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The pace of technological innovation has never been quicker. That’s a very good thing, but it can also be intimidating simply because of how many tech options there are out there for every situation nowadays. That’s why in many ways, the art of technology planning is just as important as the gear itself. If you’re at any of these four crossroads in life, consider planning an upgrade to your technology.


  1. If Starting a Business 

Modern businesses need sophisticated infrastructure to function, from a session border controller for IP networks to entire logistical chains. The issue is that having the basics covered isn’t enough to scale your company in the long term. Investing in business process automation software is something that more entrepreneurs are doing all the time. Customer relationship management software can act as a digital Rolodex and keep track of customer status. Chatbots can serve as a low-cost augmentation to human customer service. Even more promising is the power of business analytics software to make performance forecasts, keeping owners in the know about their potential. Learn which of these many options might fit your plans.


  1. If Continuing Your Education

Distance learning via communications apps like Skype became popular by necessity during 2020, but it’s always been a good option for people who want to learn but need flexibility. That being said, if you are continuing your education, whether online or in-person, you might want to take this surprising advice: go low tech. Studies show that students learn better from print textbooks than from screens. It appears to be due to two causes: speed and intentionality. People read slower from print than from digital text, which aids comprehension. Books are also actual objects you can hold, which aids focus. The bottom line is that mind and machine have to work together for learning to happen, so don’t be afraid to go offline when you can.


  1. If Concerned About Online Safety

Paranoia about the dangers of online financial transactions and identity theft is largely justified. Research by the Aite Group revealed that 47% of Americans reported being identity theft victims last year. The solution is to stay current with your digital defenses. If your device sends you an update notification, install the update. These usually contain important patches to security holes in the software. Make sure to install antivirus software on your devices as well, especially ones used for banking, shopping and business. A firewall is a good investment too since they help to head off email-based malware attacks. Most importantly, do your research. Knowing the threats is the first step to finding the tools you need to counter them.


  1. If You’re Becoming Environmentally Conscious

There may be no more important reason to invest in technology than safeguarding the future of our planet. Not too long ago, the ideas of technological progress and ecological stewardship were seen as polar opposites. That’s no longer true. In 2017, the solar industry beat government cost projections, with utility-scale production hitting $0.06 per kilowatt-hour. Photovoltaics are also incredibly versatile, able to power commercial or residential properties or be installed on specific devices.

Solar energy is, of course, not the only sustainable technology you should consider investing in. Rain barrels, for instance, can save your water bill and take pressure off the grid. Look for the federal Energy Star program label on appliances to make sure you’re getting something energy efficient. Home energy efficiency is another place where automation is taking center stage. Home energy management technology like energy use monitors and programmable thermostats can make the process of going green much simpler, often allowing control of your home power use right from a smartphone app.

The question of what technology to apply to enhance your lifestyle may seem like a complicated one, but just remember that everything starts with a plan. Before you shop around, learn your own needs and remember: You own the gadgets, they don’t own you.



Augmented automated underwriting and the evolution of the life insurance market



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




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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