IBA Group – Blog https://blog.ibagroupit.com/ A software service provider with optimized business processes and a proven history of customer interaction, IBA Group has a 30-year expertise in complex multiplatform projects Wed, 27 Mar 2024 12:15:18 +0000 en-EN hourly 1 https://wordpress.org/?v=5.9.3 Software Testing Can Be Automated, But Is This The End Of Coding As We Know It? https://blog.ibagroupit.com/?p=10133 https://blog.ibagroupit.com/?p=10133#respond https://blog.ibagroupit.com/?p=10133 The post Software Testing Can Be Automated, But Is This The End Of Coding As We Know It? appeared first on IBA Group - Blog.

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One of the most repeated statements about artificial intelligence (AI) in the technology industry is that it is about to replace coding as a specialist activity. It’s certainly true that AI has developed very rapidly in the past 18 months and it will change how code is developed, but there is some low-hanging fruit that can be addressed before worrying about the coding process.

Supporting a coding team can dramatically improve their productivity. It allows the programmers to focus on the coding processes by freeing them from some of the manual and essential tasks they need to undertake. This makes them more productive because it allows them to focus, but giving them this focus also improves the job itself, which further aids productivity.

As an example, look at the testing process. Every programmer knows that a small change to the code base can have unforeseen effects. You can’t change one section of code and just test that section only – before the client sees the system, you have to check it all again.

So the introduction of automated testing, in particular smart automated testing that can use AI to vary the functions being tested, removes the drudge work that every programmer hates. They focus on the creative side of their job and allow the AI to ensure that the code works each time a new release is packaged up.

This is true for any form of coding, but it is particularly applicable to mainframe code, where a very large code base and set of testing requirements can lead to corners being cut when testing is only performed manually. The IBA team was in Dresden recently talking about this at the GSE conference.

The IBA Head of Automation Testing, Julia Mikitjuk, recently posted an informative slideshow on LinkedIn focused on the myths around testing and automation. You can go to see the entire slideshow here, but a summary of the key points Julia made are:

  •  You don’t need to 100% automate everything for an initiative to be valuable
  • If you need to invest, then contrast the amount to what will be saved in the future
  • Automation can’t be switched on overnight — it needs planning
  • Automation might not replace your human testers — the aim is usually to augment what humans can do, rather than to replace them entirely
  • Automation helps a lot, but it can’t replace every single aspect of nuanced user interface testing

Software development is evolving. Tools like AI are making a dramatic difference, and many repetitive processes, such as testing, can be largely automated.

However, it is worth exercising caution.

As Julia outlines in her presentation, this is not the kind of project where you can push a button and suddenly it works. Even where a comprehensive testing automation system is in place, there will always be a need to run final checks with people — especially on the user interface.

Coding is evolving and AI offers a very powerful tool that can really help to improve quality and productivity at the same time, but managers responsible for software development should not believe the media hype that coding is finished – even testing code can’t be completely automated.

Automation and similar tools offer a way of reducing repetitive actions, improving quality, reducing errors, and therefore increasing productivity, but they are not an automatic replacement for the software development process. Not yet anyway!

For examples of IBA client success stories, including testing and automation, please click here. Follow the IBA Group on LinkedIn for regular updates and comment. For more information on technology strategy and how tech connects to real business solutions please click here.

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Using Data management and Analytics To Create Business Insight https://blog.ibagroupit.com/2024/03/using-data-management-and-analytics-to-create-business-insight/ https://blog.ibagroupit.com/2024/03/using-data-management-and-analytics-to-create-business-insight/#respond Thu, 21 Mar 2024 11:51:11 +0000 https://blog.ibagroupit.com/?p=10129 The post Using Data management and Analytics To Create Business Insight appeared first on IBA Group - Blog.

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Data management and analytics is a subject that has risen to the top of the CIO agenda in recent years. Companies across all industries are finding that how they store and use their data is no longer a question of infrastructure — it can define how well they can offer a service to their customers.

Think of the various aspects within data management that now need to be considered:

  • Data lakes and data warehouses: how are you physically storing data and if you need to apply real-time processing and analysis, then is the data available quickly enough for your requirements?
  • Data management in the cloud: what is the day-to-day process of managing your cloud infrastructure, and how can it add value and flexibility?
  • Visual flow solutions: which low-code solutions can allow you to create visual flows for data with the flexibility you need for constant change?
  • Smart clouds: you are unlikely to have a single cloud solution. How can in-house systems be managed alongside multiple clouds?

This can be combined and contrasted with the various options available for the manager that is planning how to analyze the data:

  • Business Intelligence: turning information — especially financial information — into valuable insights and assets. Ensuring all the data you have available contributes to the business.
  • Data Mining: finding hidden patterns in the data and creating insight that can inform management decisions.
  • Migration: planning how to migrate from existing analysis systems or plans to use a more modern and innovative environment.
  • IoT in real-time: keeping track of thousands, or millions, of sensors and not only representing those items visually, but allowing decisions to be made based on the live feedback.

It is clear that an immediate list of objectives and priorities can be created for a business that wants to focus on improved data management and analytics. There is the process of managing the data and ensuring it is available to be used quickly enough, as well as the analytics that generate insight.

The importance of this subject applies to businesses across all industries — all companies need to generate some form of insight into what they could be doing better or more efficiently.

A smarter use of data can reveal patterns and trends over time, allowing businesses to understand how certain variables change and evolve. This insight can help in forecasting future trends and making informed decisions.

Data can also be used to explore how customers interact with your business. Analyzing customer data can provide insights into customer preferences, purchasing behavior, and demographics. This information can be used to tailor marketing strategies, improve customer experience, and develop targeted products or services.

It should also be possible to use historic customer data combined with other information — such as the date, the weather, or special events — to make predictions. Businesses can build predictive models to forecast future outcomes. This can be applied to various areas such as sales forecasting, demand planning, risk management, and resource optimization.

A more effective management and analysis of data can have many other uses, such as customer segmentation or measuring the business performance. Market risks and new opportunities can be highlighted and can feed into the process of making important decisions about new services and products.

A more effective approach to management and analysis of data can lead to better business insights. These insights derived from data analysis empower businesses to make informed decisions, drive innovation, enhance competitiveness, and ultimately achieve their strategic objectives.

Data Management, Analytics, and AI is an important line of services provided by IBA Group. For case studies and examples of solutions, please click here.

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Automation of Regression Testing Improves Software Quality And Reduces Development Costs https://blog.ibagroupit.com/2024/03/automation-of-regression-testing-improves-software-quality-and-reduces-development-costs/ https://blog.ibagroupit.com/2024/03/automation-of-regression-testing-improves-software-quality-and-reduces-development-costs/#respond Mon, 11 Mar 2024 13:57:28 +0000 https://blog.ibagroupit.com/?p=10123 The post Automation of Regression Testing Improves Software Quality And Reduces Development Costs appeared first on IBA Group - Blog.

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Regression testing is a critical process for any company using software applications and systems, which is just about every organization today. Can you imagine any business today running without any software? We all know that when software is updated, usually with added features, then it is important to ensure that everything still works as it did before.

The added features need to improve the software, but without changing the reliability of all the old functionality. This is the danger for the IT team — a change may break the existing system.

It can be very expensive when a software update goes wrong. Look at the TSB Bank system upgrade in 2018. The British bank was migrating from one software platform to a new one and the upgrade failed. Customers were locked out of their bank accounts for almost a week. Random payments were being exchanged between customers who could not even login to see what was happening.

The banking regulator in the UK fined TSB £48.65 million for this mistake. That’s an expensive price to pay for a software upgrade that failed.

But the real cost is not just paying the fine that a regulator issues. How many customers moved their account because of this disaster? How many customers told their friends and family to never trust TSB? The damage to reputation and ongoing business may have cost far more than the fine.

Regression testing aims to prevent these disasters. It allows system administrators to look back at different versions of the software, testing each new one, to ensure that once rolled out into production, there will not be any glitches. It also creates a set of stages — versions of the software. This ensures that, at each stage that works, there is the ability to roll-back if a new version has problems.

This focus on system stability and reliability is critical for many modern software systems. A banking disaster is serious for customers, but think about the immediate danger to lives if an air traffic control system started failing after an upgrade? Software controls so many aspects of our life today, there are some applications that simply cannot fail.

The best way to rigorously ensure that new versions work is regression testing. The software developers create a series of tests that each new version of the software must pass to prove it works correctly.

The problem is that in a large system, there may be many thousands of potential options and functionality to be tested. It is not only easier to train an automated regression testing system to perform all these tests, but it also creates a more secure testing environment. People performing manual tests may become bored or may skip tests, assuming they will be OK. The automated regression testing system will methodically check everything over and over again.

By continuously verifying the behavior of the software against a predefined set of test cases, regression testing helps maintain the overall quality of the software product. It ensures that the software performs as expected across different scenarios and user inputs.

This is great news for a software team that wants to ensure they avoid business impact — like the TSB disaster. Regression defects can have significant business impact, leading to loss of revenue, customer dissatisfaction, and damage to reputation. Regression testing helps in mitigating these risks by identifying and fixing defects before they reach the production environment.

The approach to version control also allows a strong focus on Agile development, where small changes and improvements are rolled out quickly, rather than waiting months for a software update with many new changes. In Agile methodologies where software evolves through iterative cycles of development, regression testing plays a critical role. It allows teams to quickly assess the impact of changes and ensure that the software remains stable and reliable throughout the development process.

Automated regression testing reduces the time and cost associated with software testing, but the improved quality offered by automation is possibly even more important than cost alone. Many industries are highly regulated and problems caused by software updates can lead to heavy fines — in addition to the loss of reputation.

Regression testing is essential for maintaining the stability, reliability, and quality of software applications, ultimately contributing to customer satisfaction and business success. Automating this process not only makes it more cost-effective and faster, but it also ensures a consistent level of testing quality — essential for any modern business.

IBA Group provides automated regression testing services, systems, and advice. Please click here for more information.

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Analytics and AI Go Far Beyond ChatGPT And Bots https://blog.ibagroupit.com/2024/02/analytics-and-ai-go-far-beyond-chatgpt-and-bots/ https://blog.ibagroupit.com/2024/02/analytics-and-ai-go-far-beyond-chatgpt-and-bots/#respond Thu, 29 Feb 2024 13:51:07 +0000 https://blog.ibagroupit.com/?p=10119 The post Analytics and AI Go Far Beyond ChatGPT And Bots appeared first on IBA Group - Blog.

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News about ChatGPT dominated the business press in 2023. It was launched at the end of 2022 and was surprisingly easy (and free) for the general public to use. It caught the imagination of millions, and soon every business journal was publishing endless articles about how artificial intelligence (AI) was about to change your business forever.

But Chatbots and generative AI are not the whole story. One of the most valuable use cases for business is using AI to find patterns or preferences, to sift through customer data to see what cannot be seen by the human eye. To find insights not visible on a spreadsheet.

This is a rapidly evolving digital landscape, but it had started before ChatGPT. The integration of AI and data analytics into business operations has opened a new frontier in understanding and predicting customer behavior. This innovative blend presents an unparalleled opportunity for companies to delve deeper into the psyche of their customers, offering insights that were previously unattainable.

At the heart of this transformation is the ability of AI and data analytics to process and analyze vast amounts of data. Every day, customers generate a colossal amount of data through their interactions with various digital platforms. This data, encompassing everything from purchase history and online browsing habits to social media interactions and location data, is a goldmine for understanding customer preferences and behaviors.

It’s easy to understand that this data reveals what customers like and prefer to buy, but it also shows what they don’t like, what they look at but never buy, when they buy, which combinations of items they buy. There is huge value inside this data.

AI algorithms, particularly those based on machine learning, are adept at identifying patterns and trends within this sea of data. They can discern subtle preferences and behaviors that might be invisible to the human eye. For instance, AI can analyze past purchase data to predict future buying trends, or it can scrutinize browsing patterns to understand what products a customer might be interested in.

This predictive capability allows businesses to anticipate customer needs, sometimes even before the customers themselves are aware of them. This example from Target is one of the classic examples — it is from over a decade ago, but it is illustrative of what can be achieved. Target can predict who is going to have a baby soon, even before other family members.

AI and data analytics has come a long way since then, but the Target example makes it very clear what we are talking about – insight into what customers want and need. Moreover, AI and data analytics enable personalized customer experiences, which are key in today’s market where consumers expect services and products tailored to their individual needs.

Companies can use AI to deliver personalized marketing, where advertisements and promotions are targeted to individual consumers based on their unique preferences and past behavior. This level of personalization not only enhances customer satisfaction but also significantly increases the effectiveness of marketing campaigns.

Another significant advantage is the ability to continuously learn and adapt. AI systems evolve with every interaction, becoming more refined and accurate in their predictions and insights. This continuous improvement cycle ensures that businesses stay aligned with changing customer preferences and market trends.

AI-driven analytics can help in identifying new market opportunities and customer segments by revealing patterns and relationships that were not evident before. This can lead to the development of new products or services, tapping into unmet customer needs, and opening new revenue streams for businesses. This can be even more powerful if the brand proactively involves a small group of customers in testing new services.

However, the use of AI and data analytics also comes with its challenges, such as ensuring customer privacy and data security. Companies must navigate these challenges carefully, maintaining transparency and trust with their customers.

The opportunity presented by AI and data analytics in understanding and predicting customer behavior is immense. By leveraging these technologies, companies can gain a deeper understanding of their customers, provide more personalized experiences, and stay agile in a rapidly changing market.

This not only leads to enhanced customer satisfaction and loyalty but also provides a significant competitive edge in the business world. As these technologies continue to evolve, their role in shaping business strategies and customer relationships is set to become even more pivotal.

In a world where hundreds of millions of people have started experiencing AI on a daily basis in their personal life, it is hard for major organizations to justify not exploring this technology and what it can do for the brand to customer relationship.

Data Management, Analytics, and AI is an important line of services provided by IBA Group. For case studies and examples of solutions, please click here.

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What Should New CIOs Focus on In Their First 100 Days? https://blog.ibagroupit.com/2024/02/what-should-new-cios-focus-on-in-their-first-100-days/ https://blog.ibagroupit.com/2024/02/what-should-new-cios-focus-on-in-their-first-100-days/#respond Mon, 26 Feb 2024 11:03:10 +0000 https://blog.ibagroupit.com/?p=10115 The post What Should New CIOs Focus on In Their First 100 Days? appeared first on IBA Group - Blog.

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The first quarter of the year always brings a series of articles focused on trends for the year ahead. This is to be expected — everyone wants to look ahead when they are still in the darkness of January and February. However, I saw an interesting Gartner report that focused on this question in a different way.

Imagine that you are a new CIO. You just arrived at your new company and the technology used across the business is all under your responsibility. What would you do first?

This question has a positive and negative answer, and both are important to understand. What are the top actions you must take to define your leadership and the direction that the technology strategy will take, but also what are the top pitfalls that need to be avoided?

On the positive side, Gartner sets out these objectives as an initial approach to leading a new IT team:

  • Build credibility. Set the tone and direction for what you want to accomplish by determining both the priorities of your new company and how this matches your own personal ambition.
  • Ensure that your team and the tech being used are aligned to the present, but can also be scaled for the future.
  • Learn what works right now. Spend time with the team. Learn about the present operating model. Find gaps in motivation, talent, and workload.
  • Identify the most common issues that prevent change and progress. What is there in the company culture politics that may prevent new ideas taking hold?
  • Explore morale and fatigue in the team so you can lead change from a place where you are demonstrating a genuine improvement — you truly know what doesn’t work, so team members will buy in to change.

What is interesting about all these key steps or objectives is that they are largely focused on change and leadership, not technology. A new IT leader needs to build a network, find the problems, find what works and doesn’t work, and find out how the team really feels about the situation at present. You can’t build a credible roadmap to the future by importing it from another organization — it needs to be created by understanding the challenges of the existing team.

Communication and leadership are the real key to success.

But the Gartner report also focused on the five main pitfalls that CIOs fall into. These are the traps that prevent a new CIO from being an effective leader. The report says:

  • Pitfall 1: You build a brand that your enterprise is not interested in.
  • Pitfall 2: You make assumptions about the capabilities and capacities of IT.
  • Pitfall 3: You take action to improve how IT is perceived, based on fragmented and biased feedback.
  • Pitfall 4: You underestimate the importance of enterprise culture and politics.
  • Pitfall 5: You fail to focus on the importance of being a change leader.

I think these pitfalls, combined with the positive steps, are really powerful advice. Many people working in tech still make the assumption that a good CIO is someone with deep technical expertise. Of course, they need to understand what technology can do and what might be coming next year, but they don’t need to install it.

A great CIO understands how the business can use technology to improve their business processes and how they can get the entire workforce to support the technology – because they see it as an improvement.

Culture, office politics, and people that are invested in the old way of doing things are much more powerful than a new technology tool that will ‘revolutionize our business.’ Most people don’t like radical change. They want to see that the new ideas you are suggesting make their life better.

The most successful CIO is a great leader and communicator — not just a tech evangelist.

For more information on technology strategy and how tech connects to real business solutions please click here.

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Thoughts On The Intelligent Sourcing Interview With IBA Group CEO, Sergei Levteev https://blog.ibagroupit.com/2024/02/it-is-already-a-matter-of-survival/ https://blog.ibagroupit.com/2024/02/it-is-already-a-matter-of-survival/#respond Mon, 19 Feb 2024 15:18:33 +0000 https://blog.ibagroupit.com/?p=10106 The post Thoughts On The Intelligent Sourcing Interview With IBA Group CEO, Sergei Levteev appeared first on IBA Group - Blog.

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I’ve been contributing comment on IT, and how technology is shaping modern business, on this IBA Group Blog for many years now, so I have often had the chance to interact with the IBA CEO Sergei Levteev. Most recently, I talked to Sergei and wrote about our conversation for Intelligent Sourcing magazine.

You can find the interview here, but I thought it would be interesting to follow up and share my views on some of his comments and thoughts from the interview — a kind of follow-up from that discussion.

One of the first questions I asked Sergei was around specialization. Some IT companies focus on a single type of service — cloud specialists are a good example. IBA has a relatively wide array of expertise in several areas. I asked Sergei if this creates an advantage, and he said: “If you remember the computers and technologies we used in the 1990s, you understand that today we live in an entirely different world. In addition, it is a common situation when clients face not only one problem, but also a set of problems, and we are able to offer multiple solutions to their challenges with the use of different technologies.”

I think this is a valid point. Maybe looking back to the nineties is looking too far into history, but the underlying point is that most companies have complex supply chains and their ideal technology solution will cut across several areas. If a technology specialist can advise on automation, security, and the cloud within a single project, then this can create an advantage.

I asked Sergei why companies are not using much of the data they already have, and he said: “I agree that many companies have valuable data that they are not exploring. This is not because they don’t want to use the data. The problem is that the data is not ready to be explored. Using the best practices, we help our clients become familiar with their data and transform the data to valuable information.”

This is an important point. Every company has data. Many are swamped with data. There is so much data being recorded that they don’t know how to create any insight. The process of turning data into information is the first step towards being able to analyze it for trends and insights. As customers expect more and more personalization from companies, this is becoming critically important.

Sergei also talked about security and how this has changed for most companies since the Covid pandemic. He said: “The pandemic forced many of us to look at security issues in a new way. The companies that were not related to IT had to transfer their business online, and thus became more vulnerable to cyberattacks. As remote work infrastructure did not have the same level of security as the office environment, businesses had to invest in network security to prevent unauthorized access, data breaches, and malware infections. Therefore, the pandemic gave momentum to the development of security technologies.”

This is another important point. Most office-based employees knew their data was secure inside the office, and they very rarely needed to access systems remotely. Now, working from home and hybrid work has meant that it is normal to have access to systems from multiple locations — a large company may have thousands of people in many countries now accessing their data. An entirely new form of data security has been created in just the past few years alone.

As the full interview suggests, Sergei has a lot to say about IT and innovation, but when I asked him which industry he sees using IT for the fastest innovation in 2024, he gave his most succinct answer — and it is a good way to summarize the entire interview. He said: “Practically, all industries will be using IT to innovate in 2024. Otherwise, they will not be competitive. IT is already a matter of survival.”

IT is already a matter for survival. Get this wrong and your company may not live to see 2030. Sergei gave some great insights, and I really appreciated the chance to talk about IT strategy with him — I hope we can do it again later this year!

For a complete list of industries covered and supported technologies, please visit the IBA Group website here.

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Penetration Testing Offers An Opportunity To Improve Network Security https://blog.ibagroupit.com/2024/02/penetration-testing-offers-an-opportunity-to-improve-network-security/ https://blog.ibagroupit.com/2024/02/penetration-testing-offers-an-opportunity-to-improve-network-security/#respond Fri, 16 Feb 2024 13:47:29 +0000 https://blog.ibagroupit.com/?p=10100 The post Penetration Testing Offers An Opportunity To Improve Network Security appeared first on IBA Group - Blog.

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My wife used to work for one of the largest startups in Brazil. They had thousands of employees at their head office in São Paulo, and their service was entirely focused on their app. The company tore up all the rules about how people rent a home — they made it easy for people to find and rent in a market that was traditionally very bureaucratic and managed by traditional estate agents.

However, this also meant that they needed to manage some very sensitive customer data, such as income and bank account details. Security was extremely important because one data breach would mean a catastrophic loss of reputation.

The company had a security team and everyone across the company was trained in how to avoid cyber attacks, but they also regularly used penetration testing to check that the training had worked. This was when an external security company would try to gain access to their network, as if they were real hackers.

Sometimes this would be a disguised attack. All employees might receive an email saying they have won a prize and need to click a button to claim it — once they click, then the hackers have access to their system. Only a small percentage of people would click these links, but in the real world, only one is needed.

I always thought it was interesting that in a hi-tech startup environment, where everyone has been trained in cyber attacks and phishing, people will still click on a link because it says you have won the lottery. These are highly educated people that have been trained to be suspicious — yet some will still click the links.

This personal experience highlights the value of penetration testing — also known as pen testing. It can play a crucial role in strengthening corporate security by simulating the tactics and strategies of real-world hacker or attackers. This proactive approach allows companies to identify and address vulnerabilities in their systems before they can be exploited by malicious actors.

By conducting penetration tests, a company gains insights into potential weaknesses in its network, applications, and other systems. These tests mimic the actions of cybercriminals, trying to breach security defenses using a variety of techniques. This process not only uncovers technical flaws, such as unpatched software or misconfigurations, but also helps in assessing the efficacy of the overall security posture, including policies, employee awareness, and response procedures.

When vulnerabilities are identified, organizations can take specific, informed actions to rectify these issues. This could involve updating software, reconfiguring network elements, reinforcing firewalls, or enhancing encryption practices. Importantly, penetration testing also helps in prioritizing the vulnerabilities, allowing companies to allocate resources effectively to address the most critical issues first.

Another significant aspect of penetration testing is compliance. Many industries have regulations and standards that require regular security assessments, including pen testing. By conducting these tests, companies not only comply with these regulatory requirements, but also demonstrate their commitment to maintaining robust security practices.

Penetration testing also plays a vital role in shaping a company’s security policies and employee training programs. Insights gained from these tests can guide the development of more effective security protocols and inform employees about potential threats and best practices for preventing breaches.

Furthermore, regular penetration testing helps organizations keep pace with the evolving landscape of cyber threats. Attackers continually refine their techniques, and new vulnerabilities emerge as technology advances. Ongoing testing ensures that a company’s defenses remain effective against the latest threats.

Penetration testing is a critical element in strengthening corporate security. It provides a realistic assessment of a company’s vulnerabilities, guides the improvement of security measures, ensures compliance with industry standards, shapes policies and training, and helps companies stay prepared against evolving cyber threats. This proactive approach to security enables organizations to defend themselves more effectively against potential cyber attacks, ultimately protecting their data, reputation, and bottom line.

Penetration testing adds a critical additional layer of security, because no matter how secure your physical network is, it is really only as secure as your employees allow it to be. There is almost always a way in, if people allow it.

For more information on IBA Group Penetration Testing security services, please click here.

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Making AI Drive Revenue Is The Tech Target For 2024 https://blog.ibagroupit.com/2024/02/making-ai-drive-revenue-is-the-tech-target-for-2024/ https://blog.ibagroupit.com/2024/02/making-ai-drive-revenue-is-the-tech-target-for-2024/#respond Tue, 13 Feb 2024 15:02:14 +0000 https://blog.ibagroupit.com/?p=10092 The post Making AI Drive Revenue Is The Tech Target For 2024 appeared first on IBA Group - Blog.

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The big trend of 2023 was artificial intelligence — by a long way. The launch of ChatGPT at the end of 2022 just created a wave of excitement that has lasted all year, but what is coming next for technology in 2024?

Let’s see what some of the most important analysts have been talking about in their annual predictions.

Forrester Research talks about innovation beyond AI. Their research says: “To succeed in 2024, business leaders will need to embrace the spirit of exploration. The AI inflection point is here. It’s time to move fast, think bold, and be willing to pivot. The most dangerous move is to take a conservative ‘wait and see’ approach.”

Forrester suggests that the wave of AI hype that lasted throughout 2023 will transition into a wave of intent as companies finally realize how they can start using the technology.

Deloitte backs up this view. They believe that as companies find a real use for AI, there will be immediate revenue gains inside 2024. Their research said: “Generative AI (Gen AI) chip sales will likely reach over US$50 billion in 2024 and nearly all enterprise software companies will integrate gen AI in at least some of their offerings by the end of 2024, which could boost revenue by US$10 billion.”

Gartner suggests that Generative AI now needs to be a strategic consideration in every different department of your business. An interesting area that Gartner talks about is the modernization and upgrading of legacy technology systems. Their analysts believe that these projects can be supercharged through the use of AI.

The CTO of Amazon, Werner Vogels, has made an interesting prediction based on AI becoming more commonplace. He said that it will start changing college education and start blending college with businesses. That means companies have to shift not only how they hire but also how they design the workplace to make sure their people are constantly learning.

Talking to Forbes, Vogels said: “I’m very optimistic, not only because of generative AI, I see more and more businesses arriving that want to do good. They really are tackling hard problems … I’m very very optimistic.”

Looking through all these various predictions, there is a common theme, and it still revolves around AI. However, all the analysts are making a very similar point. The launch of ChatGPT created a very strong focus on what Gen AI can do, but most of 2023 was spent experimenting with this — and similar tools. In 2024 the expectation is that AI will now be used in real business solutions that drive revenue. This is a reasonable expectation. Many companies have launched new AI-powered solutions in Q4, and therefore these will only start making a difference in 2024.

I think the macro economy will also play an important factor in 2024. The US economy has not sunk into recession, as many economists predicted. Layoffs are low and retail sales are up. It’s all looking much better than expected a year ago. When consumer confidence returns, we may well start to see a new wave of innovation in areas such as fintech.

It could happen in 2024, but maybe this is really something for 2025. In the meantime, make sure that AI is on the agenda at your board meeting.

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Managing The Complexities Of Cloud Migration https://blog.ibagroupit.com/2024/02/managing-the-complexities-of-cloud-migration/ https://blog.ibagroupit.com/2024/02/managing-the-complexities-of-cloud-migration/#respond Tue, 06 Feb 2024 15:01:41 +0000 https://blog.ibagroupit.com/?p=10088 The post Managing The Complexities Of Cloud Migration appeared first on IBA Group - Blog.

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You have decided that the cloud makes sense. You want to gain all the advantages you have read about, such as only paying for applications and storage as they are needed. But what next? How do you move from your current infrastructure to a cloud environment?

Migrating to the cloud is a significant step for any organization, as it involves moving data, applications, and IT processes from on-premises servers to a cloud environment. This transition, while offering numerous benefits such as scalability, cost-efficiency, and enhanced performance, also presents several critical issues that must be meticulously addressed to ensure a successful migration.

The rewards are out there, but it requires planning.

You may already be using some cloud services, public or private. There are not many organizations in 2024 that retain all data storage and applications on-site, but whatever your existing structure, if you plan to migrate further into the cloud, then there are some key questions to consider:

Understanding Cloud Suitability and Selection of the Right Cloud Provider

One of the primary considerations in cloud migration is determining the suitability of the cloud for specific organizational needs. Not every application or workload benefits equally from being moved to the cloud. Therefore, a thorough assessment of the applications, including their architecture, dependencies, and performance requirements, is essential.

This assessment helps in deciding which applications should be moved to the cloud, which should be re-architected for cloud optimization, and which should remain on-premises. Furthermore, selecting the right cloud provider is crucial. The chosen provider should align with your technical requirements, compliance standards, and budget constraints. Evaluating the services, support, and SLAs (Service Level Agreements) of potential providers is essential to make an informed decision.

There are the major cloud platform providers, such as Azure and AWS, but also some niche providers that may be more suitable. In addition, it is worth paying close attention to the software you will have available for day-to-day control of your environment.

Planning and Strategy

A well-defined migration strategy is the key to a successful cloud migration. This involves setting clear objectives, timelines, and KPIs (Key Performance Indicators) to measure the migration’s success. It is important to have a phased approach, starting with less critical applications to gain experience and confidence before moving to more critical systems. This strategy should include considerations for data migration, application migration, and changes to operational processes.

This plan also needs to be communicated well, so all users are aware of what will move and when. In addition, by moving low stakes applications first, you can demonstrate a series of quick wins that give more confidence for larger migration phases.

Security and Compliance Concerns

Moving to the cloud requires stringent attention to security and compliance. The shared responsibility model in cloud computing means that while the cloud provider is responsible for the security of the cloud, the organization is responsible for securing what they put in the cloud.

This is a very important point. Your cloud platform and cloud service provider will be there to ensure the integrity of the cloud, but if the data you load into the cloud is corrupted or if you create a data breach within your own organization, then the security breach is your own responsibility.

It’s imperative to understand the compliance requirements relevant to the industry and region, such as GDPR for organizations operating in or handling data from the European Union. Data encryption, both at rest and in transit, identity and access management, and regular security assessments are vital components of a cloud security strategy.

Artificial Intelligence can also be deployed very effectively in a cloud environment to monitor your cloud for unusual activity. This can help the security team by highlighting any potential data breaches before significant damage occurs.

Cost Management and Optimization

While cloud computing can offer cost savings, it also poses the risk of unexpected expenses if not properly managed. Understanding the pricing models of cloud services and accurately forecasting usage is crucial to avoid cost overruns. Organizations should continuously monitor and optimize cloud resources to ensure they are being utilized efficiently and effectively.

The big advantage of a cloud business model is that companies pay for services only as they are used — all costs are transparent. The downside is that where CFOs have the experience of relying on sunk costs — such as software licenses bought a few years back – they may be surprised by cloud charges. Smart CFOs will know the value of shifting Capex into Opex.

Technical and Operational Challenges

Cloud migration often involves significant changes to an organization’s IT infrastructure and operational processes. Ensuring compatibility and smooth integration of cloud services with existing systems is a complex task that requires careful planning and testing.

Additionally, the organization’s IT staff may require training to adapt to the new cloud environment. Change management processes are critical to address these operational shifts and to ensure that the staff is prepared for the transition.

The internal staff can be augmented by a cloud specialist for the period of the migration, but training and upskilling have to be an integral part of the transition process so they are ready to manage when the project team is ready to leave.

Downtime and Data Integrity

Minimizing downtime during migration is crucial to avoid disruption to business operations. This requires a robust migration plan that includes data backup and a clear rollback strategy in case of unforeseen issues. Ensuring data integrity during and after the migration is also essential. This involves careful planning of data transfer methods and thorough testing post-migration to ensure all data have been accurately and completely transferred.

The value of a robust rollback cannot be stressed enough — always ensure it is possible. If a migration phase goes wrong, then it will only complicate the situation further if the rollback to a previous system is complex or impossible.

Cloud migration is a multifaceted process that demands careful consideration of various factors, such as cloud suitability, security, compliance, cost management, technical challenges, and operational impact. A comprehensive and well-thought-out migration strategy, aligned with the organization’s specific needs and goals, is fundamental to a successful and smooth transition to the cloud.

Cloud expertise is just one area within the IBA Group operations and development services team. For more information, please click here.

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GPT Models in the Banking Sector: Revolution in Artificial Intelligence https://blog.ibagroupit.com/2024/01/gpt-models-in-the-banking-sector-revolution-in-artificial-intelligence/ https://blog.ibagroupit.com/2024/01/gpt-models-in-the-banking-sector-revolution-in-artificial-intelligence/#respond Wed, 31 Jan 2024 11:02:32 +0000 https://blog.ibagroupit.com/?p=10064 The post GPT Models in the Banking Sector: Revolution in Artificial Intelligence appeared first on IBA Group - Blog.

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Building upon the insights shared in our previous article, Utilizing Artificial Intelligence Techniques in Constructing Intelligent Software Robots, in this installment we delve into GPT Models in the Banking Sector, providing insights into our solution: the EasyRPA Platform.

Let’s discuss generative models, the latest revolution in the field of artificial intelligence. Over the past year, we have witnessed remarkable progress in the realm of Generative Pre-trained Transformer (GPT) models. Trained on massive datasets, these models have the ability to generate text and process information at a level that was previously deemed unattainable.

Generative Models in certain cases successfully handle tasks we’ve discussed earlier, such as classification, information extraction, and even show results that sometimes exceed those of specialized models. However, it’s worth noting that traditional models operate faster and require significantly fewer resources for their functioning. Accordingly, if a traditional model can handle a task, it is optimal to use it.

We would also like to focus separately on the fascinating area opened up by generative models, Retrieval Augmented Generation (RAG), where these models generate content with the assistance of a search mechanism.

Retrieval Augmented Generation (RAG)

These are specialized techniques that allow using pre-trained large language models, such as OpenAI, for efficient handling of data. The techniques help connect generative models with any data that contains text and interact with this information.

Banking Sector Example

In the banking sector, the RAG technique is employed for communication with documents that contain marketing materials. For instance, a banking chatbot synchronized with the bank’s marketing materials enables customers to obtain information on relevant services based on specific criteria. This eliminates the need for manual examination of materials.

Which tasks do we entrust to artificial intelligence?

The question of which tasks can one entrust to artificial intelligence becomes increasingly relevant in the context of automating bank business processes? The answer to this question is ambiguous and depends on the specific application area.

A key consideration is understanding the cost of error in each specific process. It’s important to note that even manual processes performed by humans do not guarantee error-free outcomes, and the human factor also carries its own risks. Artificial intelligence, in turn, provides an opportunity to reduce the likelihood of errors and improve the quality of task execution.

Let’s consider examples that highlight the importance of accurate decisions:

1. Automating email classification for task distribution among departments

— Sending a task to a wrong department has minimal consequences and can be rectified manually. In this case, it’s undoubtedly feasible to entrust this task to AI.

2. Extracting data from financial documents

— Incorrect extraction of amounts from an invoice can lead to significant financial losses. The cost of error is high, but the human factor also carries its risks. Can we reduce risks by entrusting this task to AI?

Solution: We should monitor the robots. To achieve this, it’s crucial to have three components in the system:

1. Post-processing rule configuration: This allows us to adjust the results of AI work. For instance, we might want to standardize extracted dates from receipts of different clients to a unified format.

2. Automatic validation rule configuration: How can we ensure that the final invoice amount is extracted correctly? We can set up a validation rule that sums the prices of all items in the invoice and compares the result with the final total.

3. Manual task execution environment: A space where a human can intervene to recheck and correct the results of artificial intelligence in case they fail validation.

4. Periodic model retraining based on manual correction results.

Solution: EasyRPA Platform

Fortunately, there are ready-made platforms that address these challenges, like EasyRPA. In addition to tackling the entire spectrum of tasks related to RPA automation, its key advantages in working with AI in the banking sector include:

  • Integrated Machine Learning Models: EasyRPA provides the ability to train machine learning algorithms without coding and without requiring Data Science qualifications.
  • Built-in OCR Models: Enables extraction and processing of data even from scanned documents.
  • Flexible Configuration of Post-Processing and Validation Rules for AI Results: Allows fine-tuning rules for post-processing and validation of AI-generated results.
  • Built-in Workspace Application: A dedicated space where human intervention can handle manual tasks and assist the AI.
  • Continuous Model Retraining Based on Manual Corrections: The model is continually retrained based on the outcomes of manual corrections.

Attaining an optimal balance between automation and flexibility, and ensuring efficiency and security in banking business processes is possible only through a comprehensive approach where humans verify and enhance the work of robots.

Risk-Free RPA Pilot

How It Works

Selection: Together, we identify the most suitable process for automation, ensuring its significant enough to demonstrate true value.

Detailed Analysis: Our business analyst collaborates with you to craft a comprehensive description of the targeted process.

Budget Estimation: An IBA Delivery Manager reviews the project details, determining implementation costs and providing a transparent budgeting plan that accounts for all potential risks and out-of-scope tasks.

Agreement: Both parties align on a fixed scope of work to ensure clarity and mutual understanding.

Automation: Rely on IBA Group’s expertise to automate the chosen process seamlessly.

Zero Upfront Costs: As we operate on a post payment system according to the T&M model, you pay ONLY if you decide to deploy to production. If our robot is not a perfect fit, we will not charge for the work done

Zero License Costs: Once implemented, enjoy the automated process without any additional license fees.

Flexible Modifications: We believe in evolution, not reinvention. Minor process changes won’t be treated as brand-new projects. For significant alterations, we swiftly modify the existing code.

About the Risk-Free RPA Pilot

The Risk-Free Pilot isn’t just a showcase or a minimal product. It’s a comprehensive project, meticulously designed to offer genuine business value within your real operational environment. Move beyond traditional PoCs and MVPs, and experience the true potential of RPA with IBA Group 🚀.

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