These Are the Disruptive Technologies in Insurance

These Are the Disruptive Technologies in Insurance

Gunnar Brennekåsa

Gunnar Brennekåsa

It’s not easy to do business in a time of tumultuous technological-driven change. One thing is for sure: Insurers that fail to embrace a digital mindset, risk missing out on the $1.6 trillion of value according to the Work Ahead report that next-generation insurance is set to create in the coming years. McKinsey estimates there are now 1,500 InsurTechs globally thriving in this new landscape.

Among the current insurance tech trends, or InsurTech/InsureTech, that traditional insurance companies can’t afford to ignore, are the following:  

Blockchain
Blockchain technology is set to overturn the insurance industry, according to analysts CB Insights. By leveraging blockchain, insurers have the potential to dramatically reduce operating costs by automating the manual tasks involved in requesting, exchanging and entering data in areas such as underwriting, claims and reinsurance. Automating these manual tasks on a blockchain platform will also speed processing, improve data quality, reduce fraud and provide real-time transparency into the status of transactions for all involved. 

What do insurance professionals themselves think of blockchain? We asked 526 of them to find out (hint: 86% said it would be either important or very important, including 54% who said it would fundamentally transform the industry). Also check out how blockchain can transform life insurance processes, help insurance brokers, and learn how MetLife applied blockchain to solve a health insurance challenge.

Automation and Robotics
In an environment characterized by low interest rates, market overcapacity, tougher competition and growing regulations, insurers are increasingly looking to automation as the answer. For many, robotic process automation (RPA) has appeared to be the best bet for cutting costs quickly. And there are some serious advantages, e.g., with chatbots (explore our global assessment of 100 business chatbots to learn the key elements to incorporate into these systems).

One would think that in a data-driven industry, with high-volume, repetitive manual processes, RPA would be the ideal solution. Unfortunately, some processes need a more refined makeover than that. Both life and annuity (L&A) and property and casualty (P&C) insurers seeking the benefits of automation need to develop a holistic, customer-centric approach to RPA – moving to IPA (intelligent process automation). This interview with Ben Bengtsson, Cognizant’s global leader for Insurance, describes how IPA help insurers get closer to customers.

Over the next few years, RPA and more advanced cognitive technologies will be infused into a broad array of business processes. For example, if ML is added to a bot, the software will continually improve at performing a task. Guidewire’s predictive analytics tool uses both RPA and ML to assess claims in real time, flagging unexpectedly large or suspicious submissions, fast-tracking small claims and managing workflow. Amelia, IPSoft’s virtual agent, is used at insurers such as MetLife and Credit Suisse to combine ML with natural language processing (NLP) to make decisions based on real-time conversations and suggest ways she can improve her performance.

To get started, learn how to develop an effective automation strategy in insurance and check out how others are utilizing automation to handle claims data and improve quality assurance

Big Data and Analytics
Big data analytics enables the collection, processing, and analysis of more detailed and actionable information from the customers, which allows for highly personalized services. It has also opened the door to a growing group of digital natives and InsurTech companies.

Today, the advent of artificial intelligence (AI) is increasing the importance of data across the industry. AI is widely recognized for its potential to bring greater efficiency and innovation to the entire insurance lifecycle, from customer acquisition to claims processing. But effective AI depends on large amounts of sound, timely data. AI is key to competitiveness, and data is key to AI.

However, most mainstream insurers struggle to use data effectively. Our recent research found that about three-quarters of insurers have low levels of digital maturity, and are pursuing only limited digital initiatives or taking a wait-and-see approach to the digital technologies needed to leverage data. Legacy systems, siloed data, and growing volumes and varieties of data make it difficult to manage data effectively and use it to generate improved business results.

What to do then? Read more about how to tame data and the seven data architecture design principles. You can also see how others have utilized data to improve business; a global reinsurance company that uses data science to inform policy underwriting, an insurer that proactively protects customer relations, and another insurer that combats fraud through data analysis.

Artificial Intelligence (AI)
While some major insurance companies are investing aggressively in AI, most insurers are moving slowly, unsure how best to deploy these technologies. In our 2018 AI survey, only 51% of insurance executives said that AI technologies were extremely or very important to their company’s success today, which was lower than for any other industry.

However, making the transition to an AI future is no longer optional; insurers need to pick up the pace of investment (learn more in the report The Insurance AI Imperative). AI technologies – including machine learning (ML), neural networks, natural language processing (NLP) and computer vision – can handle an ever-expanding range of tasks more quickly and accurately than humans, while freeing employees to focus on more complex and higher-value activities. For example:

  • Zurich Insurance Group has partnered with the Swedish InsurTech Greater Than to allow it to analyze a potential customer’s individual driving data compared to a set of reference profiles created from more than a decade’s-worth of collected data, allowing the company to customize the premium based on the individual customer’s driving behavior.
  • Haven Life is using ML applied to third-party data such as prescription and driving records to offer real-time underwriting, which allows customers to buy life insurance online in just minutes without a medical exam.
  • AI will allow the processing of most personal and small business claims to be automated, substantially reducing operating costs. For example, U.S. insurers Allstate and Farmers use image recognition software, or computer vision, to settle auto claims without the need for an adjustor visit.

Internet of Things (IoT)
Gartner forecasts that 14.2 billion connected things will be in use in 2019, and that the total will reach 25 billion by 2021, producing immense volume of data. Smart homes, connected cars, smartwatches and other wearables all represent the future of InsurTech.

These connected things are capable of collecting, storing and transmitting to intermediaries and insurers vast quantities of data, like how a policyholder drives their car, cares for their health or manages their home. The IoT is useful in risk management and the verification of claims and simplification of claims processing and its applications are boundless.

Vitality is one insurer that is starting to capitalize on this trend: it is offering health and life insurance packages that provide consumers with wearables to track their physical activity, with rewards available to those who meet certain targets. 

To lean more, read the whitepaper Key strategies for commercial insurers: Optimizing IoT and also learn how this insurance carrier, among other things, used IoT devices to automate underwriting and claims adjustment.

How should incumbent insurers navigate in this era then? How can they keep up with ever-changing, digitally driven consumer demands, disruptive technologies and insurgent competitors? 

We believe digital transformation should be a strategic priority for every insurance business, where an agile IT model that incorporates as-a-service, cloud-based and asset-light approaches is the most proven (if not only) way to move forward. Not only will this more automated and simplified approach eventually reduce costs, but it will also ultimately reduce errors, improve claims and enliven an aging insurance industry. 

Learn more about Cognizant’s insurance practice