning to help small businesses find the right personalized and flexible plans and make sure they are serviced when needed.

There have already been several AI applications deployed through a variety of use cases, and the great thing is that we are continuously learning about those new use-cases that can define patterns to ensure that every application is not only regulatory compliant but also ethical. 

In the healthcare industry, we have already seen insurance providers such as John Hancock collaborate with Fitbit and Vitality to incentivize policyholders to become more active and make healthy lifestyle and nutrition decisions and, as such, gain access to special rates on insurance premiums. Many health insurance companies offer discounts on premiums based on a customer’s daily habits, tracked via smartphone or wearable. The data collected is non-intrusive, and enrollment is entirely optional.  

2: It follows with combining use-cases with impact-driven applications of AI

With the combined powers of big data and artificial intelligence at work, health providers and insurers can ensure a faster, smoother, and more satisfying customer experience every time. 

As a practice area, AI has already attracted over 13,000 ventures, which raised over $230Bn over ten years. 

Here are a few applications of artificial intelligence in health insurance across different sectors:

  • Risk-modelling: Assessing lifestyle factors within a specific customer segment, adding medical history while taking appropriate steps to mitigate can save both money and lives. Consequently, the deployment of a proper risk management framework should become a priority for any health insurance provider. AI can automate risk management using its ability to look for customer data patterns, thereby improving customer experience down the road. For instance, Sight Diagnostics developed a platform for blood analysis and infectious disease diagnostics based on its computer vision technology in the healthcare space. Its platform is built on sample preparation, biological staining, machine-vision algorithms, and clinical instrumentation to analyze the data and provide diagnostic solutions suitable for point-of-care use. In the past, many health insurers relied on a claims-based risk-adjusted models to calculate risk scores and medical and pharmacy claims information to predict health care costs, which were built to forecast the risk of populations, but not at an individual level. These models give a fairly decent estimation of population risk but are unsatisfactory for individual risk. Innovaccer is a healthcare data company able to identify high-risk patients to estimate the future cost of their care based on past medical history, clinical and socioeconomic data, and a host of other factors. Their cutting-edge AI techniques and advanced algorithms are instrumental parts in the transformation to value-based care. 
  • Pricing: Accurately pricing new customers’ insurance policies is challenging, particularly when the world asks for more options and flexibility. The situation becomes more complicated when a policyholder or patient suffers from pre-existing health conditions or has a complicated medical history. Well known Paris-based InsuTech, Akur8, uses a proprietary algorithm to help insurance providers charge fair rates for their policies. Companies retain complete control over their pricing models while automating the implementation of these models through AI. That way, insurance companies can remain competitive and price-efficient while also meeting local regulatory requirements.
  • Underwriting: In the insurance industry, a lot depends upon each underwriter’s decision. Unfortunately, human bias creeps into those decisions no matter how hard we try. AI can apply filters and models to organize the data that human underwriters ultimately review, making the process less cumbersome. In the future, AI may replace aspects of the human element while augmenting humans to ensure that they focus on what matters, ensuring that decisions are based on fast data access while learning from previous experience. Both UIPath and BluePrism have made significant strides to remove error-prone repetitive activities from underwriting processes.
  • Distribution and sales: By mapping the entire customer journey from start to finish and using behavioral analytics to identify patterns, insurance providers can create more lucrative product offerings through data. Sophisticated buyer ‘personas’ can be used to guide decision making and optimize marketing strategies. The same logic applied internally allows businesses to evaluate agents better and identify leaders. In insurance, those capabilities have often been delivered from more advanced multi-sided marketplaces and comparison sites. 
  • Customer service: Some companies utilize chatbots for customer service. Some well-known smart enterprises within the insurance space include Spixii, Rozie.ai, and Enterprise Bot. However, now we can take customer service to the next level above chatbots with digital humans. In 2014, IPSoft released Amelia, a fully digital customer service assistant. Unlike your typical chatbot, Amelia is a virtual assistant, complete with her facial model based on actor Lauren Hayes. Amelia uses artificial intelligence to understand customer grievances and recommend possible solutions. Using so-called “digital humans” could substantially improve customer service by reducing wait times and cutting extra costs. 
  • Claims processing: Over the last few years, companies have found various ways to integrate computer vision, predictive analytics, and text mining to automate claims processing. Tractable has done very well since its launch in 2014. The company uses computer vision to analyze accident images and estimate repair costs for vehicular insurance companies in real-time. For the past six years, the team has built one of the most extensive databases to support motor claims management problems and the provision of speedy global solutions. 
  • Fraud prevention: Artificial intelligence identifies patterns of deception in a variety of processes, including fraud. The AI also learns from previous experiences to get better and better at flagging potential fraud by combining various transactional patterns. While the input from claim handlers is crucial, artificial intelligence and machine learning automate significant portions of the overall engagement, making the real-time fraud detection component nearly seamless. Shift Technology is a very well-known and respected solution focused on embedding seamless fraud detection within customer experiences and engagements. 

3: It ends with shaping a new AI-led ecosystem: Six vital elements

To ensure a smooth transition towards delivering an ecosystem of AI capabilities, health insurance providers must consider a series of most relevant design elements.

  1. Individual data points like sensors, wearables, and smart devices must connect to each other via the internet of things and to us via the internet of people. A robust network with good connectivity is essential to maintaining a smart ecosystem.
  2. The data collected from individual sensors helps paint a virtual image of the real world for machine learning technologies. All of this information is analyzed via algorithms to develop useful business insights.
  3. Algorithms and devices use data to make independent decisions and aid human employees to improve their productivity. This process helps decentralize the process of decision-making and delegate less critical work to machines.
  4. Decisions made by machine learning algorithms happen in real-time, thus reducing waiting periods and improving customer experience
  5. Services are now offered via the internet, reducing in-person contact. Businesses can operate without the need for physical offices, which cuts down on infrastructural costs.
  6. Machines offer infinite elasticity, allowing smart factories to upgrade or replace existing systems by changing individual modules instead of undergoing massive restructuring. 

The way forward 

With the increased appearance of digitized players in healthcare and the insurance markets, it is now more vital than ever for incumbents to adapt their strategies, operations, and business models to the changing digital environment. By integrating high-quality artificial intelligence into their workflows, healthcare insurance companies can reduce wait times, improve cost-efficiency, ensure better customer experiences, and make better use of their resources. 

It is a challenging time, and the innovative process is also demanding. Careful attention and industry knowledge are required to ensure a smooth transition to an automated system. However, insurance providers who invest in automation and artificial intelligence will reap the rewards of desirable value propositions, enhanced customer service, and lucrative profit margins for years to come. 

 

About Dr. Andrée Bates

Pioneer entrepreneur with blended expertise in Artificial Intelligence (AI) and Pharma/Healthcare industry. Dr. Bates founded Eularis in 2003 to apply mathematics to commercial pharmaceutical challenges. She quickly moved into using big data and sophisticated artificial intelligence (AI) to do this, fueling dramatic improvements in financial results through custom, targeted AI solutions. Dr. Bates has led Artificial Intelligence-powered programs for numerous top-tier pharmaceutical companies in diverse areas such as clinical trials, medical affairs, and sales and marketing, which drove tangible financial results for her clients. She has authored many articles in peer-reviewed journals and industry reports. She has been a guest speaker for over 500 conferences and many pharma and healthcare companies and a lecturer in three university MBA programs (INSEAD Business School, St Josephs’ University, and Fordham University). Amelia recently profiled her as a thought leader in AI in its Women in AI Initiative.

If you’d like to connect with Andrée, don’t hesitate to contact her at Eularis. Dr. Andrée Bates is supporting our AI growth agenda at Alchemy.

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