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How Artificial Intelligence Is Driving InsurTech

Posted by Tom Barbereau on June 2019

2018 was a good year for insurers, especially in countries like the U.S., where property and casualty (P&C) doubled net income. However, a key finding of a report from PwC on the insurance sector stated “CEOs continue to report that theirs is one of the most disrupted industries.” With Artificial Intelligence disrupting industries across all sectors, the technology is now setting course to revolutionize the insurance sector. 

The PwC report mentioned above describes an optimistic industry with great expectations across the sector in the coming years. This enthusiasm is due to the industry’s disruption as InsurTech takes hold, opening up unforeseen opportunities and new products.

As the industry evolves to take advantage of this disruption, it has set its sights on the use of Artificial Intelligence (AI) and other emerging technologies, such as IoT and Blockchain, to drive this vision forward. In fact, the insurance industry is becoming ever-automated and is more actively using AI to drive new use cases and gain a competitive edge.

What are the Pressing Issues Driving Insurance Transformation?

The digital transformation of the insurance industry has been pushed by three major drivers. These drivers were described in a recent EY survey. The drivers are creating a perfect storm, forcing the industry to use digital technologies to become more innovative and efficient. These drivers can be encapsulated as follows:

  • Optimize costs using technology (digital transformation). All industry sectors are feeling the long arm of digitization of products and processes. The insurance industry, where costs and risk reduction are crucial factors in competitiveness and efficiency, needs to find better ways to cut costs and improve customer reach.
  • Augment human distribution channels with digital and direct. EY found that providing customers with omnichannel communication, i.e. communications across multiple channels including, email, mobile and digital assistants, i.e. communications across multiple channels including, email, mobile and digital assistants, improved their experiences and streamlined interactions and transactions.
  • Expand product offerings for customers. Competitive edge is challenged by the entrance of new technologies, The market for Insurance technology (InsurTech), which includes AI, IoT and blockchain, is predicted by Technavio to grow by $15 billion USD at a CAGR of over 41% to 2023. Digitization of services and processes can allow an insurance company to create new products and offer personalization as never before, allowing them to capitalize on the space.

Insurers must adapt by using technology to meet the needs of these three core drivers; the insurance sector is in a great position to do so. Maturation of technologies such as big data analysis and AI has created market and product opportunities. You can see a lot of prime examples of this by looking at Technavio’s report which highlights the applications of AI in insurance. The report points out that “Al will prove to be beneficial for InsurTech firms. For instance, robotics can be used to automate many processes in InsurTech solutions.”

A report by Accenture on the digital transformation of the insurance sector shows that in the next 3 years, almost half of the insurers will be utilizing AI technologies to optimize processes, develop new business models, and improve old ones.

Before delving into the use of AI in the insurance sector, let’s take a look at the precursor to this, Robotic Process Automation.

Taking Small Steps: Robotic Process Automation

The initial foray into the use of digitally transformative technologies in the sector has been in the use of Robotic Process Automation (RPA). Automating processes has set the scene for more intelligent ways of performing tasks, AI being its next stop.

RPA is a well-established market in its own right, worth around $4 billion USD by 2025. Accenture identified a strong use case for the application of RPA to reduce costs and speed up processing. They found that using RPA software reduced processing costs by up to 80%. In addition, the return on investment (ROI) came in at around 3 months, and average handling times were reduced by 40%.

RPA is a type of robotic software used to replace repetitive human tasks. In the insurance sector, it’s been used to improve operational effectiveness, cut costs, and in doing so, creates a competitive edge. The typical use cases for RPA in an insurance setting include:

  • Automation of insurance sub-processes, such as data linking between spreadsheets across multiple systems, moving data from invoices to core systems, and data scraping from websites.
  • Underwriting and claims processing: processing data with speed and accuracy, automatic notification of loss adjusters, sending out assignments to claims handlers, consolidating disparate claim information.

However, RPA should not be confused with AI. Where RPA automates tasks, Artificial Intelligence-based solutions are designed to learn how to perform tasks better. AI uses data as a kind of training platform to adapt to new situations. It is often likened to human intelligence as some forms of AI are based on ‘neural networks,’ that mimic the way the human brain operates (on a simplified level). Artificial Intelligence also incorporates the subsets of machine learning and deep learning - each used for specific applications. Here’s a brief synopsis of different forms.

The adaptive intelligence of AI allows it to be applied to many different areas of insurance. It’s the application of AI to insurance use case models that will propel the industry into a new era.

Getting Smart About Insurance: AI in Insurance

The new wave of automation is smart. It uses AI to turn data into actions.

An earlier PwC report, found that in the insurance sector “61% are exploring the benefits of humans and machines working together”, while also “more than half of insurance CEOs are clear about how robotics and artificial intelligence can improve the customer experience.”

Solutions that use the power of AI and data are being used to digitally transform insurance for good. A brave new world of insurance is being directed by the use of AI-driven technologies. These technologies are used by the sector to improve customer experience, provide more accurate and speedy services, and innovate new and personalized products. Some of the areas that AI is being applied to are:

Insurance fraud prevention

Globally, Reinsurance Group of America (RGA) estimates that there are around 3-4% of insurance claims are fraudulent. RGA describes insurance fraud as the “perfect crime,” as there is little redress. In the U.S., insurance fraud is estimated to be around $80 billion per year. The RGA report also identified that in 2017, 22% of insurers were applying machine learning (a subset of AI) to capture fraudulent claims.

Machine learning automatically analyzes large data sets. In doing so, it checks multiple variables to identify anomalies quickly and accurately. In other words, machine learning algorithms can be used to spot trends in patterns within transactions that point to fraud. Some insurers applying this technique claim a 210% ROI by automating fraud analytics using an AI solution.

Smart assistants and chatbots

Intelligent voice-activated assistants like Amazon Echo, are paving the way for the use of smart assistants and chatbots in the insurance sector. Health insurance is seeing a trend in the use of intelligent chatbots, for example. Insurers Manulife offers Alexa Skills to allow customers to query account details and check benefits. Intelligent chatbots are also being applied to improve customer relations, identify relevant products, and speed up transactions. Servion predicts that by 2025, 95% of customer interactions will be via AI-driven interactions.

Claims settlements

Settling an insurance claim is a time-consuming and intensive process. This makes it a costly part of a customer transaction. AI applications, including ‘machine vision’ can be applied to the process of claim settlement. For example, AI solutions offer image processing associated with a claim, e.g. photos of a damaged car or evidence of home theft/damage, etc. The photos associated with the claim are uploaded via an app and the AI-driven software will analyze the images. The claim can then be processed in minutes and communication with the customer is fully-automated.

Behavioral premium pricing

Data is the lifeblood of AI as well as insurance. Wearables and other IoT device sensors, such as those available in connected cars, can be used to generate the data needed to process a claim or determine risk levels for insurance premiums. This innovation is providing real-time data needed to give more accurate information.

The result is the personalization of insurance. This is facilitated by the use of data analytics driven by AI; behavior rather than claims being the deciding factor on pricing premiums. In this context, AI is augmenting and creating new use cases for the IoT in the context of insurance. This is perhaps the most compelling use of AI in the insurance industry, allowing for new products to be built around the individual.

Smarter Insurance Futures

The insurance industry may be buoyant, but insurers should not stop looking for better ways to do business. The application of AI to insurance use cases offers new insights, seamless and speedy customer interactions, and novel products. In an age of digital transformation, keeping a competitive edge is a challenge.

Fortunately, InsurTech vendors are forging change and applying cutting-edge solutions based on AI to insurance challenges. In doing so, they are morphing labor-intensive and costly processes into a smooth, interactive customer experience, while cutting costs and reducing risk. This already reaps benefits for the industry, the scope of which is only held back by our imaginations.

Looking to Innovate at the Intersection of AI and InsurTech? 

At Next Big Thing AG, we support founders integrally in developing sustainable, data-driven business models that make use of blockchain, the Internet-of-Things and machine learning technologies. Our team of developers help you developing the innovative solutions of tomorrow while our experienced management executive team are mentoring you along the entire business cycle. 

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Tags: Articles, Machine Economy, Insurance, Artificial Intelligence