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PREPARING FOR THE WORST: WHY CYBER INSURANCE IS NO LONGER A LUXURY

By Piers Wilson, Head of product management, Huntsman Security

 

In recent years we’ve seen a huge financial fallout for organisations that have suffered large-scale cyber attacks; from the £500,000 slapped on British Airways for the 380,000 compromised card payments of customers, to the possible $915m fine that Marriott may face following the enormous data breach last year. These repercussions are only likely to worsen as the volume and severity of attacks increases. For instance, the General Data Protection Regulation (GDPR)’s arrival last year means that companies now face fines of up to 4 percent of global revenues or €20 million, whichever is greater.

 

In light of these risks, cyber-insurance is emerging as a safety net offering businesses protection if the worst happens. Far from being a luxury, there is every possibility that cyber-insurance will soon become a necessity for any organisation storing personal data. In the same way that drivers are required by law to have motor insurance, businesses may be obliged to have measures in place to guarantee compensation for customers left at risk by any data breach.

 

Eligibility: Proof is Paramount

Unfortunately, as with motor insurance, even if cyber insurance becomes an obligation, getting insured may be difficult or expensive. Insurance companies will only provide policies to organisations that are insurable; either through low risk, or because they are prepared to pay significant premiums. To lower their premiums, organisations will have to prove they are a low risk by taking sufficient steps to protect their sensitive data. Just as home and contents insurers require policy holders to have locks on all the doors and windows, businesses must be able to demonstrate that they have the appropriate systems and processes in place to protect their data.

 

However, anyone who has taken out home insurance will testify that there’s a big difference in premium between having a simple lock on a door, and having multi-point locks and a burglar alarm. In an age of organised cybercrime, state-sponsored cyber-attacks and advanced cyber-threats, merely having anti-virus software and firewalls is unlikely to be enough. Organisations should therefore consider reinforcing their current defences and adopting a more progressive approach to cybersecurity; in turn encouraging insurers to offer more affordable policies.

 

Shaping your premium

As when taking out any insurance policy, the first thing organisations will need to do is establish the exact risk they face in order to determine their premium. This is critical for two reasons. First, a more accurate assessment will allow a more accurate, and ideally better-priced, premium. Second, by auditing their defences in this way, organisations will face less risk that their claims will be refused if the worst eventually happens. Much like a driver who states their car is always parked in a locked garage will have a hard time claiming if it’s stolen from the street outside their house, organisations that are found to have over-stated their security capabilities could be in for a nasty shock.

 

At its most basic, any risk assessment needs to consider the kind of data that is being stored, and what level of security it is defended by. Identifying where the most valuable data resides will help predict where attackers are most likely to strike, and to thereby assess whether current security measures are strong enough. As part of this, organisations should also consider whether appropriate access controls are in place. For example, there’s no need for a receptionist to have access to sensitive financial data, so their privileges should not extend to that information.

 

Organisations will also need to demonstrate their preparedness in the event of an attack. The faster an organisation can react, and the more it can minimise any potential damage, the lower its premiums will be. For instance, businesses must have the ability to monitor their systems for any suspicious behaviour that indicates data is being accessed or used in ways that it shouldn’t; whether that is by an employee or by an unknown party. This capability can prove particularly useful in identifying potential threats before real damage has been done, safeguarding company data and helping to bring down cyber-insurance premiums by reducing impacts. With attacks showing no signs of slowing down, these processes should be automated as much as possible, otherwise the potential savings will be offset by the fact that security teams are dealing with a blizzard of alarms, both false and all too real.

 

Given that cyber-risk is increasing continually, those that choose not to insure against it risk leaving themselves, and thereby their customers, vulnerable to potentially catastrophic consequences. Organisations must recognise that an ounce of prevention is always better than a pound of cure, and while an insurance policy provides an indispensable safety net, they must focus on doing all they can to avoid becoming a casualty in the first place.

 

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Technology

WHAT EVOLUTIONARY AI MEANS FOR FINANCIAL SERVICES

FINANCIAL SERVICES

by Babak Hodjat, VP of Evolutionary AI at Cognizant

 

Many banks and other financial services institutions (FIs) are beginning to recognise the benefits of AI-driven solutions as a way to get ahead in the market and challenge the competition. Amongst many other benefits, the technology enables organisations to offer hyper-personalised customer experience,  dramatically improve internal decision making, and drive operational efficiency. However, many businesses are struggling to move beyond the experimental phase and reach actual AI deployment. It is those organisations that are at risk of being left behind.

The financial world has already been transformed by AI, and this transformation is continuous. A new breed of AI, known as ‘evolutionary AI’ has begun to further accelerate innovation. It is capable of automatically designing itself with little need for explicit programming by humans – innovatively creating complex AI models, and optimising decisions considering multiple scenarios.

This technology is revolutionary for industries across the world, but in particular it is set to transform the financial services sector. Enabling businesses to spot novel strategies that would never have been identified by human data scientists, and, in turn, allowing companies to take full advantage of today’s massive data sets – evolutionary AI will soon be a vital tool in all FIs’ arsenals.

 

The nuts and bolts of evolutionary AI

Emerging technologies that enable AI algorithms to design themselves are allowing organisations to transcend human limitations. Evolutionary AI operates iteratively. Firstly, it randomly generates a set of potential solutions to form an initial population and assigns a score to each solution based on how well it performs relative to other solutions. In the second round, it retains the solutions that performed best, perhaps only 5% of the total, and recombines their components, sometimes “mutating” them to create a new population. This new population is then tested, and the process begins again. Over multiple generations, the appropriate components of the more successful solutions become increasingly prevalent in the population, and eventually a solution is discovered that yields the best outcomes.

 

Advantages and use cases

Compared to human design, evolutionary AI can be deployed far more quickly, avoids biases and preconceptions, and typically performs better. Furthermore, the chosen model will evolve and improve over time based on new data.

Evolutionary AI can be applied in a wide variety of areas at FIs. Some examples include designing quantitative trading strategies to maximise returns while minimising risk and loan underwriting. Rather than relying on human analysis, evolutionary AI solutions can quickly analyse all the combinations of relevant variables to create models that more accurately assess the risk of default by a potential borrower.

 

A recipe for success

In order to reap the benefits of the technology, FIs should focus on the following:

  • Responsible AI – Behave in ways that make customers and employees comfortable, i.e. not making decisions that are unethical or exhibit bias. Companies need to monitor them to ensure they continue to act appropriately, as they learn and evolve.
  • Viewing AI through a business lens – Having AI projects managed by cross-functional teams with business executives in the lead is a good place to start. Companies also need to look across their organisations to identify opportunities to generate concrete business value from AI — not only in reduced costs but also in boosting revenues by delivering enhanced customer experiences and through improved decision-making.
  • Enhance data management – AI applications depend on access to timely and accurate data, which is a challenge for many FIs that have fragmented data architectures with multiple legacy systems. Companies need to identify which types of data are required for each AI project and ensure they can be captured in an appropriate format.
  • Approach with speed and caution – AI projects need to be rolled out quickly, while at the same time be rigorously measured, so failures are terminated promptly while successes are moved into production.

The sophistication of AI technology is set to significantly improve over the coming years as it continues to design and test itself. As a result, it will become more critical to the productivity of FIs, and soon businesses will recognise it as a vital tool for consulting on important business decisions. It will not be long before humans and AI are working alongside each other, with robots handling routine tasks, enabling employees to focus on more complex and sensitive activities. Delivering more value together than either could on their own.

 

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Technology

6 EXAMPLES OF ARTIFICIAL INTELLIGENCE IN USE TODAY

ARTIFICIAL INTELLIGENCE

We’re probably not aware of the moment when artificial intelligence sneaked into our lives and became a part of our everyday existence.

Was it the first movie recommendation we got from Netflix? Or the item we’ve purchased using Amazon’s suggestions?

AI is now all around us, and it’s holding tremendous potential, with new application possibilities being discovered every day.

We’ve gathered six very practical examples of AI, to show just how widespread this technology is today, and how prevalent it is yet to become.

1.    Healthcare

The use of AI in healthcare is already bringing many benefits – at the beginning of the year, we’ve witnessed  AI outperforming six radiologists in reading mammograms and identifying breast cancer more accurately and quickly.  A computer algorithm can now analyze images in just a few seconds, significantly improving the speed of diagnosis.

The first AI-designed drug molecule, by Excienta, is currently being tested on humans. While it usually takes three to four years for traditional research to reach this stage, it just took 12 months for the algorithm to make it possible.

As for the current COVID-19 crisis, the Chinese technology giant Alibaba has recently developed an algorithm that can detect coronavirus in seconds, with 96% accuracy. The algorithm that analyzes CT images of patients’ chests is used by more than 100 healthcare facilities to distinguish the disease from other viral pneumonia cases.

2.    Virtual Personal Assistants

Alexa, Siri, Cortana, and Google Assistant are just some of the most notable examples of artificial intelligence we’re all familiar with.

We interact with our PAs regularly – ask them for directions, information about the weather and the news. They allow us to finish various tasks easily, without having to use our hands – we can stream podcasts, play music, make to-do lists, set alarms, schedule our meetings, or order pizza.

These voice assistants use machine learning technology and natural language processing so that they can get smarter and more capable of understanding voice queries. In other words, with the help of AI and its subsets, voice assistants learn from your previous searches and preferences and use all the information they collect to offer you better search results and service.

3.    Customer Service

Even if you’re still not interacting with your devices using your voice assistant, you’ve surely communicated with AI at least once, most probably in the form of a chatbot.

There is hardly any good online store that doesn’t offer at least some kind of AI-powered customer support.

The most common are conversational chatbots that are now able to answer 80% of most common customers’ queries in an accurate and timely manner, without any need for additional human intervention.

With data AI chatbots gather on the customers, they are now able to facilitate human-like interaction and personalize it more than their human counterparts.

Conversational AI algorithms can now give offers and recommendations that are more likely to fit customers’ needs and interests, boosting both their satisfaction and retailers’ revenue.

4.    Finance

The banking and finance sector has recognized the possible advantages of AI early on and is now successfully implementing the technology for various purposes.

The finance industry relies heavily on large amounts of data and accurate real-time information. With the use of AI, it’s now much easier to detect frauds, money-laundering, or any other suspicious behavior. Some of the financial advisors’ tasks can now be automated too, as  AI-powered advisors can quickly scan the market data, and predict the best portfolio or stock.

One of the best examples of how useful AI in the banking industry can be, is Erica, an AI employee of the National Bank of America. This digital financial assistant has already served over 7 million customers and handled over 50 million queries. Apart from managing many other different tasks, Erica helps customers with their transactions and budgeting, tracks their spending habits, monitors duplicate charges, and gives useful advice.

 

5.    Smart Vehicles and Delivery

Cars and drones are also shifting towards the use of AI.  Even though artificial intelligence is widely used in car manufacturing, its use in the automotive industry is most commonly related to the use of self-driving vehicles, that are leveraging machine learning and vision to find their way through the traffic safely.

Autox is, for example, currently testing their autonomous grocery delivery within San Jose. Their vehicles use AI software, real-time cameras, and sensors to navigate within a geofenced zone, with plans for gradual expansion.

Amazon and Walmart are already investing large amounts of money into drone delivery programs. Amazon’s goal for its Prime Air service is to create fully electric drones that can deliver packages lighter than 5 pounds, to their customers located within 15 miles, in less than 30 minutes.

6.    Smart Homes

One of the finest examples is Nest, the thermostat algorithm, which uses an intelligent machine learning process to learn about your behavior and the temperatures you like. It then anticipates and adjusts your home or your office to your temperature needs, at the same time saving significant energy resources.

Google acquired Nest back in 2014 for $3.2 billion and now aims to create a smart and helpful home. The tech giant is trying to connect devices such as thermostats, cameras, alarm systems, doorbells, and locks under the same roof, offering an easy to use smart home solution.

However, for this to work seamlessly, technological advancement in the field of IoT and 5G needs to be utilized. Near-zero latency is what allows for smart homes to be remotely controlled.

As you can see, AI is impacting and improving every aspect of our lives and our society. It will revolutionize the way we do different things, from driving our cars to receiving medical treatment. Although this technology is still in its infancy, it has already managed to disrupt the above-mentioned areas and offer us a sneak peek into the future.

 

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