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Selling Digital Transformation To An Industry That’s Reluctant To Change

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Laurent Charpentier, CEO at Yooz

 

When Henry Ford created the Model T, he transformed car manufacturing from a slow, expensive process requiring highly skilled teams to one where a non-expert team of people could assemble a car in about 90 minutes.

More than a hundred years later, Ford Motor Company is in the midst of another, ongoing revolution—one whose impact on every industry only accelerated during the pandemic: digital transformation.

Yet, not every industry is equally sold on operating smarter with technology, even if they desperately need to do so. Some are happy with tried-and-true processes. So, how do you sell change in industries where they don’t necessarily want it?

 

What does ‘digital transformation’ really mean?

The term digital transformation has been thrown around so much that it’s almost lost its meaning. What it actually means is using technology and data to automate outdated, often  manual tasks. Another essential aspect of digital transformation requires gathering, aggregating and accessing data efficiently, thus enabling corporate stakeholders to make better-informed, data-driven decisions.

The pandemic forced many organizations to adopt digital transformation by integrating video calls, videoconferencing and remote working options in their daily business practices. Today, companies can go a step further by asking departments what challenges or inefficiencies they’re now experiencing as a result. When employees propose improvements, they can have a positive impact on efficiency, costs and job satisfaction.

Digital transformation needn’t involve a significant change or a complete overhaul of a process to be effective. Companies resistant to change can start small by targeting an area or process that’s struggling or one with the most potential for a high return on investment. The organization needs time to recognize the benefits of one digitization before proceeding to a complete digital transformation. Small steps allow time to get buy-in for future stages.

Digital transformation can affect and impact every part of an organization. Some industries have focused more on one area—often the front office touching revenue-driving activities—but might lag in the back office. From my experience, goods-producing industries like construction or manufacturing often seem more reluctant to change than others.

But you can’t stereotype an entire industry. There will always be trendsetters willing to try new things and push the boundaries of the “normal process.” Late adopters are more cautious. They believe the risk is too great and adhere to the mentality, “If it’s not broken, don’t fix it.”

 

Why are some companies reluctant to modernize their systems and processing?

Several factors could explain a reluctance to embrace digital transformation, such as:

  • Lack of awareness about the benefits and ROI of automation or digital transformation;
  • Legacy accounting, enterprise resource planning or other systems posing barriers to modernization;
  • Fear of breaking a “tried and true” process (however imperfect) that isn’t “broken;”
  • Lack of resources to drive transformation projects;
  • Difficulty finding the right tools due to outdated or overly complex processes.

In the accounts payable space for example, common reasons organizations put off digital transformation initiatives often include inadequate time allocated to implementing and training everyone on new processes. Another fear is that the change will be too costly, and there are more pressing challenges to deal with first.

Other companies have been the industry or local market share leaders so long that they feel no need to adjust their processes. But with the shifting environment that the pandemic brought to all industries, even those have woken up to the need for change and improvement.

Perhaps it’s due to the new structure of their organization post-pandemic, or it could be because their competitors took positive steps to incorporate digitization. Regardless, the competition is starting to surpass the former leaders, and the laggards see they must keep up or be left behind.

 

How can you sell change in an industry that fears it?

Getting buy-in from all levels helps ensure a smooth digital transformation implementation process that leads to faster, more efficient user adoption and the greatest ROI. The primary decision-makers and stakeholders depend on your industry, business function and organization. But the support of those who will use the digital solution regularly is crucial in gaining approval from top decision-makers, as they are key influencers in the process.

An accounts payable automation initiative, for example, needs the CFO’s complete buy-in. Usually, a designated champion will supervise the entire project, acting as the interface between users and decision-makers.

As a technological provider, you can leverage events like industry or software trade shows and conferences to share your ideas and perspectives on digital transformation with reluctant audiences.

You can reach (and educate) an even broader range of decision-makers in various industries using virtual and digital events such as webinars, partnerships or sponsorships with relevant or complementary businesses. Even local vectors like chambers of commerce and professional C-level associations can be a good way to educate companies on the benefits of digital transformation.

Educate first and provide valuable free resources such as white papers, industry reports and webinars to start conversations around new technology solutions and how they can benefit an organization.

Finally, when entering a new industry or niche, cast a wide net with public and educational approaches using email marketing and paid social media. You also need a personalized touch and individual attention at certain points in the marketing process. Success stories that back up your value proposition and ROI are essential to building credibility with your audience.

Ford Motor Company looks nothing like it did in the 1900s—or even the 1990s. Ford’s digital transformation has made the company a leader in automation, the use of software in manufacturing and even robotics. Other industries have no choice but to follow suit to remain competitive.

Change can be hard sometimes, especially when it comes to making a technology leap. Some industries are naturally more reluctant than others, but there can be holdouts in even forward-thinking industries. Does this modify the approach to selling change in different industries? Not really. Sometimes, you just have to digitally transform an industry one company at a time.

Business

Ransomware chokes COBRA: How AI-powered data analysis can support financial services’ plight

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By Toby Butler, Financial Crime Solutions Manager at Ripjar

 

Ransomware attacks are on the increase in the United Kingdom. Most of the British Government’s COBRA meetings have been convened in response to ransomware attacks, showing how cybersecurity breaches are as pressing as national emergencies and crises. The National Cyber Security Centre’s (NCSC) annual review found this year that the country was hit by 17 ransomware incidents that were so impactful they “require a nationally coordinated response”. That extends to the financial services sector, which saw an increase of ransomware attacks with 55% of organisations hit in 2021.

Where does this leave the sector and how can artificial intelligence and machine learning be instrumental in understanding the risks companies face against future ransomware attacks?

Toby Butler

Company information is being stolen and sold to different threat groups, who prey on the individuals in that organisation who are more likely to pay them. The UK is one of the most cyber-attacked countries in the world and the Government has been criticised for being “ill-equipped” to deal with this exponential rise of fraud cases.

 

Ransomware-as-a-Service

Ransomware is one of the most common forms of cybercrime. Fighting it has become one of the biggest problems that organisations today face during their everyday operations. For instance, Malware (malicious software) encrypts the files of a single computer, then works its way through an entire network to reach the server and inflict maximum damage. Company information is being stolen and sold to different threat groups, who prey on the individuals in that organisation who are more likely to pay them.

When these attacks occur the victims, more often businesses, are left with minimal options. If they have substantial backup solutions already in place, they can attempt to restore the encrypted data to their servers. But if that data isn’t already secured elsewhere, they may need to pay a ransom to the criminals behind the attack. Thereby allowing the business to function once again and restoring their reputation. The cost of paying the ransom will feel considerably smaller compared to starting a business again from scratch. Sophos’ State of Ransomware in Financial Services 2022 report found that 52% of financial services organisations paid the ransom to restore their data, the average remediation cost in financial services was US$1.59M.

Cybersecurity Ventures estimates that ransomware is set to cost global businesses more than $256 billion by the end of 2031. By that token, organisations need to be extremely mindful of the potential threats they may face. Businesses need to understand the methodologies these hackers use, to address the weaknesses within their domain and take measures to isolate and prevent further ransomware attacks from happening again.

 

The rise of WAMs

According to a recent report by security firm CyberSixgill, 19% of the 3,612 cyberattacks that took place in 2021 were traced back to Wholesale Access Markets – or WAMs for short. WAMs are, in essence, underground internet flea markets. These markets are where aspiring attackers come to purchase network access from threat actors – the individual or entity involved in carrying out the cyber-attack. Types of threat actors include insiders, cybercriminals, rival organisations, or even nation states stealing data.

WAMs sell access to multiple compromised endpoints (or pathways) for around 10-20 dollars. Researchers found that WAMs listed access to approximately 4.3 million compromised endpoints in 2021, which include access to both provider and enterprise software (for example, an organisation’s Slack channel) up to 180 days before the attack itself took place. This shows how long these compromised endpoints remain undetected without proper internal analysis.

 

How can Financial Services stay ahead of the curve?

The use of Artificial Intelligence (AI) and machine learning is undisputed across modern businesses and sectors, and continues to revolutionise processes across the board. AI is a significant player in the financial services industry, building the ‘cyber-wall’ against nefarious users. It gives organisations optimal insights into reducing the likelihood of a ransomware attack in the future.

Namely, AI and machine learning collects and analyses vast amounts of messy (structured and unstructured) data from disparate sources. The challenge for the sector is to understand the volume and variety of the raw data collected from any source to build better protection in the future.

Structured information could be best understood as the clear data we see in a table. For example, the following attendees made a business meeting: first name – Joan, surname – Smith, age – 46. But unstructured information is information presented in a complex manner. For example, ‘there were five people who attended the business meeting, one of whom was forty-six and called Joan Smith’. Naturally, due to the complex nature of the prose, it would be more difficult for a machine to process that data into a digestible format for further risk analysis. This is where AI continues to prove invaluable.

AI uses natural language processing to understand the information provided on the web. As the software continues to evolve, natural language processing reads the information in a way a human would to extract the key information from the text. By incorporating AI and machine learning within an organisation’s IT infrastructure, companies operating within financial services can be better equipped to handle cybercrime.

These tools are flexible and adaptable, they can be configured to analyse different types of data from different sources to curate key insights. This collated information provides a better analysis of the organisation’s exposure, allowing them the opportunity to get upstream in preventing future attacks. This kind of approach is essential to processing listings on WAMs.

The power to analyse data to identify weakness is vital in the battle against cybercrime. It gives organisations a better understanding into what they could expect to see in the future. Hosting the correct data, and with the analytical skills, financial organisations can gain a better understanding of the methodologies and weaknesses in-house that attackers use and exploit to hold them to ransom. Organisations can then use this as a reference to pinpoint compromised endpoints, giving them a chance to reduce access before this route can be exploited and ruin their business.

With cybercrime and ransomware continuing to remain prevalent, it’s vital that financial services companies understand how they can get ahead of the curve and build a robust security platform within their IT infrastructure that can withstand an attack. In 2022, a ransomware attack occurred every 40 seconds. The mindset for the sector needs to be one of when, not if.

Organisations need to be thinking about an attack now – before it’s happened. Pre-planning and preparing for the worst possible outcome from future threats and adversaries. The introduction of AI and machine learning in the fight against cybercrime is a must, and the sooner the industry gets behind in implementing AI, the safer it will be through the next decade.

 

 

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Banking

How Banks Can Boost App Innovation, Speed and Compliance

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Steve Barrett, Senior Vice President of International Operations, Delphix 

As new finance and banking applications disrupt the market each day, and customer expectations around speed, privacy and quality continue to grow, financial organization CIOs and DevOps teams have to innovate quickly to bring new apps and updates to market, while remaining strictly compliant to a myriad of regulations. DevOps innovation in financial services requires fast access to accurate, compliant test data, and as anyone who touches the industry knows, data privacy is a highly complex, critical process woven into the everyday world of finance.

Banks and financial services organizations collect vast amounts of data, but using that data for innovation can be challenging due to the vast size and complexity of test data. These challenges can inhibit the adoption of new and transformative technologies and hinder innovation if they are not addressed head on. To address these challenges, many organizations are integrating the use of highly innovative test data management (TDM) tools within their DevOps ecosystems. DevOps TDM provides access and delivery of lightweight, compliant data for DevOps initiatives including digital transformation, software upgrades, cloud migration, artificial intelligence and machine learning (AI/ML), and analytics.

Data – the last automation frontier

Historically, application teams manufactured data for development and testing in a siloed, unstructured fashion. Over time, large IT organizations began consolidating TDM functions to take advantage of innovative tools to create test data. With the rise of modern development methodologies like DevOps and CI/CD that demand fast, iterative release cycles and end-to-end API-driven automation, legacy TDM approaches are often no longer sufficient.

Reliance on a traditionally manual, ticket-driven, request-fulfill model creates time drains during test cycles and slows the pace of application delivery. Consider the payments industry, in which agile technology companies using optimized DevOps processes can release new code hundreds of times per month. In contrast, traditional banks with slow IT ticketing systems may take months to release new features. These manual, legacy TDM approaches exist in contradiction with modern DevOps practices and CI/CD processes that depend on automation and fast feedback to development teams.

TDM for the DevOps Era

DevOps teams rely on TDM to evaluate the performance, functionality and security of applications. However, while processes including storage, compute, and code have all been automated, data has eluded the reach of most DevOps toolchains.

Now, DevOps TDM can help accelerate app releases and increase compliance.by automating the delivery, provisioning, and compliance of data. These practices provide both development and testing teams with data APIs, including the ability to refresh, rewind, bookmark, group, tag, branch, and share test data, to accelerate DevOps productivity and improve application quality. DevOps TDM also includes copying production data, and the masking (anonymization) and virtualization of data through the DevOps pipeline, which helps accelerate app releases and increase compliance.

And as the pace of application development quickens, so does the pace of privacy regulations and efficiently ensuring compliance in DevOps has become a significant challenge for enterprises. Non-production data used for testing software applications, reporting, and analytics can contain up to 80% of an enterprise’s sensitive data. To solve this, DevOps TDM provides integrated data masking to de-identify personally identifiable information (PII) and other sensitive data in non-production environments, eliminating the risk of sensitive data exposure.

The World Quality Report 2022-2023[1] by Capgemini stressed the importance of an enterprise wide approach to test data provisioning (a core component of TDM). The report states, “Over the years, with stringent regulatory and security requirements around data, organizations have increased their focus on provisioning test data safely and securely.”

The report shows that secure test data provisioning remains a challenge, with only 20% of respondents having a fully-implemented enterprise test data provisioning strategy in place to address security and compliance requirements.

Data is the catalyst to innovation

Automation is fueling myriad digital transformations within the financial services sector, but without the right data, these application innovations cannot succeed. DevOps TDM can help further accelerate DevOps initiatives by automatically delivering fresh, complete, and secure test data wherever and whenever it is needed, in minutes. With DevOps TDM, banks and financial institutions can innovate faster, reduce time-to-market for updating legacy applications, and accelerate development and testing of disruptive fintech.

 

[1] Source: https://www.capgemini.com/insights/research-library/world-quality-report-wqr-2022/

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