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4 WAYS AI IS RESHAPING THE INSURANCE INDUSTRY

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INSURANCE INDUSTRY

Karlyn is a writer who specializes in the technology and insurance spaces

 

The technological revolution is changing everything around us, from the way we communicate to the way we purchase goods and services. It’s even changing the face of the insurance industry, by helping us get better, faster, more accurate coverage.

One of the biggest technological innovations in the insurance world today is artificial intelligence. While insurance startups are taking more and more advantage of artificial intelligence each day, this technology was actually created in the 1950s.

Today, AI is becoming an important tool in the insurance sector to help with risk management. Below, we walk through what artificial intelligence is and how it’s helping the insurance industry improve their processes.

 

What is Artificial Intelligence?

Artificial intelligence is technology that helps computers to think rationally and solve problems similar to humans. As computers can hold more information now than ever before, critical thinking becomes easier to teach machines how to do. Today, “big data” processes and stores more information than any one person ever could.

Karlyn

Machine learning and deep learning are two of the biggest sectors in artificial intelligence today. Machine learning allows computers to identify and analyze continuous trends, which in turn helps them better predict outcomes. A car insurance company could use machine learning to predict both driving patterns and outcomes for specific customers or customer bases.

Deep learning, on the other hand, teaches computers to lead by example. Training computers to perform tasks utilizing artificial neural networks allows computers to complete tasks that humans would normally have to do, which can cut down on time spent on administrative tasks.

 

Artificial Intelligence and the Insurance Industry

Since AI aims to make more trusted and accurate decisions, free from human error, many industries are utilizing the technology in big ways. The insurance sector in particular is harnessing the power of AI to stand out from the competition and revolutionize the way consumers purchase insurance.

You can learn about some of the ways the insurance industry is using AI below:

  1. Improving the Speed of the Claims Process
    If you’ve ever filed an insurance claim, you know how much time it can take from start to finish. Many customers dread having to contact an agent and walk through the dozens of questions needed in order to complete the claim, but AI hopes to change this process by speeding it up and making it more accurate. Instant responses via chat boxes allow customers to get information directly after an accident.
  2. Preventing Fraud and Blocking Hacking
    According to the FBI, approximately $40 billion is stolen from insurance companies through fraud each year. These dollars lost impact both business efficiency and consumer costs. Companies that utilize artificial intelligence can identify and track irregular behaviors to prevent hacks and other fraud before it even occurs.
  3. Adding Personalization to Solutions
    AI also allows insurance companies to personalize their solutions, since no two accidents or incidents are ever the same. Taking a personalized approach allows companies to tailor their services from person-to-person, which can help save them costs and improve customer experience. Through a simple AI application over the phone, for example, an insurance company could get permission to track someone’s driving and thus use that data to adjust their rate. If they are a safer driver, their accident risk is lower, so the insurance company could provide them with a better rate.
  4. Offering 24/7 Accessibility for Customers
    One of the best features artificial intelligence offers is 24/7 access without the need for a 24/7 staff. Companies can save on staffing while also providing around-the-clock value to their consumers. This is especially important given the liability aspect of the insurance industry, when accidents can happen anytime and people need access to information fast. Rather than having to pick up the phone and get an agent on the line, customers can use a chatbox to help them through the process.

Insurance companies can maximize their efficiency by utilizing artificial intelligence. Not only does AI help make insurance safer from hacking and fraud, it also provides more accurate and reliable data for claims processing. All of these features help insurance companies save big. Further, customers feel safer and more protected.

To learn more about how AI is transforming insurance, and the startups that are helping to lead the movement, check out the infographic below!

 

Banking

Augmented automated underwriting and the evolution of the life insurance market

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By Alby van Wyk, Chief Commercial Officer at Munich Re Automation Solutions

 

It’s almost inevitable. Spend your working life identifying, analysing, quantifying and ascribing monetary value to risk, and you’re likely to have a fairly strong aversion to it. Or more accurately, an aversion to undertaking new endeavours with inadequately understood consequences. The insurance industry is, on any number of levels, the very definition of risk-averse.

And yet, for all the commentary suggesting otherwise, insurance still has an appetite for innovation. If the insurtech sector is any indication, then an interest in and requirement for new solutions is being recognised and slowly addressed.

Declan O’Neill

It may not employ the language of disruption that runs through the wider fintech market, it may be short a few unicorns and unable to boast some of the record-breaking funding rounds, but a quiet tech evolution has been building in insurance nonetheless. Hence the advent of automated underwriting facilitated by more advanced algorithms and data analysis.

Where insurtech does overlap with its more vocal fintech counterparts is in the greater use of artificial intelligence (AI) and machine learning to solve age-old problems around data analysis and interpretation.

It’s about five years or so since AI first became a topic of conversation in insurance. Since then, despite the intensity of the debate, it has often felt like a reality that is always just over the horizon – a destination that kept moving even as more and more efforts were directed towards it.

But recent research suggests that the journeys made so far have not been in vain. We are at a point where embracement of AI is about to step up a gear. The global value of insurance premiums underwritten by AI have reached an estimated $1.3 billion this year, as stated by Juniper Research; but they are expected to top $20 billion in the next five years. As a destination, it is closer and more attainable than ever before.

However, AI is not an island. Its promise of $2.3 billion in global cost savings to be achieved through greater efficiencies and automation of resource-intensive tasks will not be achieved in isolation.

AI remains part of a more complex ecosystem of data gathering and analysis. It can apply new technologies to get the best out of the already established and still-emerging data sources that feature in underwriting offices around the world. It emphatically does not require these existing investments to be ripped out, replaced or downgraded.

It is more helpful therefore to see AI as the differentiating factor in the latest generation of insurance IT: augmented automated underwriting, or AAU for short.

AAU gives underwriters the ability to spot patterns and connections that are, frankly, either invisible to the human eye or which take normal, human-assisted processes unfeasible amounts of time and resource to identify.

Whereas earlier generations of automation were able to pick up the low-hanging fruit of insurance markets – the individuals whose driving history fit into clearly delineated boxes, for example – AAU can take into account all of the rich complexity of the human experience. It can spot the nuances and individualities that populate the life market, for example, and translate those into accurate policies.

That’s good news for both underwriters and their customers. AAU can significantly reduce the need for separate medicals, repeated questions, lengthy decision-making processes, and drastically increase the speed at which a potential insurer can get a quote and cover – while continually improving the way risk is calculated and managed.

It can make sure the decision-making process remains in the hands of underwriters rather than IT departments, enabling them to set and update the rules and parameters as befits their preferred business model. It consequently makes advanced, complex and precise decision-making available to a broader range of underwriting businesses – which is good for those businesses, good for customers and ultimately good for the entire industry.

AAU – augmented automated underwriting – is an example of the realisation of AI’s promise. As such, it’s set to become one of the key talking points and disruptive technologies of the insurance industry. And this time, AAU is both a journey and destination that all progressive insurance organisations need to be considering for their future operations.

 

 

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Scaling securely in the automation-first era

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By Brandon Traffanstedt, Sr. Director, Field Technology Office at CyberArk

 

Robotic process automation (RPA) has been one of the key technologies underpinning digital transformation and, since it first appeared on the market a few years ago, the market has grown substantially. Now expected to reach $11 billion by 2027, RPA helps organisations achieve the efficiency, accuracy and speed necessary to thrive.

By successfully supplementing rather than replacing human resources, RPA is empowering workers to use their experience and capabilities in a more engaging and beneficial way, rather than focusing on manual and time-consuming processes. For example, in the financial services industry, RPA bots are helping to do everything from streamlining manual underwriting processes and reducing fraudulent activity through to account monitoring and assisting with new customer onboarding. While this leads to numerous benefits for workers and employers, organisations need to be aware that RPA comes hand-in-hand with specific security considerations.

As with other new and powerful technological initiatives, RPA projects need to be approached with cyber security as necessary component. Doing so will allow organisations to deliver enhanced digital experiences both quickly and safely.

 

Brandon Traffanstedt

RPA advancement

Multiple industries have embraced RPA as a means of solving business problems. Yet, early implementations of RPA, namely semi-attended bots, necessitated human supervision, requiring a person to hit the ‘go’ button in order to accomplish a task and requiring the user’s digital identity to do so.

As organisations look to digitally advance however, ‘citizen developers’ or those who use low-code or no-code platforms to design their own automated processes have taken it upon themselves to push automation to the next level – entirely unattended robots.hese unattended robots though, require access to the same networks, systems, and applications as their human counterparts, including access to systems which require the highest level of privileged access. This access makes robot credentials and identities just as vulnerable to threat actors as those of human workers, and not effectively securing them provides opportunity for havoc.

The future of RPA then, has created a rift between security and automation teams. With security professionals demanding stricter measures and the latter struggling to implement them, many developers have been discouraged and ceased their creativity and innovation whichc is necessary to advanceing RPA technology. Those developers who have decided to continue in their pursuits and adopt non-approved RPA programmes however, have created gaps in their company’s cybersecurity.

 

Putting security first

Fortunately, there is a way to address security problems while still using secure unattended robots, allowing citizen developer innovation and without demanding additional work from the teams which organisations are wanting to free up. The solution is the automated and centralised management of RPA credentials.

All hard-coded privileged credentials are removed from robot scripts and replaced with an API call pointing to automatically rotated credentials maintained in a secure, centralised repository – rather than manually assigning, managing, and upgrading the credentials a bot needs to do its work. This ensures security mechanisms, such as multifactor authentication, password uniqueness and complexity requirements, and the suspension of privileged credentials are all consistently implemented.

It’s also good practice for security teams to ensure bots have their own unique identity credentials – similar to to limiting a human user’s access or rights to the bare minimum necessary for their work. This ensures non-repudiation and separation/segregation of duties, as well as limits access to the applications and databases bots need.

 

Liberating works and innovation

To truly unlock the citizen developer’s innovation and liberate workforces through RPA, organisations must adopt DevSecOps and bring automation and security together from the start. By engaging with security teams and professionals at an early stage, organisations will be able to effectively – and safely – scale the number of RPA bots in their organisation.

 

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