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Now is the time for a transatlantic dialog on the risk of AI 

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Artificial intelligence is no longer the world’s darling; no longer the “15 trillion dollar baby.” Mounting evidence that AI applications can cause harm and pose risk to communities and citizens has lawmakers under pressure to come up with new regulatory guardrails.

While the US government is deliberating on how to regulate big tech, all eyes are on the unbeaten valedictorian of technology regulation: the European Commission. This past Wednesday, April 21, the Commission released wide-ranging proposed regulation that would govern the design, development, and deployment of AI systems. The proposal is the result of a tortuous path that involved the work of a high-level expert group (full disclosure: one of us was a member), a white paper, and a comprehensive impact assessment.

The proposal has already elicited both enthusiastic and critical comments and will certainly be amended by the European Parliament and the Council in the coming months, before becoming a final piece of legislation. It is, however, the first of its kind, and marks an important milestone. In particular, it sends a signal to regulators in the US that they will have to address AI as well, especially since the proposal underscores the need for AI risk assessment and accountability for both material and immaterial damage caused by AI — a major concern for both industry and society.

The main ideas

The proposed regulation identifies prohibited uses of AI (for example, using AI to manipulate human behavior to circumvent users’ free will, or allowing “social scoring” by governments), and specifies criteria for identifying “high-risk” AI systems, which can fall under eight areas: biometric identification, infrastructure management, education, employment, access to essential services (private and public, including public benefits), law enforcement, and migration and border control. Whether or not an AI system is classified as “high-risk” depends on its intended purpose and its modalities, not just the function it performs.

When an AI system is “high-risk,” it will need to undergo a pre-deployment conformity assessment and be registered in a to-be-established EU database.

The focus on transparency in the proposed regulation is laudable and will change industry practice. Specifically, the new regulations would emphasize thorough technical documentation and recording a technology’s intentions and assumptions.

But the strategy of pre-classifying risk has a blindspot. It leads the Commission to miss a crucial feature of AI-related risk: that it is pervasive, and it is emergent, often evolving in unpredictable ways after it has been developed and deployed. Imposing strict procedures on a subset of AI systems and checking them mostly while they are still “in the lab,” may not capture the evolution of risks emerging from the interaction between AI systems in the real world and the evolution of their behaviour over time. The Commission’s proposal contains provisions for post-market surveillance and monitoring, but these provisions appear weaker than the pre-deployment ones.

As it stands, the Commission’s proposal relies heavily on the development of algorithmic auditing practices by so-called “notified bodies” and in the private sector as a whole. Auditing practices, ideally, should be consistent across the markets and geographies where an AI system is deployed; it should also be oriented towards the main requirements of so-called “trustworthy AI,” and be grounded in principles of equity and justice.

The need for consistency across markets

The spotlight is now on US regulators, as well as industry leaders. If they aren’t able to promise consistent auditing in US markets as well, that will impact the whole AI ecosystem.

Instead of playing regulatory ping-pong across the pond, leaders on both sides of the Atlantic would benefit from initiating a research- and stakeholder-led dialog to create a transnational ecosystem focused on maximizing the impact of AI risk identification and mitigation approaches. At the moment, such a transnational approach is hindered by different cultural approaches to regulation, strong tech lobbying, lack of consensus on what constitutes AI risk assessments and AI auditing, and very different litigation systems.

All these barriers can be overcome, and we can reap the real benefits of AI, if the European Commission’s proposal is taken as a cue to harmonize approaches across borders for the maximum protection of citizens. This dialog should focus on equity and impact, outlining optimal procedures for effective risk and audit documentation, and identifying what is needed from governments, civil society, and higher education to build up and maintain a transnational ecosystem of AI risk assessment and auditing.

The benefits are obvious. Strong regulation would meet a strong technology research landscape. Rather than reconciling approaches after the fact, co-developing the regulatory approach from the outset and creating the preconditions for mutual learning would be far more effective. The renewed prospects for an enlightened transatlantic dialog on digital issues are a one-time opportunity to make this happen.

Mona Sloane is an Adjunct Professor at NYU’s Tandon School of Engineering and Senior Research Scientist at the NYU Center for Responsible AI.

Andrea Renda is Senior Research Fellow and Head of Global Governance, Regulation, Innovation & Digital Economy at the Centre for European Policy Studies.

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Source: https://venturebeat.com/2021/04/23/now-is-the-time-for-a-transatlantic-dialog-on-the-risk-of-ai/

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Longevity startup Gero AI has a mobile API for quantifying health changes

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Sensor data from smartphones and wearables can meaningfully predict an individual’s ‘biological age’ and resilience to stress, according to Gero AI.

The ‘longevity’ startup — which condenses its mission to the pithy goal of “hacking complex diseases and aging with Gero AI” — has developed an AI model to predict morbidity risk using ‘digital biomarkers’ that are based on identifying patterns in step-counter sensor data which tracks mobile users’ physical activity.

A simple measure of ‘steps’ isn’t nuanced enough on its own to predict individual health, is the contention. Gero’s AI has been trained on large amounts of biological data to spots patterns that can be linked to morbidity risk. It also measures how quickly a personal recovers from a biological stress — another biomarker that’s been linked to lifespan; i.e. the faster the body recovers from stress, the better the individual’s overall health prognosis.

A research paper Gero has had published in the peer-reviewed biomedical journal Aging explains how it trained deep neural networks to predict morbidity risk from mobile device sensor data — and was able to demonstrate that its biological age acceleration model was comparable to models based on blood test results.

Another paper, due to be published in the journal Nature Communications later this month, will go into detail on its device-derived measurement of biological resilience.

The Singapore-based startup, which has research roots in Russia — founded back in 2015 by a Russian scientist with a background in theoretical physics — has raised a total of $5 million in seed funding to date (in two tranches).

Backers come from both the biotech and the AI fields, per co-founder Peter Fedichev. Its investors include Belarus-based AI-focused early stage fund, Bulba Ventures (Yury Melnichek). On the pharma side, it has backing from some (unnamed) private individuals with links to Russian drug development firm, Valenta. (The pharma company itself is not an investor).

Fedichev is a theoretical physicist by training who, after his PhD and some ten years in academia, moved into biotech to work on molecular modelling and machine learning for drug discovery — where he got interested in the problem of ageing and decided to start the company.

As well as conducting its own biological research into longevity (studying mice and nematodes), it’s focused on developing an AI model for predicting the biological age and resilience to stress of humans — via sensor data captured by mobile devices.

“Health of course is much more than one number,” emphasizes Fedichev. “We should not have illusions about that. But if you are going to condense human health to one number then, for a lot of people, the biological age is the best number. It tells you — essentially — how toxic is your lifestyle… The more biological age you have relative to your chronological age years — that’s called biological acceleration — the more are your chances to get chronic disease, to get seasonal infectious diseases or also develop complications from those seasonal diseases.”

Gero has recently launched a (paid, for now) API, called GeroSense, that’s aimed at health and fitness apps so they can tap up its AI modelling to offer their users an individual assessment of biological age and resilience (aka recovery rate from stress back to that individual’s baseline).

Early partners are other longevity-focused companies, AgelessRx and Humanity Inc. But the idea is to get the model widely embedded into fitness apps where it will be able to send a steady stream of longitudinal activity data back to Gero, to further feed its AI’s predictive capabilities and support the wider research mission — where it hopes to progress anti-ageing drug discovery, working in partnerships with pharmaceutical companies.

The carrot for the fitness providers to embed the API is to offer their users a fun and potentially valuable feature: A personalized health measurement so they can track positive (or negative) biological changes — helping them quantify the value of whatever fitness service they’re using.

“Every health and wellness provider — maybe even a gym — can put into their app for example… and this thing can rank all their classes in the gym, all their systems in the gym, for their value for different kinds of users,” explains Fedichev.

“We developed these capabilities because we need to understand how ageing works in humans, not in mice. Once we developed it we’re using it in our sophisticated genetic research in order to find genes — we are testing them in the laboratory — but, this technology, the measurement of ageing from continuous signals like wearable devices, is a good trick on its own. So that’s why we announced this GeroSense project,” he goes on.

“Ageing is this gradual decline of your functional abilities which is bad but you can go to the gym and potentially improve them. But the problem is you’re losing this resilience. Which means that when you’re [biologically] stressed you cannot get back to the norm as quickly as possible. So we report this resilience. So when people start losing this resilience it means that they’re not robust anymore and the same level of stress as in their 20s would get them [knocked off] the rails.

“We believe this loss of resilience is one of the key ageing phenotypes because it tells you that you’re vulnerable for future diseases even before those diseases set in.”

“In-house everything is ageing. We are totally committed to ageing: Measurement and intervention,” adds Fedichev. “We want to building something like an operating system for longevity and wellness.”

Gero is also generating some revenue from two pilots with “top range” insurance companies — which Fedichev says it’s essentially running as a proof of business model at this stage. He also mentions an early pilot with Pepsi Co.

He sketches a link between how it hopes to work with insurance companies in the area of health outcomes with how Elon Musk is offering insurance products to owners of its sensor-laden Teslas, based on what it knows about how they drive — because both are putting sensor data in the driving seat, if you’ll pardon the pun. (“Essentially we are trying to do to humans what Elon Musk is trying to do to cars,” is how he puts it.)

But the nearer term plan is to raise more funding — and potentially switch to offering the API for free to really scale up the data capture potential.

Zooming out for a little context, it’s been almost a decade since Google-backed Calico launched with the moonshot mission of ‘fixing death’. Since then a small but growing field of ‘longevity’ startups has sprung up, conducting research into extending (in the first instance) human lifespan. (Ending death is, clearly, the moonshot atop the moonshot.) 

Death is still with us, of course, but the business of identifying possible drugs and therapeutics to stave off the grim reaper’s knock continues picking up pace — attracting a growing volume of investor dollars.

The trend is being fuelled by health and biological data becoming ever more plentiful and accessible, thanks to open research data initiatives and the proliferation of digital devices and services for tracking health, set alongside promising developments in the fast-evolving field of machine learning in areas like predictive healthcare and drug discovery.

Longevity has also seen a bit of an upsurge in interest in recent times as the coronavirus pandemic has concentrated minds on health and wellness, generally — and, well, mortality specifically.

Nonetheless, it remains a complex, multi-disciplinary business. Some of these biotech moonshots are focused on bioengineering and gene-editing — pushing for disease diagnosis and/or drug discovery.

Plenty are also — like Gero —  trying to use AI and big data analysis to better understand and counteract biological ageing, bringing together experts in physics, maths and biological science to hunt for biomarkers to further research aimed at combating age-related disease and deterioration.

Another recent example is AI startup Deep Longevity, which came out of stealth last summer — as a spinout from AI drug discovery startup Insilico Medicine — touting an AI ‘longevity as a service’ system which it claims can predict an individual’s biological age “significantly more accurately than conventional methods” (and which it also hopes will help scientists to unpick which “biological culprits drive aging-related diseases”, as it put it).

Gero AI is taking a different tack toward the same overarching goal — by honing in on data generated by activity sensors embedded into the everyday mobile devices people carry with them (or wear) as a proxy signal for studying their biology.

The advantage being that it doesn’t require a person to undergo regular (invasive) blood tests to get an ongoing measure of their own health. Instead our personal device can generate proxy signals for biological study passively — at vast scale and low cost. So the promise of Gero’s ‘digital biomarkers’ is they could democratize access to individual health prediction.

And while billionaires like Peter Thiel can afford to shell out for bespoke medical monitoring and interventions to try to stay one step ahead of death, such high end services simply won’t scale to the rest of us.

If its digital biomarkers live up to Gero’s claims, its approach could, at the least, help steer millions towards healthier lifestyles, while also generating rich data for longevity R&D — and to support the development of drugs that could extend human lifespan (albeit what such life-extending pills might cost is a whole other matter).

The insurance industry is naturally interested — with the potential for such tools to be used to nudge individuals towards healthier lifestyles and thereby reduce payout costs.

For individuals who are motivated to improve their health themselves, Fedichev says the issue now is it’s extremely hard for people to know exactly which lifestyle changes or interventions are best suited to their particular biology.

For example fasting has been shown in some studies to help combat biological ageing. But he notes that the approach may not be effective for everyone. The same may be true of other activities that are accepted to be generally beneficial for health (like exercise or eating or avoiding certain foods).

Again those rules of thumb may have a lot of nuance, depending on an individual’s particular biology. And scientific research is, inevitably, limited by access to funding. (Research can thus tend to focus on certain groups to the exclusion of others — e.g. men rather than women; or the young rather than middle aged.)

This is why Fedichev believes there’s a lot of value in creating a measure than can address health-related knowledge gaps at essentially no individual cost.

Gero has used longitudinal data from the UK’s biobank, one of its research partners, to verify its model’s measurements of biological age and resilience. But of course it hopes to go further — as it ingests more data. 

“Technically it’s not properly different what we are doing — it just happens that we can do it now because there are such efforts like UK biobank. Government money and also some industry sponsors money, maybe for the first time in the history of humanity, we have this situation where we have electronic medical records, genetics, wearable devices from hundreds of thousands of people, so it just became possible. It’s the convergence of several developments — technological but also what I would call ‘social technologies’ [like the UK biobank],” he tells TechCrunch.

“Imagine that for every diet, for every training routine, meditation… in order to make sure that we can actually optimize lifestyles — understand which things work, which do not [for each person] or maybe some experimental drugs which are already proved [to] extend lifespan in animals are working, maybe we can do something different.”

“When we will have 1M tracks [half a year’s worth of data on 1M individuals] we will combine that with genetics and solve ageing,” he adds, with entrepreneurial flourish. “The ambitious version of this plan is we’ll get this million tracks by the end of the year.”

Fitness and health apps are an obvious target partner for data-loving longevity researchers — but you can imagine it’ll be a mutual attraction. One side can bring the users, the other a halo of credibility comprised of deep tech and hard science.

“We expect that these [apps] will get lots of people and we will be able to analyze those people for them as a fun feature first, for their users. But in the background we will build the best model of human ageing,” Fedichev continues, predicting that scoring the effect of different fitness and wellness treatments will be “the next frontier” for wellness and health (Or, more pithily: “Wellness and health has to become digital and quantitive.”)

“What we are doing is we are bringing physicists into the analysis of human data. Since recently we have lots of biobanks, we have lots of signals — including from available devices which produce something like a few years’ long windows on the human ageing process. So it’s a dynamical system — like weather prediction or financial market predictions,” he also tells us.

“We cannot own the treatments because we cannot patent them but maybe we can own the personalization — the AI that personalized those treatments for you.”

From a startup perspective, one thing looks crystal clear: Personalization is here for the long haul.

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Source: https://techcrunch.com/2021/05/07/longevity-startup-gero-ai-has-a-mobile-api-for-quantifying-health-changes/

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7 Ways Artificial Intelligence is Improving Healthcare

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Emerging technologies have the potential to completely reshape the healthcare industry and the way people manage their health. In fact, tech innovation in healthcare and the use of artificial intelligence (AI) could provide more convenient, personalized care for patients.

It could also create substantially more value for the industry as a whole—up to $410 billion per year by 2025.

This graphic by RYAH MedTech explores the ways that technology, and more specifically AI, is transforming healthcare.

How is Technology Disrupting the Patient Experience?

Tech innovation is emerging across a wide range of medical applications.

Because of this, AI has the potential to impact every step of a patient’s journey—from early detection, to rehabilitation, and even follow-up appointments.

Here’s a look at each step in the patient journey, and how AI is expected to transform it:

1. Prevention

Wearables and apps track vast amounts of personal data, so in the future, AI could use that information to make health recommendations for patients. For example, AI could track the glucose levels of patients with diabetes to provide personalized, real-time health advice.

2. Early Detection

Devices like smartwatches, biosensors, and fitness trackers can monitor things like heart rate and respiratory patterns. Because of this, health apps could notify users of any abnormalities before conditions become critical.

Wearables could also have a huge impact on fall prevention among seniors. AI-enabled accelerometer bracelets and smart belts could detect early warning signs, such as low grip strength, hydration levels, and muscle mass.

3. Doctors Visits

A variety of smart devices have the potential to provide support for healthcare workers. For instance, voice technology could help transcribe clinical data, which would mean less administrative work for healthcare workers, giving them more time to focus on patient care.

Virtual assistants are expected to take off in the next decade. In fact, the healthcare virtual assistant market is projected to reach USD $2.8 billion by 2027, at a CAGR of 27%.

4. Test Results

Traditionally, test results are analyzed manually, but AI has the potential to automate this process through pattern recognition. This would have a significant impact on infection testing.

5. Surgery / Hospital Visits

Research indicates that the use of robotics in surgery can save lives. In fact, one study found that robot assisted kidney surgeries saw a 52% increase in success rate.

Robotics can also support healthcare workers with repetitive tasks, such as restocking supplies, disinfecting patient rooms, and transporting medical equipment, which gives healthcare workers more time with their patients.

6. Rehabilitation

Personalized apps have significant care management potential. On the patient level, AI-enabled apps could be specifically tailored to individuals to track progress or adjust treatment plans based on real-time patient feedback.

On an industry level, data generated from users may have the potential to reduce costs on research and development, and improve the accuracy of clinical trials.

7. Follow-ups and Remote Monitoring

Virtual nurse apps can help patients stay accountable by consistently monitoring their own progress. This empowers patients by putting the control in their own hands.

This shift in power is already happening—for instance, a recent survey by Deloitte found that more than a third of respondents are willing to use at-home diagnostics, and more than half are comfortable telling their doctor when they disagree with them.

It’s All About the Experience

Through the use of wearables, smart devices, and personalized apps, patients are becoming increasingly more connected, and therefore less dependent on traditional healthcare.

However, as virtual care becomes more common, healthcare workers need to maintain a high quality of care. To do this, virtual training for physicians is critical, along with user-friendly platforms and intentionally designed apps to provide a seamless user experience.

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Source: https://www.visualcapitalist.com/7-ways-artificial-intelligence-is-improving-healthcare/

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AI In Healthcare: 7 Benefits That Can Advance Medical Facility Operations

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Science is progressing in this digitally advanced world. This includes computer science, medical facilities, and many other fields. But the amazing part is these branches often fuse to form a new one. Just like AI in healthcare.

AI in medical facilities is the fusion of computer science with the medical field. This technology is said to help this field in many ways. Furthermore, AI has said to increase the percentage of long-term treatment completion by 96%!

That was one part of it. There are several others. These pros make the medical industry invest in AI. Furthermore, this investment is going to make the AI market share around $ 7.7 billion by 2021! So let’s take an insight into the benefits of AI in healthcare. But first, let’s learn a bit about this technology.

Artificial Intelligence – Introduction

We all hear about artificial intelligence. Yet we often fumble when we try to explain it. So let’s make it clear from the term itself. The term artificial intelligence was first coined by Alan Turning in the 1950s. However, several other scientists went on adding more flesh and blood to this term. Turing set the prime goal and vision of this term with one simple question. “Can machines think?” Scientists have tried all these years to answer this question in the affirmative.

Artificial intelligence means the duplication of human intelligence. This intelligence is infused in machines. This makes them complete tasks that require human thinking. Artificial intelligence has some sub-branches:

  • Machine learning
  • Deep learning, and
  • Automation

This branch of computer science has enabled these to perform work without human effort. In short, machines can do what humans can! From businesses to government sectors are implementing this technology for:

  1. Better security
  2. Enhanced productivity
  3. Assured quality, and
  4. Proper safety

For healthcare, the applications are the same. But the area in which this technology is applied is different. So let’s check those out!

7 AI in Healthcare Benefits That Provide Advanced Facilities

Technology has been evolving; you often find yourself surrounded by many apps and websites about medical facilities. These apps are often powered by AI.

Did you know? AI in healthcare helps to save 20%-50% of yearly savings! Furthermore, medical centers are adopting AI for making many manual processes automated. Starting from surgery to disease detection, you get many such facilities. Now let’s check the most important ones.

1. Better data-driven decision

Doctors have a hectic schedule. And remembering and finding necessary documents and data can be extremely important. So rather than manually finding them AI and healthcare can assist doctors in this process. Since an AI system tends to collect all the documents related to the organization in a cloud. Therefore, authoritative users can access this data at any point in time. This can be extremely beneficial while making decisions.

2. Detect disease at an early stage

Now you have all the information at your disposal. So you can compare a patient’s records easily to find out towards which direction the disease is progressing. Furthermore, AI-driven medical apps can also help in this. These apps monitor your heartbeat, pulse rate, and other necessary details. Also, if you input about your health issues it will provide you with:

  • Daily reports about your health
  • Practices that you need to obtain
  • Daily health habits
  • Getting a doctor’s appointment
  • Appointment reminders
  • Virtual appointment and others

3. Assistance in surgery

Automation is used in many industries. But after much research, it has been implemented in the medical field as well. Hospitals nowadays implement surgical systems. Here the machines make accurate movements required during surgery. Automation, therefore, has these advantages:

  • Minimal blood lack
  • Less pain
  • Use of antibacterial nano-robots to prevent infections
  • Reducing side effects and much more

4. Post-surgical updates

Now, we know how AI in healthcare assists doctors in surgeries. It also provides them with updated reports about the patients’ current condition. These reports are backed up by previous reports. Therefore, these reports are highly accurate in nature.

5. Automated human support

As said before, AI in healthcare and other fields has reduced human labor. Robots have taken over the roles of nurses. Here are some ways how robots are better replacements than humans:

  • Robotic Assistance
  • Exoskeleton robots help paralyzed people get physiotherapy
  • Checks blood pressure
  • Helps to check temperatures
  • Maintains sugar levels
  • Helps patients to take their medicine on time and others

6. Supports mental health

People often ignore mental health. But it’s one of the most important health issues that we face in this current time. Depression and its sister companions often come when you feel abandoned. Therefore, AI companion robots or conversational robots, help you keep positive.

These robots have to build personality detection algorithms. They detect your emotions and help to maintain a balance in them. This helps people suffering from mental health issues remain positive.

AI-based mental health apps also help. This helps in the following ways:

  • Tracking daily lifestyle habits
  • Automatically track sleeping hours
  • Provides reminders about medicines, appointments, and other activities
  • Teaches relaxation techniques
  • Enables you to participate in like-minded groups
  • Helps to maintain a journal and much more

7. Saves money and energy

AI in healthcare tends to save 50% of a firm’s yearly expenditure. Furthermore, it also reduces many other activities. Let’s check how AI is enabling that:

  • Reduce unnecessary hospital visits by creating platforms for virtual appointments
  • Simplifying and automating accounting
  • Unburdening staffs from unimportant tasks to focus more on patients’ health
  • Reducing treatment time because important data are provided in a single click
  • Creating time-saving administrative duties and much more

So, these were some of the most important AI applications used in healthcare. However, the list doesn’t end here. Read more at Healthcare Automation.

Before you leave, let’s take a look back at all that we have discussed.

AI in Healthcare Benefits – In a Nutshell

  1. Helps to make better decisions with AI’s big data analytics
  2. AI helps in better diagnosis and early-stage detection of a disease
  3. Artificial intelligence in healthcare extends a hand during surgeries
  4. Updates medical facilities with accurate reports about patients’ post-surgical conditions
  5. AI robots tend to provide better support to patients especially for daily activities
  6. Supports patients suffering from mental health issues
  7. Saves time and energy by making processes efficient

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The ‘Cyber Attacks’ Winter is Coming — straight for small firms in India Inc.

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Cyber intrusions and attacks have increased exponentially over the last decade approximately, exposing sensitive information pertaining to people and businesses, thus disrupting critical operations, and imposing huge liabilities on the economy. 

Cybersecurity is a responsibility that employees and leaders across functions must shoulder simply because it is the gospel truth – you cannot protect what you cannot see. As organizations have shifted to the work-from-home model due to the outbreak of the COVID-19 pandemic, it’s increasingly important to keep your company’s data secure. 

While the pandemic has led to near or complete digitalization of operations amongst financial institutions, it’s also increased the potential for cyberattacks that lead to adverse financial, reputational, and/or regulatory implications for organizations. 

According to Accenture, cybercrime is said to cost businesses $5.2 trillion worldwide within five years. “With 43% of online attacks now aimed at small businesses, a favorite target of high-tech villains, yet only 14% prepared to defend themselves, owners increasingly need to start making high-tech security a top priority,” the report continues.

A recent McAfee study shows global cybercrime costs crossed US$1 trillion dollars in 2020, up almost 50% from 2018.

India too saw an exponential rise in cybersecurity incidents amid the coronavirus pandemic. Information tracked by the Indian Computer Emergency Response Team (CERT-In) showed that cybersecurity attacks saw a four-fold jump in 2018, and recorded an 89 percent growth in 2019.

The government has set up a Cyber Crisis Management Plan for countering cyber-attacks effectively, while also operating the Cyber Swachhta Kendra (Botnet Cleaning and Malware Analysis Centre).

Banks and Financial Institutions (FIs) are some of the highest targeted market sectors. An analysis by Can we hyperlink this: https://www.fitchratings.com/videos/exploring-bank-cybersecurity-risk-13-04-2021?mkt_tok=NzMyLUNLSC03NjcAAAF82rxN_2lbDTsEp4tfBu4tUGP7i6wyb1OGpyNY0Z8lQPhdz9C7KQ-NIriTcJqNSDyb9qfQ_essxS-TdNWMgJesb-RA4yN4t7T-XqXmVfWW4dau36SW6ZE 

“>FitchRatings in collaboration with SecurityScorecard reveals that banks with higher credit ratings exhibited better cybersecurity scores than banks with lower credit ratings. 

Bharti Airtel’s chief executive officer for India, Gopal Vittal, in a letter to the telco’s 307.9 million subscribers, detailed out how Airtel is carrying out home delivery of SIM cards and cautioned subscribers from falling prey to cyber frauds. He cautioned them against the rapid rise in cyber frauds, highly likely via digital payments. “There has been a massive increase in cyber frauds. And as usual, fraudsters are always finding new ways to trick you,” he added in the letter. 

Barcelona-based Glovo, valued at over $1 billion, that delivers everything from food to household supplies to some 10 million users across 20 countries, came under attack recently when the “hacker gained access to a system on April 29 via an old administrator platform but was ejected as soon as the intrusion was detected”, according to the company.

The attack came less than a month after Glovo raised 450 million euros ($541 million) in funding. 

According to Kaspersky’s telemetry, close on the heels of coronavirus-led pandemic and subsequent lockdown in March 2020, saw a total number of meticulously planned attacks against remote desktop protocol (RDP) jumped from 93.1 million worldwide in February 2020 to 277.4 million 2020 in March — a whopping 197 percent increase. In India, the numbers went from 1.3 million in February 2020 to 3.3 million in March 2020. In July 2020, India recorded its highest number of cyberattacks at 4.5 million.

The recent data breach at the payment firm Mobikwik, affected 3.5 million users, exposing Know Your Customer (KYC) documents such as addresses, phone numbers, Aadhaar card details, PAN card numbers, and so on. The company, however, still maintains that there was no such data breach. It was only after the Reserve Bank of India’s intervention that Mobikwik got a forensic audit conducted immediately by a CERT-IN empaneled auditor and submitted the report. 

Security experts have observed a 500% rise in the number of cyber attacks and security breaches and a 3 to 4 times rise in the number of phishing attacks from March until June 2020.

These attacks, however, are not just pertaining to the BFSI sector, but also the healthcare sector, and the education sector.

Image Source: BusinessStandard.com

What motivates hackers to target SMBs? 

Hackers essentially target SMBs because it’s a source of easy money. From inadequate cyber defenses to lower budgets and/or resources, smaller businesses often lack strong security policies, cybersecurity education programs, and more, making them soft targets. 

SMBs can also be a ‘gateway’ to larger organizations. As many SMBs are usually connected electronically to the IT systems of larger partner organizations, it becomes an inroad to the bigger organizations and their data. 

How can companies shield themselves from a potential cyberattack: 

As a response to the rising number of attacks in cyberspace, the Home Ministry of India issued an advisory with suggestions on the prevention of cyber thefts, especially for the large number of people working from home. Organizations and key decision-makers in a company can also create an effective cybersecurity strategy that’s flexible for adaptation in a changing climate too. Here are a few use cases: 

  • CERT-In conducted ‘Black Swan – Cyber Security Breach Tabletop Exercise’, in order to deal with cyber crisis and incidents emerging amid the COVID-19 pandemic, resulting from lowered security controls. 
  • To counter fraudulent behavior in the finance sector, the government is also considering setting up a Computer Emergency Response Team for the Financial Sector or CERT-Fin.
  • Several tech companies have come forth to address cybersecurity threats by building secure systems and software to mitigate issues like these in the foreseeable future. For example, IBM Security has collaborated with HCL Technologies to streamline threat management for clients through a modernized security operation center (SOC) platform called HCL’s Cybersecurity Fusion Centres. 

Some of the ways through which companies can mitigate potential risks include: 

  • Informing users of hacker tactics and possible attacks
  • Establish security rules, create policies, and an incident response plan to cover the entire gamut of their operations
  • Basic security measures such as regularly updating applications and systems
  • Following a two-factor authentication method for accounts and more

While these measures are some of the ways to be on top of your game in the cybersecurity space, they will also help in sound threat detection while helping gain better insights into attacks and prioritizing security alerts so that India is better prepared for an oncoming attack and battling any unforeseen circumstance that might result in huge loss of data, resources and more. 

Coinsmart. Beste Bitcoin-Börse in Europa Source: https://www.mantralabsglobal.com/blog/the-cyber-attacks-winter-is-coming-straight-for-small-firms-in-india-inc/

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