David Kuhn, Insurance Solutions Director at Mendix
What is digital transformation? This is a term that countless CTO’s have battled with in every industry.
Essentially, it can be viewed as the process in which you capitalise on the power of technology to enhance your business model, acquire customers, and most importantly, create meaningful experiences. For insurance companies, digital transformation is also a response to new competitive threats, aging technology, evolving regulatory requirements, and emerging service-based product offerings. Today, digital transformation holds the key to a radical change in the industry, which will enable carriers to roll out products faster, respond to customer needs, and enable its employees to stay productive.
Changing dynamics within insurance
The insurance sector is under huge pressure to offer its customers the kind of services that they want. This includes a wide portfolio of products, a high level of personalisation and pricing transparency, combined with the need to know what factors are under consideration for the premiums being quoted to prospects. Unless an insurer is matching those expectations, there is nothing that will sway a prospect in the first place. But not reaching prospects isn’t the only challenge insurers face. Existing customers also expect this level of transparency. If it’s not met, they will switch providers without a second thought. Insurance has been ranked as the hardest to gain new customers so if current customers are also leaving, this is a serious challenge.
But this is only the tip of the iceberg. Insurance companies have always had a large amount of claims. This has been amplified by the current coronavirus pandemic, which has led to a surge in claims that clog insurers inboxes. These new claims, arrive in such volume that customers find themselves waiting for hours, if not days, to speak directly with someone who can explain how the outbreak affects their policy. If smaller claims are not automated, this forces the claims team to spend time on claims that do not require the human interaction. Agents are overwhelmed; and it has become clear that the industry needs to automate processes to mitigate loss to revenue growth and improve experience.
But that is not all. In addition, market leaders are coming head-to-head with new entrants that are planning to transform insurance in much the same way Uber has changed ride-hailing or Amazon has taken over ecommerce. The combination of data-driven technology features with insurance products, called “Insurtech” has become successful because the capability enables companies to diversifying their offerings. Some of them are even offering data services and moving away from traditional insurance methods. This is changing the rulebook for large carriers who are looking at their own strategies to keep existing customers, attract new ones and provide them with the experience they demand.
With this, it quickly becomes apparent that digital transformation isn’t something that the sector can afford to wait on – it needs to happen now. So why is it not commonplace yet?
Inhibitors to innovation
The first culprit in insurance’s slow rate of adoption of innovation is the large footprint of legacy systems. These rigid, cumbersome enterprise systems plague the insurance industry more than any other economic sector. Due to this, adopting a radical approach is rarely possible. Instead, insurance companies prefer to incorporate new solutions that integrate easily with core and legacy systems. This approach doesn’t continue to push the enterprise forward, it is just adding technical debt.
This is an area where large carriers can take a leaf from the “insuretech” book, where microservices architecture is the norm. This type of distributed computing enables IT professionals to update and deploy one application of function at a time, without any impact on the wider business. Luckily for large carriers, they don’t have to choose between their legacy infrastructure and this more agile take on operations management. Using the right kind of technology, they can combine both to offer the best level of service, regardless of their internal challenges.
Then there is the age-old issue that all industries face: a lack of appropriate resources. Too often, businesses have the willingness to innovate, but their limited talent pool prevents them from turning their ideas into real-world solutions. Whether it’s a limited number of developers in the IT team or a lack of communications between the divisions coming up with new services and improved solutions to their business challenges, important projects often end up being pushed back simply because the company doesn’t have the right people to deliver them.
Betting on low-code – it’s a no-brainer
So how do insurance companies get themselves out of this conundrum?
First, the industry needs to change the way it looks at digital transformation. Too often, insurers focus on speed when it comes to digital transformation. But that need for speed is not a goal in itself. Being able to process information faster and deliver a better service to customers at speed is simply an outcome of successful digital transformation. Instead of focusing on pace, insurers need to assess what the objectives of their digital transformation really is. Do they want to compete with new entrants? Do they want to arm their staff with modern data-driven tools to attract tech-savvy talent and find new customers? Do they want to automate manual or paper-based processes to increase the productivity of their staff?
Once they’ve identified their objective, they will be able implement the biggest mindset shift associated with digital transformation: that it is not the sole responsibility of the IT team, because the IT team is seldom on the frontlines when it comes to assessing the needs of customers and staff. Instead, insurers will benefit from greater collaboration between IT and the various business divisions. Insurance companies that are already embarking on this mindset change have an ace in the hole: low-code, a technology that enables employees who have little to no technical experience to turn their ideas into real-world applications. This is a tremendous benefit when it comes to experimenting with ideas that could have a significant digital impact on the business. Paired with traditional software engineers, these teams can challenge market differentiation at a pace envied by others. By empowering employees across the whole business with tools to collaborate on software development, insurers can tap into huge creative potential to turn ideas into applications that support the business’ long-term ambitions.
Crucially, the real problem isn’t that there is a lack of digital skills in the insurance sector; what we truly lack is activating digital mindsets across all employees. Today, every graduate coming out of university is tech-savvy and has the technical ability to code. They only need to be given the right tools in order to significantly contribute to the business.
This also helps ease the burden on the IT team, which often starts working on projects without full visibility of the implications for the business and any governance issues. For an industry that is wary of risks and keen to mitigate them, this may come as a surprise. Fortunately, with low-code, this problem can be eradicated. To ensure the highest level of transparency, low-code is a way of self-document everything IT is working on, providing a holistic view of every project within the business. This means that compliance with regulation becomes a whole lot easier, especially in an industry where changes occur frequently, and audits are commonplace.
The insurance industry is already embracing digital transformation – it just needs the right tools and mindset to ensure it empowers all employees to participate in this major change for the industry.
AI: CUSTOMER FACING EMPLOYEES’ BEST FRIEND IN THE FINANCIAL SERVICES INDUSTRY
By Ryan Lester, Senior Director, Customer Experience Technologies at LogMeIn
We’ve all heard the old saying “money talks.” Well when it comes to customer loyalty and retention, good customer experience talks much louder, with 30% of customers leaving a brand and never returning due to a bad experience.
The truth is, there are a lot of companies with similar products and services, but that doesn’t mean that differentiation is impossible. So, what’s the solution? For financial services, large and small, customer experience is becoming the key competitive differentiator and the best way to deliver an impactful experience is to empower customer-facing employees to do their best work. Artificial intelligence (AI) is enabling these employees to create remarkably better customer experiences, resulting in customer loyalty, advocacy, and overall growth.
For financial institutions that have been considering new strategies for improving the quality and efficiency of their customer experience, here are a few ways AI can enable them to deliver the “human factor” that good customer experience demands whilst ensuring customer facing employees can provide a more positive experience for customers.
Increase employee productivity
How much of employees’ time is spent searching for answers to questions? Do they ever have to put customers on hold or even step away to get additional help? AI helps provide front-line employees real-time guidance so they can spend less time looking for information and more time solving problems. An AI-powered chatbot, for example, can be listening in the background of a conversation helping point employees to the right data, solutions, and processes to resolve customer issues faster than ever before.
Deliver a consistent customer experience
When banking customers engage with their financial institutions, they measure the speed and accuracy of the service through two criteria. First, how quickly can the system access their account and deliver the correct information? Is it faster than a human could type it in and share it? And second, if they eventually do need to be connected to a live customer support agent, is their information captured and passed along accurately? AI technology takes those general queries off the customer support team’s plate, providing a quick, accurate, and effective response. If a query needs a more in-depth response, AI can hand it off to support staff to address.
Not only this but leveraging a centralised, AI-powered knowledge solution ensures every employee has access to the same, updated information, so no matter who the customer speaks to, they can be assured that employee responses are both consistent and accurate across the board.
Accelerating employee training and onboarding
Like any industry, employee turnover is inevitable and can be costly. But, not training new employees correctly or in a timely manner could be much more costly. When it comes to financial services there is a lot to learn, whether it is something simple like the process for checking an account balance to all the nuances associated with mortgage loans. AI can support on-the-job training by helping new employees answer questions confidently, correctly, and much quicker than they could before.
Improving employee satisfaction
Today’s banking customer has all kinds of new ideas about their banking experience. “The Amazon Effect” has successfully raised consumer expectations to the extent that a consistent, personal, and relevant experience is the new normal. As a customer, how many times have you been told “I’m sorry, I don’t know the answer?” Customers want solutions to their problems and employees want to be able to deliver those solutions as efficiently and effectively as possible. AI assisting in the background helps minimise those negative moments – making employees job easier, less stressful, and overall more enjoyable.
Identify knowledge gaps
Do you know all the questions employees are getting asked? Do you know what’s easily answered and what’s not? Real-time insights allow knowledge managers to keep up to date on frequently asked questions and gaps in current resources. This allows them to strategically improve or add content where needed.
Augmenting customer service
Whether talking with an AI chatbot or a personable customer service team member, the modern banking customer has high expectations for convenience, speed, and security. Which means that the technology you choose to deploy and how you deploy it is now just as important as who you hire and how you train them.
Today’s AI solutions won’t replace customer service agents or get in the way of the human factors that drive the customer experience. On the contrary, they augment it, allowing the business to do more without adding human resources. The higher the quality of a AI chatbot solution, the better it will be at taking the routine requests off the plate of customer service agents—giving them more time to provide a personalized and positive experience for customers.
BEFORE THE INK IS DRY: CORRECTING BIOMETRIC SPOOFING MYTHS
Eric Setterberg, System Design Engineer at Fingerprints
Biometric authentication is highly robust, and the latest solutions offer considerably greater security than their authentication predecessors: PINs and passwords.
But as biometrics moves into new areas such as payments and access control, privacy and security concerns are rising. Biometrics has long been subject to scrutiny, with many elaborate examples of people working to trick biometric sensors to crack devices in the media and online.
To ensure the continued adoption of biometrics, it is important to shine a light on the reality of biometric spoofing.
The Evolution of Biometric Solutions…
The first use of fingerprints as forensic evidence was in an Argentinean court case in the late 1800s. With the technology still in its infancy, this was done manually and by eye, comparing latent residual prints lifted from crime scenes to charts of inked fingerprints obtained from the suspects at arrest.
A few decades later, the FBI began collecting fingerprints of criminals and civilians. They also introduced the automated comparison of fingerprints by computers in the 1970s. These “traditional representations” have now been standardized by ISO and ANSI.
… and their Spoofs
The earliest and simplest of these matching devices were easy to spoof. Really, all you needed was a photocopy or a good image of a fingerprint to make a successful spoof.
But as biometrics moved to more advanced technology, the game for biometric ‘spoofers’ has changed and the task of crafting fake fingerprints is considerably more difficult.
The biggest boost for biometric security, however, came with its introduction into mobile phones.
How Mobile Changed the Game
Before the widespread integration of fingerprint sensors in smartphones, the technology underwent significant evolution. No operator wanted to use large biometric sensors in modern phone designs. Sensors had to become much smaller to reach the perfect price and design point for the mobile world, but this meant needing to capture data from a smaller surface area of the finger.
To maintain the security of these smaller sensors, algorithms evolved significantly in order to utilize a greater amount of data per unit area. These mobile-driven hardware and software changes resulted in the optimized image capture of modern touch sensors.
As a result, tricking these systems now requires a considerably higher level of detail to be reproduced correctly for a match to be successful, far beyond rudimentary gummi bear spoofs and photocopies…
Setting the Perfect Spoofing Scenario
Compromising fingerprint authentication via spoofing can still be done, even with all the technological advancements. However, it now requires considerable care, skill, money, and time. And to start, a good latent print…
To retrieve a latent print that’s high quality enough to work, you either need a willing volunteer to lend you their finger, or the commitment to stalk a victim until a viable fingerprint can be retrieved. Even with a decent latent print, modern spoofs then require advanced photoshop skills and/or a lab to successfully convert latent prints into effective moulds.
So – what about those articles boasting how easily they have hacked the latest smartphone device’s fingerprint sensor?
In fact, there are only two instances of fingerprint spoofing seen in the media nowadays: proof of concept and cooperative spoofs. Lay enthusiasts and media go through the effort of setting up a lab to create spoofs with latent fingerprints either from themselves or cooperative volunteers. Even the most successful of these take months of work, a highly skilled team, and the perfect scenario of circumstances.
Put simply, the effort required for spoofing modern fingerprint sensors cannot be applied at any scale. Each biometric spoof needs to go through the same laborious process and clinical conditions. So, if you can bring together a willing group of spoofing enthusiasts, tricking a biometric device could earn you fifteen minutes of fame on the internet, but it is likely to be conducive to a successful criminal business plan…
A “How” Without a “Why”
Spoofing biometrics remains technically possible, and there will always be those up to the challenge of trying to hack the latest technology. But the reality is that modern biometric solutions require more time, skill, and frankly, luck, to successfully spoof than ever before. Not to mention that tireless R&D work is continuously strengthening spoofing resistance. And, as use cases start to combine multiple biometric authenticators, such as combining fingerprints with face or iris to perform an authentication, spoofing will only become more complex.
By comparison, hacking PINs and passwords is considerably simpler and more scalable, making it far more lucrative. And, criminals generally take the path of least resistance.
For the average consumer, greater use of biometric authentication is not only a means of simplifying authentication, but dramatically improving the security of their devices, applications, and personal data. With PINs and passwords still the most common authentication method outside of mobile, it is imperative that the true security and advanced nature of modern biometric authentication solutions are understood.
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