The Importance of ESG in Software Development

ESG is a massive movement in the global market that’s forcing businesses to adjust their approach to sustainability and corporate practices. ESG (environmental, social, and governance) practices are measured in scores that are beginning to dictate whether people invest in the company or not. 

The scores generally go from 0-100; anything below 50 is bad and will impact the company's reputation, bottom line, and long-term potential. Anything above 70 is great and consumers will look at the company as though supporting them is supporting the good of people and the planet.  

This recent commercial from Apple will give you a good idea of how that looks:

When it comes to software and technology, companies are under a ton of pressure to minimize their carbon footprint, reduce energy consumption, and implement eco-friendly practices throughout the software development lifecycle. 

The “S” or the social component is measured based on the work environment (diversity and inclusivity). This is going to be crucial for attracting and retaining talent. 

And lastly, when it comes to the governance of technology - the focus is on using data ethically and being transparent when making decisions. Data privacy is a focal point, especially now with six million data records being exposed in the first quarter of 2023.

Finding Your Solution

Sustainable IT isn’t an easy or replicable task but it’s absolutely necessary for companies to prioritize as we go forward with heightened environmental and ethical awareness. Custom software is a massive influence in this sense as it’s the focus of sustainable technology and can completely change the image of a company looking to improve its ESG.

These are some ways custom software enhances this process:

ESG practices for custom software development are like an umbrella that encompasses the process of tracking, managing, improving, and repeat. Microsoft is one of the best examples of this, and they check each box adequately:

Environmental sustainability: Microsoft wants to become carbon-negative by 2030 and to remove all the carbon it has emitted since it was founded by 2050. The company also invested in renewable energy and has implemented sustainable practices in its offices and data centers.

Social responsibility: Microsoft has implemented a handful of social responsibility initiatives, like giving $3.2 billion in donated and discounted technology to over 300,000 nonprofits serving over 1.2 billion people globally.

Governance practices: In the ESG report from Microsoft, they talk about prioritizing transparency, accountability, and ethical decision-making (As you would hope). In addition, the company has also set goals to improve its cybersecurity and data privacy practices. 

Managing and tracking this entire process in addition to the logistics aspect of technical adjustments are made possible through custom software. KPI monitoring, automating workflows, IoT tracking of energy usage, scalable metrics, and accessible data storage systems, all fall under the IT umbrella. 

Not Investing in Technology 

One way or another, the market is headed in this direction - companies who don’t pivot can expect the following: 

Missed Opportunities: Stakeholders are looking at ESG as a benchmark of a company's longevity. Without it, companies are going to struggle to attract environmentally and socially conscious customers as well as investors.

Increased Risk: Without adequate technology investments in data security and privacy, companies run the risk of data breaches and cyberattacks. These incidents can not only damage the company's reputation but also lead to financial losses and legal liabilities.

Competition: Imagine your competitor not investing in ESG practices, but you do. Would you say you have a leg up when it comes to marketability? If your answer is yes - why are you still in the reversed role?

ESG Going Forward

The futures for both ESG and technology are promising, and their relevance in the marketplace is only expected to grow. How will the two merge? Will AI embody quality assurance managers for companies' ESG practices? How will your company leverage each component?

Most companies don’t know where to begin, which is why we created this free tool to get you started on the right foot. While it won’t create an ESG plan for you, it can help you make informed decisions and navigate the dynamic landscape of sustainability and technology.

Written By Ben Brown

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ISU Corp is an award-winning software development company, with over 17 years of experience in multiple industries, providing cost-effective custom software development, technology management, and IT outsourcing.

Our unique owners’ mindset reduces development costs and fast-tracks timelines. We help craft the specifications of your project based on your company's needs, to produce the best ROI. Find out why startups, all the way to Fortune 500 companies like General Electric, Heinz, and many others have trusted us with their projects. Contact us here.

5 Skills Needed to Work in Tech Today

As each passing day raises new concerns surrounding the implications of AI, there’s a lot of speculation from workers about what it takes to become indispensable. The thing about this is that it’s not a matter of what you do, but how you continue to do it. As someone who provides value to your industry, you need to adjust to its demands and pay attention to what’s required because that’s what’s going to set your efforts apart long-term.

Artificial intelligence is bound to make people feel that they have to be tech-savvy and understand how to leverage these new tools at maximum capacity. In reality, this may be far-fetched, because there are prerequisites and foundational skills that go beyond technical expertise for workers today and it starts with communication and problem-solving. 

The way AI is evolving suggests that it needs guidance from experts, people who can identify the problems and tasks that the system will solve in the first place. With that said, nothing is slowing down the trajectory of AI anytime soon, so with these prerequisites and foundational skills locked down, here are the areas tech workers need to focus on:

Cloud Computing

This is likely the most fundamental tool needed to develop high-performing, scalable platforms and applications, especially when it comes to AI. Imagine you're a project manager building an application for a telecommunications company that monitors network performance and predicts network failures.

Two aspects of cloud computing you’ll want to focus on might include the following:

• Infrastructure as a Service (IaaS): Understand how to provide and manage virtual machines, storage, and networking resources in the cloud. This is going to demand familiarity with provider offerings, such as AWS EC2, Azure Virtual Machines, or Google Compute Engine, and how to configure and scale these resources to meet the application's requirements.

• Platform as a Service (PaaS): You’ll need platform-level services from cloud providers that streamline app development and deployment. This can include services like Azure App Service, AWS Elastic Beanstalk, or Google App Engine since they offer pre-configured environments for deployment without you having to worry about managing the underlying infrastructure.

Machine Learning

This arguably could have been number 1 since it’s what makes AI as versatile and convenient as it is. In 2021, of all the use cases for machine learning, improving the customer experience accounted for 57% of companies worldwide. 

Two key principles of machine learning that workers should gain familiarity with include the following:

• Unsupervised Machine Learning: Unsupervised learning involves training models on unlabeled data to discover patterns or groupings within that data. Clustering algorithms like k-means, hierarchical clustering, or Gaussian mixture models are good options to identify similar data points or clusters. Dimensionality reduction techniques like principal component analysis (PCA) or t-SNE also help to reduce the dimensionality of data (number of dimensions applied) while maintaining and preserving its structure.

• Supervised Learning: Supervised learning is a popular approach we’re seeing with machine learning where models are trained using labelled data (opposite of unsupervised learning). Tech workers will want to understand the concept of input features and target labels, and how algorithms such as linear regression, decision trees, support vector machines (SVM), or neural networks can be applied to learn patterns and make predictions.

Data Science

Data science is interesting because it combines elements of math, statistics, computer science, and domain knowledge as a means to analyze high volumes of data and identify patterns, trends, and relationships that will then be used to make informed decisions and predictions. It's the driver behind data-driven decision making which Bloomberg identifies as “An elusive aspiration for most organizations”. This highlights the untapped potential of data science since it’s clear organizations recognize the potential value of their data but struggle to turn it into actionable insights. 

Two key aspects of data science for workers to know going forward include the following:

• Data mining: Remember those high volumes of data we mentioned? Well, data mining is what’s going to allow workers to identify those patterns, trends, and relationships we mentioned using algorithms and techniques. Properly leveraging data mining is what’s going to remediate that data overload and turn it into actionable insights.

• Data visualization: This practice involves representing data in visual formats such as dashboards, graphs, charts, and maps. The ability to create clear and concise visual representations of data is crucial for workers to communicate findings, drive that data-driven decision-making processes, and foster a culture of data literacy within their organization. Proficiency in this is an indispensable skill…

Deep Learning

Deep learning is a subset of machine learning that trains neural networks to understand things and be able to make decisions and predictions without being directly programmed to do so. A key differentiator between machine learning and deep learning is that deep learning models excel at handling unstructured and high-dimensional data like audio, images, and text. Deep learning is something that’s going to push the envelope when it comes to what machines can achieve which makes it crucial for tech workers to understand how to leverage it in their work.

Here are two key aspects of deep learning for tech workers to focus on:

• Neural Network Architectures: Understanding different types of neural network architectures is essential in deep learning. For instance, convolutional Neural Networks (CNNs) are commonly used for computer vision tasks, Recurrent Neural Networks (RNNs) are great for sequential data analysis, and Generative Adversarial Networks (GANs) are primed for generating new content. As a tech worker, it’s a great idea to study these architectures and be able to recognize what model is best for different tasks. 

• Training and Optimization: Deep learning models require a lot of computational resources and training to achieve high-level performance. Tech workers need to know various optimization techniques such as gradient descent, backpropagation, and regularization methods (Such as L1, L2, and Dropout) to train deep neural networks effectively. Additionally, understanding techniques like transfer learning or pre-trained models might just help leverage existing knowledge and reduce the training time for specific tasks.

Internet of Things (IoT)

IoT technology is reshaping industries across the globe and ultimately changing the way we interact with our surroundings. Above all else, IoT technology gauges where a business's systems are in terms of performance and enables them to leverage data-driven decision-making. 

Two key aspects of IoT for tech workers to become familiar with:

• Connectivity and Integration: IoT revolves around the premise that having various interconnected devices, sensors, and systems can create a network of objects. Workers need to understand the logistics and technology behind IoT connectivity, such as wireless protocols (e.g., Wi-Fi, Bluetooth, Zigbee), network infrastructure (e.g., edge computing, cloud platforms), and data transmission protocols (e.g., MQTT, CoAP). This is effectively going to let you design, implement, and manage IoT solutions, which ultimately leads to seamless communication and interoperability between the different components.

• Industry-specific Knowledge: You need to understand how to tailor IoT solutions to the specific needs of your sector. For example, healthcare workers might use IoT applications in remote patient monitoring, while manufacturing workers may focus on IoT-enabled predictive maintenance. In essence, it’s not a one size fits all approach, but if you know the industry (Or industries) you’re serving - you can add a lot of value that will be hard to replace. 

The Takeaway

People still have a lot of value to bring to the workforce that compliments the unique potential of artificial intelligence. You have to be willing to try new things and give up old methodologies to move forward. Never fall victim to thinking you know it all, and work like you can never know enough.

Written By Ben Brown

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ISU Corp is an award-winning software development company, with over 17 years of experience in multiple industries, providing cost-effective custom software development, technology management, and IT outsourcing.

Our unique owners’ mindset reduces development costs and fast-tracks timelines. We help craft the specifications of your project based on your company's needs, to produce the best ROI. Find out why startups, all the way to Fortune 500 companies like General Electric, Heinz, and many others have trusted us with their projects. Contact us here.

Financial Verification Software in 2023

One of the biggest challenges facing the growth of financial technology is a lack of control when verifying user information. This is a serious issue, especially considering the role these services play in our day-to-day lives.

With FinTech having transformed the way people manage their money, the need for data safety cannot be overstated. In this article, we will look at why this issue is so significant for companies of all sizes and what can be done to mitigate the risk. 

The Importance of FinTech Security

Fintech security can be compared to a secure home. Just like you wouldn't leave the windows and doors of your house unlocked, fintech companies cannot put their platforms at risk of being broken into. The security systems FinTechs use in this case becomes the home security system except for a millionfold the number of members.

What The Research is Telling Us

Last year, research found that more than 50% of financial institutions were impacted by cybersecurity breaches, which is a 21% increase from the previous year. Additionally, more than 40% of these attacks were aimed at small to mid-sized businesses of which only 14% have the resources to defend themselves.

And lastly, a survey last year found that over 20% of US companies who did face an attack lost between $100,000 to nearly $500,000, with 4% losing over one million dollars.

Options Moving Forward

As we consider the best options for financial firms to maintain the security of their platforms in 2023, one of the most relevant and pressing topics in the sector is KYC (Know Your Customer) software. Before delving into other facets, let's take a closer look at this aspect of fintech security:

Defining KYC: In simple terms, KYC is the process of confirming the identity of your clients and checking that they aren’t involved in any illegal activities. KYC software is an automation tool that supports financial institutions, which includes fintech businesses, in meeting regulations and mitigating any possibility of misconduct.

The software simplifies the customer onboarding process by collecting and verifying their personal information. It then cross-references the information with various databases. 

The process is mandatory when opening/maintaining bank accounts in the United States and Canada, as well as in several other countries. This is certainly for good reason as taking on new customers poses plenty of risk without proper verification processes.

This is why every startup needs to strategize and prepare for these contingencies. Yep, it starts that early, and as we said earlier, it’s the small to mid-size institutions that are targeted the most and impacted the hardest.

Now, although KYC is important, it is not the only component needed to ensure your platform is secure. Other aspects include:

• Customer Due Diligence (CDD): This is half the process of KYC as this is what collects and cross-references the information financial institutions use to determine the risk customers pose to the institution.

• Anti Money Laundering (AML): AML goes hand in hand with KYC since KYC is merely a component of AML technology. It’s designed to prevent any illicit activity such as money laundering or other offences alike. 

• Fraud Detection Software: This technology analyzes transactions and flags anything that comes across as unusual or suspicious based on pre-determined criteria. This helps to quickly identify potential fraud and minimize the risk of revenue loss.

Again, we’ve emphasized that the financial institutions that prioritize meeting regulatory requirements using these processes will be better equipped to handle cyberattacks and reduce the risk of data breaches, financial losses, and damage to the company’s reputation. 

Investing in the right financial verification software not only meets regulatory requirements but also gives clients peace of mind knowing their information is protected. Aside from the direct risks facing firms in terms of security, it’s said that the vast majority of customers won’t stay with platforms that poorly integrate KYC guidelines.

The Takeaway

Financial firms need to consider how KYC fits into their platform. Is it already a high priority? Do your customers find it annoying? The performance of your platform is meaningless if the experience is not enjoyable for your users. This means that consistently evaluating your platform and getting the necessary help will set up any firm for success in the long run. 

Written By Ben Brown

—

ISU Corp is an award-winning software development company, with over 17 years of experience in multiple industries, providing cost-effective custom software development, technology management, and IT outsourcing.

Our unique owners’ mindset reduces development costs and fast-tracks timelines. We help craft the specifications of your project based on your company's needs, to produce the best ROI. Find out why startups, all the way to fortune 500 companies like General Electric, Heinz, and many others have trusted us with their projects. Contact us here.