Deep learning (DL) tools like convolutional neural networks which contain millions of simulated neurons structured in layers enable artificial intelligence (AI) to imitate the learning, reasoning, perception and problem solving of the human brain.
This technological change is revolutionizing every dimension of the insurance industry. While insurers, suppliers, insurance brokers and consumers are getting better at implementing DL and AI tools for the improvement of reasoning and productivity, cost minimization and the enhancement of the customer experience, this technological shift will be even faster.
In this blog post, we are going to share with you four aspects insurers need to focus on and how they can get prepared so as to get the most out of this tech-driven transformation.
Table of contents
- Four AI aspects impacting the insurance sector
- How health insurers can prepare for the rapid AI-related shifts
Four AI aspects impacting the insurance sector
1. Data abundance from connected devices
The number of connected consumer devices will drastically rise in the near future. In accordance with World Economic Forum, the number will reach one trillion by 2025.
In addition to smartphones, smart watches, home assistants, fitness trackers and cars, examples of new growing connected device categories include medical devices, eyewear and clothing. Plenty of data generated by these devices will make insurers and insurance brokers gain a deeper understanding of their clients.
As a consequence, they can come up with new insurance product categories, more customized pricing and more real-time service delivery.
2. Rise of Physical Robotics
The innovation in the robotics field will keep on transforming how humans interact with everything around them. 3-D printing (also known as additive manufacturing) will take manufacturing and commercial insurance products of the future to the next level.
3-D printed buildings and 3-D printed medical devices will be more common. Therefore, insurers will need to evaluate how this innovation affects risk assessments.
Besides, optimized surgical robots among other innovations will become feasible in the coming years. Health insurers and health insurance brokers will have to be well-informed about the way the rise of robotics in daily life will change risk pools, alter client expectations and pave the way for new products and channels.
3. Data ecosystems and open source
Due to the ubiquity of data, there will be open source protocols which helps ascertain data can be shared and used across industries.
For instance, wearable data such as one from medical devices or fitness trackers could be directly shared with health insurance providers. The data could also be made available through Apple, Amazon, Google and a range of different consumer device manufacturers.
4. Enhancements in Cognitive Technologies
The use cases of convolutional neural networks and other DL technologies will be extended to other applications beyond image, unstructured text processing and voice.
These cognitive technologies will serve as tools to process complex data created by “active” health insurance products attached to the behavior and activities of an individual or a client.
Thanks to the rising adoption of these technologies, health insurance companies will be able to access to models that are consistently learning and adapting to the world around them.
This will help health insurers come up with new product categories and while adapting to changes in risks or behaviors in real time.
How health insurers can prepare for the rapid AI-related shifts
1. Get educated on AI-related technologies and trends
Although it may seem these tech-driven changes involve only employees in the IT department, directors in the company board and customer relationship management teams should also take the time and resources to really understand these AI-related technologies.
For instance, health insurers are unlikely to know much from limited-scale Internet of Things (IoT) pilot projects in different parts of the business.
It is advisable that pilots and proof-of-concept (POC) projects be designed to test not only the way a technology works but also the level of success the health insurer might executing in a specific role within a data- or IoT-based ecosystem.
2. Develop and start implementation of a coherent strategic plan
Health insurance providers need to determine how to use technology to enhance their business strategy based on the insights from AI involvements.
The senior leadership team’s long-term strategic plan will require a multiyear transformation that touches operations, talent, and technology.
Some health insurers are already beginning to take innovative approaches such as starting their own venture-capital arms, acquiring promising insurtech companies, and forging partnerships with leading academic institutions.
Insurers should develop a perspective on areas they want to invest in to meet or beat the market and what strategic approach—for example, forming a new entity or building in-house strategic capabilities—is best suited for their organization.
This plan should address all four dimensions involved in any large-scale, analytics-based initiative—everything from data to people to culture. The plan should outline a road map of AI-based pilots and POCs and detail which parts of the organization will require investments in skill building or focused change management.
Most important, a detailed schedule of milestones and checkpoints is essential to allow the organization to determine, on a regular basis, how the plan should be modified to address any shifts in the evolution of AI technologies and significant changes or disruptions within the industry.
Beyond being able to understand and implement AI technologies, insurers also need to develop strategic responses to coming macrolevel changes.
As many lines shift toward a “predict and prevent” methodology, health insurers will need to rethink their customer engagement and branding, product design, and core earnings.
Auto accidents will be reduced through use of vehicles with self-driving capabilities, in-home flooding will be prevented by IoT devices, buildings will be reprinted after a natural disaster, and lives will be saved and extended by improved healthcare.
Likewise, vehicles will still break down, natural disasters will continue to devastate coastal regions, and individuals will require effective medical care and support when a loved one passes.
As these changes take root, profit pools will shift, new types and lines of products will emerge, and how consumers interact with their insurers will change substantially.
All of these efforts can produce a coherent analytics and technology strategy that addresses all aspects of the business, with a keen eye on both value creation and differentiation.
3. Create and execute a comprehensive data strategy
Data is fast becoming one of the most—if not the most—valuable asset for any organization. The insurance industry is no different: how health insurers identify, quantify, place, and manage risk is all predicated on the volume and quality of data they acquire during a policy’s life cycle.
Most AI technologies will perform best when they have a high volume of data from a variety of sources. As such, health insurers must develop a well-structured and actionable strategy with regard to both internal and external data.
Internal data will need to be organized in ways that enable and support the agile development of new analytics insights and capabilities. With external data, health insurers must focus on securing access to data that enriches and complements their internal data sets.
The real challenge will be gaining access in a cost-efficient way. As the external data ecosystem continues to expand, it will likely remain highly fragmented, making it quite difficult to identify high-quality data at a reasonable cost.
Overall, data strategy will need to include a variety of ways to obtain and secure access to external data, as well as ways to combine this data with internal sources.
Health insurers should be prepared to have a multifaceted procurement strategy that could include the direct acquisition of data assets and providers, licensing of data sources, use of data APIs, and partnerships with data brokers.
4. Have the right talent and technology infrastructure
In augmented chess, average players enabled by AI tend to do better than expert chess players enabled by the same AI. The underlying reason for this counterintuitive outcome depends on whether the individual interacting with AI embraces, trusts, and understands the supporting technology.
To ensure that every part of the organization views advanced analytics as a must-have capability, health insurers must make measured but sustained investments in people. The insurance organization of the future will require talent with the right mindsets and skills.
The next generation of successful frontline insurance workers will be in increasingly high demand and must possess a unique mix of being technologically adept, creative, and willing to work at something that will not be a static process but rather a mix of semiautomated and machine-supported tasks that continually evolve.
Generating value from the AI use cases of the future will require health insurers to integrate skills, technology, and insights from around the organization to deliver unique, holistic customer experiences.
Doing so will require a conscious culture shift for most health insurers that will rely on buy-in and leadership from the executive suite. Developing an aggressive strategy to attract, cultivate, and retain a variety of workers with critical skill sets will be essential to keep pace.
These roles will include data engineers, data scientists, technologists, cloud computing specialists, and experience designers.
To retain knowledge while also ensuring the business has the new skills and capabilities necessary to compete, many organizations will design and implement reskilling programs.
As a last component of developing the new workforce, organizations will identify external resources and partners to augment in-house capabilities that will help health insurers secure the needed support for business evolution and execution.
The IT architecture of the future will also be radically different from today’s. Health insurers should start making targeted investments to enable the migration to a more future-forward technology stack that can support a two-speed IT architecture.
On the whole, rapid advances in technologies in the next decade will lead to disruptive changes in the insurance industry.
The winners in AI-based insurance will be health insurers and health insurance brokers that use new technologies to create innovative products, harness cognitive learning insights from new data sources, streamline processes and lower costs, and exceed customer expectations for individualization and dynamic adaptation.
Most important, health insurers that adopt a mindset focused on creating opportunities from disruptive technologies—instead of viewing them as a threat to their current business—will thrive in the insurance industry in near future.