With an increase in adoption of commercial and investment banking technology, organisations are now providing customers with greater communication, ease of access and financial opportunities. In fact, between 2017-2021, consumers in Asia-Pacific emerging markets increased their use in digital banking by 33%, with 88% of consumers now utilising it today. Furthermore, investment banking technology really took off during the last decade with blockchain as even political bodies such as the EU are now looking to invest in crypto currencies.  For many people at heritage financial firms, the digital transformation seems like a scary move. Gartner recently predicted that by 2030, 80% of heritage financial firms will either go out of business, become commoditised or only exist formally. The expectation is that fintech organisations and global digital platforms will only gain more relevance and thrive under the conditions of digital transformation. The problem for many is the use of legacy technology, which by its very nature is traditionalist and outdated. With an increase of people working from home, people want both stronger commercial and investing banking technology. For the customer, it will allow them to access their finances with ease, which creates opportunities for fintech security companies that are then able to provide greater protection from outside threats. For investors, the ability to mobilise their investments with greater ease can only be achieved through stronger technology. In this EM360 podcast, we speak to Mark Aldred, VP of Sales at Auriga, about the use of banking technology in 2021, the risks associated with it, what new technologies we expect to see and how we, as business professionals, can prepare ourselves for the inevitable dangers.

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Commercial and Investment Banking Technology

As much as people fear that they have lost their anonymity on the internet, technologies that previously companies and individuals alike to regain this privilege are starting to show their shortcomings. The VPN setup, which has been gaining steady momentum since it became publicly available in 1999, is finally reaching the end of its lifeline as the surge of cybercrime has reared its ugly head. The best thing we can do during this uncertain time is to make the VPN setup comfortable in its final days, say our farewells and welcome the future of SASE technology.  With the increase of remote working globally helping to improve productivity and employee satisfaction, new challenges have arrived. One of the key problems comes with unsafe Wi-Fi networks, which can usually be found within cafes or at home and can put organisations at risk. The VPN setup also often covers huge areas, which when combined with insecure networks can mean that potential security risks are actually more destructive than ever before.  SASE, or Secure Access Service Edge, provides users with access to critical apps for all parts of your business, without having to go through corporate headquarters. This means that regardless of where you are working, your data remains safe and your network remains protected. Joining our Head of Content Max Kurton in this EM360 Podcast is Mike Wood, CMO at Versa. In this podcast, Mike guides us through the way in which IT teams go about introducing, implementing, and adopting SASE into their organisations, the shortcomings of the VPN setup and much more.

The Future of SASE and the Death of the VPN Setup

Needless to say, trusted computing is a complex and heavily debated subject. Even today, in 2021, the debate continues, and organisations are still weighing up the benefits of what a trusted computing hardware or software system might bring to them. In traditional trusted computing hardware, technology is used to allow the user to decide what they can trust and what they can't. Of course, this advantage of freedom can seem fantastic to many users, but the debate opens up again surrounding the effectiveness of humans. We already know that humans make mistakes, and we know that sometimes computers can be much better judges thttps://em360tech.com/podcasts/daniel-burrus-agility-react-disruption (han humans.) Opening this can of worms with us in this EM360 podcast is Thorsten Stremlau from Trusted Computer Group. In this podcast, we hear how far trusted computing hardware and software has come in the last few decades, what the future brings for it, the answers to some of the most popular questions in this hot topic and the benefits trusted computing can truly bring.

Is Trusted Computing Hardware and Software Outdated?

With the increasing lack of anonymity on the internet, users and organisations alike are looking to implement a VPN setup within their system in order to gain a stronger sense of security. In countries with strong firewalls such as China, businesses prioritise the use of VPNs in order to open themselves up to the global market. With that said, a weak VPN setup can often cause severe security problems within their organisation. Companies are now forcing their workforce to work from home, and while it's granted a huge amount of flexibility and has yielded some overwhelmingly positive results for organisations, it comes with security risks. When organisations implement VPNs, it means that they are extending their full network into their home device and are actually allowing more entry points for potential adversaries to commit security offenses.  Rejecting the VPN Setup in Favour of Zero Trust Network Access ModelsMore modern practices are favouring Zero Trust Network Access models, or ZTNAs, as a way to assist organisations with hybrid working. ZTNA is an architecture that is fundamentally different from a VPN setup and allows users to operate on a separate network. In this podcast, our Head of Content Max Kurton speaks to Kurt Glazemakers, Chief Technology Officer at Appgate. They talk about the future of the ZTNA industry, the problems organisations have in switching from a VPN setup to a ZTNA and the drawbacks of using a VPN.

ZTNA Models: Fixing Flaws in the VPN Setup

Privacy enhancing technologies, or PETs, can be used for a multitude of reasons; whether it's being used to decrease the crime rates of countries, for social good or even for the use of your business, PETs have proved time and time again to be effective. PETs are broad, and when using one within your business, the focus really should be on providing a safe network for your customers, clients and consumers. One way in which PETs can be used for this is by blocking third party website traffic analysis, thus preventing your customers from being monitored. This is not only something that needs to be paid attention to by people within the tech industry, but really for any B2B or B2C business. Customer data is often readily available, and when permission has not been given by the customer, legal implications await.  In this EM360 podcast, we speak to Ellison Anne Williams, Founder and CEO at Enveil. Ellison Anne covers the many different ways in which PETs can be used for social good, how to implement them, the necessity of PETs in areas such as the health industry and the future of data protecting tech.

Using PETs for Social Good

What data science needs, in our current world where we have more data than we know what to do with, is a solution that allows data to be readily applicable and useful for the growth of an organisation. This does not just mean the ability to analyse the market, but it also means the ability to enhance integrated experiences, giving organisations a stronger connection with their customer base. This is where we start to mark the difference between data cleanliness and data readiness. With data cleanliness, we are enabling a process that fixes errors, corrects formatting and completes data within a dataset. This ultimately makes that data much more high quality and rewarding depending on what data science aims your business has. Data readiness, in contrast, is data that's ready to be used by the business owners and can be combined with other data sources in order to make intelligent decisions. Yes, data cleanliness is important in order to achieve data readiness, however the two are distinct operations. Joining us in this EM360 podcast is Mike Kiersey, CTO at Boomi. Throughout this podcast, we will walk you through the methods of becoming data ready, the best practices to maintain in your data strategy, the use of AI in data readiness and much more. 

Data Readiness: What Data Science Needs

Changing methodologies and approaches to B2B marketing creates constant challenges for those attempting to reach their market segment with ease. What B2B means today is very different to what it meant in the past, and this is in part due to the effects of content marketing. While the days of print magazines, posters and radio ads are less common nowadays, new incarnations of these, in the format of content marketing, consistently change the industry.  One way in which companies are now capturing the attention of their audience is through podcasting. Again, what B2B means in the modern day is different to what it meant in the past, but that doesn't mean that some commonalities cannot be held. In contrast to its distant relative, radio advertising, podcasting allows organisations to take the audience on a long journey, exploring potentially relatable problems that they face in the day to day. It still grants the advertiser air time, it still provides them with a platform to talk to people while they make their daily commute to work, but it's more in depth and relatable for their market segment. It then allows organisations to provide themselves as the solution to their posed problems, driving more leads and sales to their business. In this EM360 podcast, we are joined by Kieran Flanagan, Senior Vice President Marketing at HubSpot. Kieran is here to discuss the new age of B2B customer communication, the types of ROIs companies likely to see if they add podcasts and other digital media to their marcomms mix and other ways to implement B2B marketing campaigns. 

What B2B Means Within a Content Driven World

While new technologies are constantly being developed to fight cybercrime and strengthen cybersecurity systems, much of the cybersecurity is left yawning. New additions to technologies such as Endpoint Detection and Response (EDR), while effective, are not implementing the level of change that we need to see if we want to ensure safety while reducing workloads of employees. EDR, for instance, often sends alerts to employees notifying them that unexpected activities need to be investigated. How many emails do we receive a day from job recruiters, collaboration tools, social media tools and others? Of course, investigating cyberthreats is important, but it's hard to care about additional newsflashes after receiving your 20th promotional email of the week from your local pizzeria. Beyond this, there are already some serious undeniable threats in cyberspaces that cannot be ignored. With hundreds of devices existing within every organisation, there exists hundreds of attack vectors. Yes, certain cybersecurity technologies can exist, but adversaries always develop new attack methods. Really, it's worth keeping up to date with the latest news in AI in order to find a technology that can learn these methods and grow over time.  News in AI proves to be more and more interesting everyday with new technologies being applied to protect security interests. For those of us already working in cybersecurity, machine learning in AI is old news, but how many organisations are using deep learning-based prevention? According to Deep Instinct, deep learning-based prevention helps us to surpass "The Cybersecurity Trade-Off" where organisations prevent threats, but also receive high volumes of false positives. This helps to prevent a 'boy-cried-wolf' situation and instead brings real, analysed threats to your attention.  Delivering us the latest news in AI is Shimon Noam Oren, VP Research & Deep-Learning at Deep Instinct. In this podcast, he delves into the 'prevention trade-off dilemma', the problems with cybersecurity prevention software, the ins and outs of deep learning and how it can provide a more robust cybersecurity methodology.

Using Deep Learning to Fight Cybercrime

The phone scam has been in the cybercriminal's playbook for decades, but the pandemic has lead to a sharp increase of these attacks. According to Eric Griffith from PC Mag, According to Eric Griffith from PC Mag, a well constructed phone scam can exploit more money than a scam conducted via email, social media, websites or apps. This becomes all the more concerning with our reliance on our phones in 2021, particularly when employees work from home. With the increase of remote working and fewer people in conventional workplaces, the need for communication tools has of course increased, but call centres are now sifting through more work than anybody could have anticipated. For some, call volumes increased by 800%, which has created intense work pressure for employees. Cybercriminals have now adapted their phone scam methods to specifically target call centres, leaving them vulnerable to attacks and placing huge responsibilities on customer service staff.  The Evolution of the Phone Scam Voice phishing, or 'Vishing', is a form of social engineering attack that is primarily used to steal privileged credentials from corporations. The aim is to manipulate the target into exposing a weakness in the company, leading to data leaks or cybertheft. Vishing is not new, but it evolves continuously; changes in the market lead to changes in behaviour, which lead to new tactics. Joining us on in this podcast is Nikolay Gaubitch, Director of Research at Pindrop. Throughout this podcast, Nikolay will explain the dangers of vishing, how it affects call centres and what you can do to protect your business from a devastating phone scam.

Vishing: The Evolution of the Phone Scam

Security threats are unavoidable and inescapable for modern businesses. No matter the size of the enterprise, dealing with the likes of data breaches and ransomware attackers has become commonplace. The key, then, is to know how exactly to detect and respond to these incidents. With new threat hunting and detection technologies, tools, and techniques being created each quarter, the security solutions pool is becoming bigger and bigger.   In this podcast, Chris Steffen, Research Director at Enterprise Management Associates (EMA), speaks with Dr. Anton Chuvakin, Head of Solutions Strategy at Chronicle and Google Cloud, about the emerging trends in threat hunting and investigation, as well as incident response. The conversation kicks off with a look at the challenges that organisations face when a breach occurs and the proliferation of high-profile security breaches and ransomware attacks within legacy systems. Dr. Anton then lends his expertise on the act of combining intelligence about global threats in the wild, threats inside your network, and unique signals from the overlap between the two, before delving into top tips for overcoming the “signal to noise” ratio. To close, the pair explore the impact of President Biden’s Executive Order on Cybrsecurity and the latest trends in threat hunting and investigation.

Chronicle: Detecting Breaches and Ransomware Attackers

The world of artificial intelligence and machine learning is everchanging, with new trends being discovered every year. In the wake of GDPR in 2018, the use of such technologies was applied to legal documents, company legislations and privacy regulations. In 2019, this trend continued while others experimented with incorporating AI into video game design. In 2020, the COVID-19 pandemic meant that AI was used to create digital workers, making up for medial labour that users would usually perform while in the office. In 2021, we are seeing new trends, but we are also seeing barriers. According to IDC, the artificial intelligence market is forecast to grow 16.4% by the end of 2021, but even still, obstacles stand in the way for innovation and even for development. Deploying machine learning is difficult; that's why, for this exclusive EM360 podcast, we are speaking to Dr. Eugene Izhikevich, CEO of Brain Corp. In this podcast, we will be delving into some of the biggest problems facing the AI landscape today, predictions for 2021 and some of the solutions.

Machine Learning is Facing Barriers

With new analytic trends emerging as we delve deeper into this decade, organisations are starting to pay attention to solutions and tools that offer them greater insights into their data. A study from Forrester Research revealed that less than 0.5% of all data is ever analysed and used, while only 12% of enterprise data is used to make decisions. As it currently stands, much of our data is confined to silos, meaning that it is too segmented to be analysed, while many organisations still have not received enough training to empower their data scientists and fix the data gap. The quickest solution would be to invest in a technology that performs much of the analysis for you automatically, i.e. augmented analytics. Augmented analytics is one of the latest data trends and for good reason; it implements machine learning and natural language processing to automate analysis processes that would usually be conducted by an expert in that field. Essentially, data is processed faster than it would be by a human, which also makes it cost effective. Despite this, some organisations remain concerned about the implementation process, the perceived risks and the costs. Joining us in this EM360 podcast is Rohit Maheshwari, Head of Strategy and Product at Subex. In this episode, we talk to him in depth about the benefits of augmented analytics, how it can bring value to your business and the restrictions of legacy software.

What is Augmented Analytics?

Implementing AI to automate sales and financial duties is nothing new, but recently there has been a lot of discussion related to AI powered Order-to-Cash platforms. In nearly every sector, reducing waiting times means reducing costs, but Order-to-Cash AI can also be the key to customer retention and expansion while also speeding up financial processes. In 2021, we are attempting to bounce back from a massive disruption, but that disruption has meant the development of new technologies that allow organisations to excel. Securing customers and retaining pre-existing customer bases has been cited as the biggest challenge to 61% of companies by SEM Rush. So, could Order-to-Cash platforms be the solution? Joining us on this EM360 podcast is Mark Sheldon, CTO of Sidetrade. In this episode, Mark delves into the the impact of Order-to-Cash AI on sales and finance teams, how payment intelligence software can benefit ROI and cost reduction as well as exploring the top considerations for organisations to be aware of before investing in AI for their sales and finance teams. 

Order-To-Cash Platforms in an AI World

As more and more businesses experience latency issues in traditional cloud databases, edge computing is now more popular than ever before. Having a device at the edge of your network allows for smoother run times while also synchronising with other geo-distributed devices in your ecosystem that are placed on other parts of the globe.  Fusing an already impressive piece of kit with machine learning results in something truly impressive: Edge AI. Edge AI brings in faster decision making, vast improvements to UX and is more energy efficient than other data management tools. Processing data can now be done in real time, so why is there still scepticism about adopting edge AI? Why haven't more businesses adopted it already?  Joining us in this EM360 podcast is Dan Warner, CEO and Co-Founder of LGN; an organisation dedicated to bringing new edge technology to a wider audience. 

What is Edge AI and How Can it Help You?

Email is the front door into an organisation and humans typically manage it. However, with phishing attacks becoming more targeted and sophisticated, and increasing cases of account takeover and data loss due to a successful email attack, humans alone can no longer be relied on to protect the inbox. Fortunately for businesses, there are email security solutions - Artificial Intelligence (AI) technologies - that can help. Join Dr Eric Cole, CEO and Founder of Secure Anchor Consulting, and Mariana Pereira, Director at Darktrace, as they discuss email security and why organisations now, more than ever, need to treat it as a top priority. In this podcast, the pair explore how to secure enterprise inboxes with AI. Mariana leads the conversation by sharing her knowledge and expertise on the current threat landscape for email in 2021, the use of AI in email security, and the key factors decision-makers should consider when determining the best AI system. The discussion ends with a look at a real-life case study of an email attack autonomously stopped by AI. Want to learn more? Check out our recent Q&A with Mariana on how Antigena Email can create a self-defending inbox.

Darktrace: The Importance of Email Implementation

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