Changes in consumer habits are of great interest to insurance organizations. Customers who prefer to handle business digitally would scoff at the prospect of having to meet in-person with a broker and fill out a long application by hand to start a policy. In fact, the number of digital-first clients is increasing with research showing that 75% of people who switched to digital channels for the first time during the pandemic indicate that they will continue to use them.
Additionally, the industry is expected to shift from its current state of “detect and repair” to a “predict and prevent” methodology, transforming every aspect of insurance in the process, according to a study on the impact of AI in insurance. As more carriers shift to this methodology, they will need to rethink their customer engagement and branding, product design, and more. For example, auto accidents will decrease through the use of vehicles with self-driving capabilities, and damages from a pipe bursting or an appliance leaking will be prevented or mitigated by IoT devices. This will advance as both insurers and insurance workers become proficient at using new tech.
Within the last year, many insurers adopted artificial intelligence and new technologies such as process mining, robotic process automation (RPA), low/no-code, and intelligent document processing (IDP). For those who are currently not using these technologies, many said they planned to introduce them in the near future: process mining (39%), RPA (42%), low/no-code (58%), and IDP (45%). The bottom line is that AI enabling technologies will be essential for insurers’ success. Here are the latest AI technologies explained and how they are changing digital habits in the industry.
Low/No-Code
Insurers need a framework that gives them the agility and speed to change, adapt and create applications quickly -– something that low-code platforms are ideal for.
The low-code approach enables insurers to build applications using simple ‘drag and drop’ components, versus the time it takes to write actual lines of code.
Low/no-code platforms are easy to use and fast to deploy, and they enable insurers to rapidly build applications to replace manual processes that are often done via spreadsheets and through email, and also to connect and extend their core policy and claims systems, helping them to create a technology ecosystem that can increase process efficiency, ultimately driving a better customer experience.
Process Intelligence
Automating policy and claims processes that impact customer experience is key for insurers. In fact, according to McKinsey, those who do so and compete for best-in-class customer experience generate two to four times more growth in new business and about 30% higher profitability than firms with an inconsistent customer focus.
However, getting the automation right is the first major challenge. You can identify which workflows are best for digitization by taking a holistic look at your organization’s processes. Process intelligence can help prep insurers for automation by revealing a birds-eye view of how your processes are performing, enabling organizations to pinpoint workflows that offer the best opportunities for change. With process intelligence, you can see your processes operating in real time and discover where bottlenecks occur, where repetition happens, where data is missing, and where automation is working or not. Furthermore, it can tell insurers how much an exception is costing their business
Content Intelligence
Insurance is document-centric, and content intelligence enables your workers – both human and digital – to understand and create meaning from enterprise content. It is used in a workflow for driving better, faster decisions throughout the policy and claims lifecycles. Content is rich information that helps knowledge workers make decisions. When you read a document, you are not simply identifying data, you are understanding that document. Content intelligence delivers cognitive skills that the new digital workforce can harness to turn your unstructured content into structured, actionable information, making your digital workers smarter and your processes run more efficiently.
For example, with content intelligence capabilities, AI becomes a digital assistant that can read, understand, and interpret a document – such as an accident report or claim form – while an adjuster is engaged with the client. Infusing content intelligence capabilities into document-centric workflows enables insurers to understand claims in context, and therefore adjudicate claims more intelligently and provide quicker, more efficient customer service.
Natural Language Processing (NLP)
More and more insurance providers are embracing digital solutions for their pain points, including the growing adoption in the industry of NLP. The global NLP market is expected to be worth $35 billion by 2025. A form of AI, NLP can automatically read, understand, and derive meaning from text in several different contexts and is able to be trained to be knowledgeable in specific areas. In insurance, this is usually done by having NLP analyze a large volume of claims to create a database of knowledge then give insurers tools to accelerate decision-making, reduce costs, and avoid human errors.
Adjusters and claim handlers can use NLP during calls to capture a client’s speech and automatically fill out claims forms, making the claims process easier for everyone involved The technology can analyze both speech and text quicker than humans, so insurers only have to manually verify them once collected.
In short, NLP technologies can assist insurers to reduce costs, increase efficiency, and help them adapt to a new, evolving market.
Machine Learning (ML)
Machine learning not only augments policy and claims processing but can also automate the entire process for more simple tasks, understanding the richness of content as part of a workflow while still doing the data extraction and validation where needed. It can transform documents, even unstructured ones such as emails or invoices, into actionable and valuable information that can be further leveraged to improve processing speed and accuracy.
It’s also playing an increasingly important role in responding to the complexity of customers’ experiences, aiming to create easy, seamless engagements throughout their journeys, from onboarding and underwriting to claims and renewals.
McKinsey predicts that by 2030 more than half of claims activities will be replaced by automation. Roles that focus on repetitive work and manual processes will cease to exist in their present form. Technologies like low/no-code, process and content intelligence, ML, and NLP will change not only customer interactions but impact internal operations as the insurance industry continues to evolve. And as McKinsey warns, only those carriers who ‘adopt to opportunities from disruptive technologies’ will thrive in the insurance industry in 2030.