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.
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:
- 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.
- 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.
- 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.
- 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!
WHY DIGITAL TRANSFORMATION IN FINANCIAL SERVICES IS ABOUT CULTURE FIRST, TECH SECOND
Stuart Templeton, Head of UK at Slack
In today’s world, there’s no such thing as a ‘non-tech fin’. Every financial services company needs to consider itself a fintech in order to bring about the innovation, speed, and transparency that customers expect, and that’s why most are pumping significant investment into their digital transformation efforts.
Part of the challenge faced by traditional incumbent banks is that they rely on legacy core systems that stifle the speed of change. These core systems were not built in an API first era. The good news of course is that the obligations of PSD2 and open banking have gone some way to facilitate future innovation.
While legacy banking platforms do continue to present a technical challenge, the human one can be even greater. Traditional institutions are often faced with the prospect of rebuilding their culture from scratch in the pursuit of becoming digital-first. Like many industries, the fundamental challenge is one of coordination: the creation and maintenance of alignment over time.
Couple this with the fact that the expectations of today’s workforce are changing, then companies in the industry have a real job on their hands. A growing percentage are digital natives, and millenials – who greatly value trust and transparency – make up the largest proportion of the workforce today. So how have businesses in the industry historically ingrained culture, and how does this need to change?
Old ways of working – Team A, and Team B
Traditionally, the culture within large financial organisations has been separated by two distinct teams: operations, and tech. They are driven by seemingly opposing forces – one by GANTT charts and lofty business goals, the other by agile software delivery and customer obsession. Often, the two don’t even speak the same language, let alone collaborate and share ideas. Of course there are digital projects, but they aren’t the embodiment of the business, and often tech teams find themselves battling to get buy-in from internal stakeholders who are somewhat removed from those that drive innovation.
Part of the problem is even the notion of having digital transformation projects – there is no such thing in today’s environment – as digital is an overarching movement, and financial services institutions must think of themselves as ‘digital factories’ in order to see a marked change. It is no longer enough to deliver tech updates both internally and externally once every few months, with speed diminished by layers of bureaucracy.
What needs to happen, then, is that these two business segments need to find a way to blend that helps the old incumbents forget their binary ideas of teamship from time gone by and instead let them come together to become one unit. Flattening the established hierarchy so that workers from across all lines of the business can communicate, share ideas and identify problems in real-time is, after all, the key to addressing the transformation gap. They need to think on their feet and iterate as they go: it’s agile thinking, but permeating outside of just the software delivery cycle.
Eating the elephant – one bite at a time
The solution, in theory, is relatively simple: companies need to break open the silos of information created by technologies like email and ensure anyone within a business has access to the knowledge and skills they need to make their projects a success. But of course, in practicality, this can present a seemingly insurmountable task.
Using technology to create an agile and transparent working environment that fosters collaboration is key for many financial services organisations that want to see real tangible results from their investments. Digital natives such as TransferWise and Starling Bank are getting this right by prioritising a decentralised business model, one that empowers collaborative working and knowledge sharing that in turn has a positive impact on employee satisfaction and retention.
They do this through collaboration hubs that provide a rich, permanent, searchable record of knowledge for everyone in the organisation.
Looking ahead: Team ‘us’
Predictions are very difficult, but in five years’ time we can expect to see a greatly altered perception of the financial services industry. We can expect that digital communications tools will continue to play an integral role in the evolution of their workforce culture, helping to bring the right people together internally within the business, as well as strengthening relationships externally with partners and customers alike.
Ultimately, in order to keep learning and improving, banks need to ask questions of themselves as competition and customer demand becomes more fierce: “Why are we doing this?” “What’s the benefit here, and who are we considering in the pursuit of this goal?”
To answer these things, a culture of collaboration and openness is key – underpinned, of course, by the tools that empower it.
DISPELLING BIOMETRIC MYTHS AND MISCONCEPTIONS
By Lina Andolf-Orup, Head of Marketing at Fingerprints
Gangsters cutting off enemies’ fingers to access secret locations and spies lifting fingerprints from martini glasses – the imagination of the entertainment world has been running wild ever since biometrics entered the scene.
Couple that with the limitations of some early biometric solutions from fifteen years ago, still anchored in the minds of many consumers, and you have the perfect recipe for an apprehensive and uncertain public.
Thawing lukewarm attitudes with a biometric touch
The biometrics industry has made great strides in the last few years – something particularly true for smartphones. Fingerprint authentication has replaced PINs and passwords as the most popular way to authenticate on mobile, with 70% of shipped smartphones now featuring biometrics.
And it doesn’t end there. Many adjacent markets are now eager to benefit from the secure and convenient authentication solutions that biometrics offer. Take the payments industry, for example, where biometrics payment cards are currently gathering real momentum.
However, some consumers are still uneasy about accepting biometrics. A recent study found that 56% of US and EU consumers are concerned about the switch to biometrics as it’s not enough understood to be trusted.
Although attitudes are shifting for the better, stats like this demonstrate there is still some work to do to disprove common biometric myths and showcase just how smart today’s solutions really are.
Dispel, adopt, repeat
The evolution in consumer biometrics in the last two decades has been phenomenal. And today’s solutions are far more advanced and safe than many may think.
To help bring an end to the myths, let’s expose some of the most common misconceptions around biometrics.
Myth: Biometric data is stored as images in easy-to-hack databases.
A leading myth about biometrics is that when a fingerprint is registered to a device, it is stored as an image of the actual fingerprint. This image can then be stolen and used across applications. In reality, the biometric data is stored as a template in binary code – put simply, encrypted 0s and 1s. Storing a mathematical representation rather than an image makes hacking considerably more challenging. In most consumer applications, this template is also not stored in a cloud-based location, its securely hosted in hardware on the device itself for example in the smartphone, in the payment card. Thus, it stays privately with its owner.
Myth: Fingerprints can be easily replicated to ‘trick’ devices.
The internet is full of articles and videos that claim it is possible to use materials from cello tape to gummy bears to craft fingerprint spoofs and access biometric systems. Although there may have been a time where gummy bear spoofing was the go-to party trick, todays’ consumer biometric authentication solutions have too many technological defences, such as improved image quality and matching algorithms, to simply ‘trick’ devices. Plus, on top this, the criminal needs to have access to the person’s device where this fingerprint is enrolled e.g. smartphone, payment card, before he/she notices and blocks it. This is not scalable nor common, in comparison to gaining access to someone’s PIN code or skimming a contactless card.
Myth: Physical change will prohibit access to my device.
Although our irises don’t change as we age, our fingerprints can and our faces will. Does that mean we have to update our biometric devices every few months to capture these changes? Not quite! Unless there are drastic, sudden changes, the ‘self-learning’ algorithms in modern-day biometric systems are able to keep up with our developing looks.
Who you gonna call? Mythbusters!
These are just some of the common biometric myths and misunderstandings perpetuating in consumer mindsets. Thankfully, though, while we’re working hard to rid the world of the myths, belief in the value of biometrics is only expected to grow. But as solutions expand and diversify, the myth-busting fight will continue.
Fingerprints has been a leader of innovation in biometrics for the last two decades. We’re proud of the expertise and R&D we’ve been able to pour into our biometrics solutions to deliver stronger security and a better user-experience. To learn more about the most common biometric misconceptions and the modern-day technology that allows us to dispel them, download our eBook here.
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