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Why banks are right now at that ‘Change or Die’ crossroads

Source: Finance Derivative

Change is often difficult, time-consuming and expensive. But ignore it at your peril. For years, business change of course has centred around digital transformation, what else? Here, the banking sector is not the first thing that springs to mind, nor is it the definition of cutting edge. The truth is that banks have reached a crossroads and need to seriously adapt their businesses now or, over the next few years, some brands may disappear altogether. As the old cliche says: change or die.

It’s time for action

A report from The Financial Times Focus (FT Focus) illustrates the urgency for banks to modernise their offering. Not only do two in three banks expect to lose market share unless they embrace digitisation, but 58% of respondents predict they will cease to exist completely in the next five to ten years, if they fail to change their business models. Wow, that’s a frightening prediction and one that I don’t believe exists in any other sector, making it the ultimate driver for change.

The report goes on to say that with 74% of respondents predicting that technology giants such as Amazon and Google will hold the largest market share of the banking industry within just five years, now is the time for action. I do wonder which brands will fail to achieve enough change and be lost to history.

Making change actually stick

One major obstacle as banks transform digitally is the fact that they cannot let go of their outdated legacy systems. They look even further behind when you consider the likes of Apple, Airbnb, Amazon, Google, Netflix and Uber and how they are actually transforming modern life for all of us. And that customer viewpoint is an important consideration for banks as they have many neo-banks and fintech apps snapping at their heels ready to hoover up their customers if they are perceived to have made the slightest slip.

What is still holding banks back? With constantly shifting goalposts due to changing markets and expectations, reaching that ‘digitally transformed state’ is in reality unachievable. Rather, it becomes a process of continuous evolution as new systems/projects are introduced over the short, medium and long term.

Some banks are grabbing the headlines, for example JP Morgan Chase is moving as much as 50% of its applications and data to the cloud in 2022. Given increasing customer demands and market pressures, as well as the need to respond to world events, it makes sense that banks need to start thinking like technology companies, that’s why the same bank invests $12 billion per year on technology.

Covid sped up the digital transformation process in banking ‘a great deal’ (60% according to Statista) but it is still lagging way behind other sectors with Technology (78%), perhaps predictably topping the list, but also Healthcare (74%), Retail & Ecommerce (70%), and Manufacturing (65%).

Not only do banks appear slow to react to such a crisis, but they are still just dipping their toes in the digital water, with only 27% launching a digital transformation strategy last year.

Furthermore, according to Cornerstone Advisors, seven in 10 banks don’t plan to replace their core systems as part of their digital transformation. In addition, few have deployed—or plan to deploy—core integration/middleware platforms or payment hubs. Without these platforms and without replacing the legacy systems, the promise of real digital transformation will be difficult to attain.

It paints an even bleaker picture when we consider that 70% of transformation projects within financial institutions fail altogether and deliver no meaningful return on investment. Clearly it’s time for them to up their game and use the technology shifts in the market to their advantage.

What does Digital Transformation mean for banks?

When done right, the billions being invested in digital initiatives makes good business sense and delivers a win-win for both customers and banks. Customers enjoy better experiences and the convenience of accessing services across multiple devices; while banks see improved process efficiency through automation.

With customers able to do more online safely and securely, trust in the brand grows, and they can enjoy a more personalised offering with better customer engagement.

Banks benefit in a number of ways too. Not least, increased revenue and client satisfaction due to 24/7 always-on services. Acquisition of new customers becomes cheaper and easier. Better customer engagement stems from leveraging client data. Account management and support become easier via digitised paperwork. Digital transformation enables organisations to build an environment of ongoing innovation and adaptability vital for future growth.

Ultimately, what this means operationally is a huge number of efficiencies, not least: elimination of paperwork; less time spent servicing clients; increased productivity; organisational transparency; effective teamwork; lower operational costs; and risk reduction in core activities.

The challenges facing banks

Bank CIOs and Digital Transformation Leaders clearly do not have an easy job. But with massive budgets on the table surely they can buy their way out of this?

Arguably banks are simply playing catch-up, making investments and changes that should have been made five (or more) years ago.

Not helping the matter is the significant developer skills shortage, which makes it difficult for firms to hire the right technical resources to support projects, and the fact that some projects can take up to 18 months to complete with a traditional development approach.

Furthermore, by the time one area has been tackled, the market has often moved on once again, and the ‘new’ solution is no longer quite as new.

How low-code can help

Business Process Automation is of course vital for banks to achieve any sort of digital transformation. One solution that will help banks meet current, and future, challenges is using low-code in their automation. In fact, Gartner analyst Milind Govekar predicts that 70% of new applications will be developed using low-code or no-code techniques by 2025.

A low-code platform enables organisations to achieve a rapid rate of change with minimal effort, coupled with fast delivery. This is because low-code enables the building and updating of process applications with reduced coding. The traditional hand-coding approach is replaced with an intuitive visual development style. Here, drag and drop user interfaces are used to add different types of elements, such as connection to databases, other software applications or logic elements, and even blockchain implementations.

This reduction in code requirements drastically accelerates development timelines, both for new application builds and change requirements to existing processes. The organisation becomes more agile as a result, and is able to achieve significant gains in operational efficiency without any breaks in governance. In other words, low-code makes complex automation easy and accessible, in a highly streamlined and comprehensive workflow.

CEC Bank, one of the largest financial institutions in Romania, used the Aurachain low-code platform to accelerate digital transformation in three critical areas: an integrated system for monitoring and maintenance of the bank’s ATM and POS fleet, a fully digital onboarding process for new SME customers, and the digitalization of online trade finance solutions for SMEs. Key benefits include an automated platform that achieves high reliability, availability and maintainability of key business services for ATM/POS. In addition, the new onboarding process automates complex workflows, incorporating business rules and actions; implements a single user interface across systems and processes; can be quickly tailored to incorporate internal or regulatory governance processes.

Customer-First Priority Areas

How should banks focus their considerable budgets now to ensure digital transformation success?

The first step is vital to get right: the strategy must focus first and foremost on the customer. Here, automating processes to create a seamless CX plays a major role. In addition, customer data must be used to create more personalised services and products.

Delivering an omnichannel offering is not only important, but expected by customers. Significant technology investments are required to compete with new fintech companies, online banks and challenger banks – as well as meet ever-climbing customer expectations. Not surprisingly, finding specialised business transformation talent to develop such solutions is critical.

The Future

Within financial institutions that think they’re three-quarters of the way through their digital transformation strategy (or more), just 39% implement Robotic Process Automation; and way less are using chatbots or machine learning (according to Cornerstone Advisors). Given the fact that low code is so critical to intelligent business automation, how can they seriously be moving towards a digital future without using these technologies? There seem to be some major discrepancies, implying institutions are in fact further away from their goals than they believe.

One thing is clear. With the alternative being possible death, banks need to change now.
Those that step up and put the tech and cultural foundations in place today, including using low-code to achieve process automation, will find themselves well-positioned in the future.

As opportunities arise with more emerging technologies, these organizations will be ready to forge ahead while many others will be falling further behind in the catch-up game.

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Business

Driving business success in today’s data-driven world through data governance

Source: Finance derivative

Andrew Abraham, Global Managing Director, Data Quality, Experian

It’s a well-known fact that we are living through a period of digital transformation, where new technology is revolutionising how we live, learn, and work. However, what this has also led to is a significant increase in data. This data holds immense value, yet many businesses across all sectors struggle to manage it effectively. They often face challenges such as fragmented data silos or lack the expertise and resources to leverage their datasets to the fullest.

As a result, data governance has become an essential topic for executives and industry leaders. In a data-driven world, its importance cannot be overstated. Combine that with governments and regulatory bodies rightly stepping up oversight of the digital world to protect citizens’ private and personal data. This has resulted in businesses also having to comply e with several statutes more accurately and frequently.

We recently conducted some research to gauge businesses’ attitudes toward data governance in today’s economy. The findings are not surprising: 83% of those surveyed acknowledged that data governance should no longer be an afterthought and could give them a strategic advantage. This is especially true for gaining a competitive edge, improving service delivery, and ensuring robust compliance and security measures.

However, the research also showed that businesses face inherent obstacles, including difficulties in integration and scalability and poor data quality, when it comes to managing data effectively and responsibly throughout its lifecycle.

So, what are the three fundamental steps to ensure effective data governance?

Regularly reviewing Data Governance approaches and policies

Understanding your whole data estate, having clarity about who owns the data, and implementing rules to govern its use means being able to assess whether you can operate efficiently and identify where to drive operational improvements. To do that effectively, you need the right data governance framework. Implementing a robust data governance framework will allow businesses to ensure their data is fit for purpose, improves accuracy, and mitigates the detrimental impact of data silos.

The research also found that data governance approaches are typically reviewed annually (46%), with another 47% reviewing it more frequently. Whilst the specific timeframe differs for each business, they should review policies more frequently than annually. Interestingly, 6% of companies surveyed in our research have it under continual review.

Assembling the right team

A strong team is crucial for effective cross-departmental data governance.  

The research identified that almost three-quarters of organisations, particularly in the healthcare industry, are managing data governance in-house. Nearly half of the businesses surveyed had already established dedicated data governance teams to oversee daily operations and mitigate potential security risks.

This strategic investment highlights the proactive approach to enhancing data practices to achieve a competitive edge and improve their financial performance. The emphasis on organisational focus highlights the pivotal role of dedicated teams in upholding data integrity and compliance standards.

Choose data governance investments wisely

With AI changing how businesses are run and being seen as a critical differentiator, nearly three-quarters of our research said data governance is the cornerstone to better AI. Why? Effective data governance is essential for optimising AI capabilities, improving data quality, automated access control, metadata management, data security, and integration.

In addition, almost every business surveyed said it will invest in its data governance approaches in the next two years. This includes investing in high-quality technologies and tools and improving data literacy and skills internally.  

Regarding automation, the research showed that under half currently use automated tools or technologies for data governance; 48% are exploring options, and 15% said they have no plans.

This shows us a clear appetite for data governance investment, particularly in automated tools and new technologies. These investments also reflect a proactive stance in adapting to technological changes and ensuring robust data management practices that support innovation and sustainable growth.

Looking ahead

Ultimately, the research showed that 86% of businesses recognised the growing importance of data governance over the next five years. This indicates that effective data governance will only increase its importance in navigating digital transformation and regulatory demands.

This means businesses must address challenges like integrating governance into operations, improving data quality, ensuring scalability, and keeping pace with evolving technology to mitigate risks such as compliance failures, security breaches, and data integrity issues.

Embracing automation will also streamline data governance processes, allowing organisations to enhance compliance, strengthen security measures, and boost operational efficiency. By investing strategically in these areas, businesses can gain a competitive advantage, thrive in a data-driven landscape, and effectively manage emerging risks.

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The Benefits of EV Salary Sacrifice: A Guide for Employers and Employees

As the UK government continues to push for greener initiatives, electric cars have become increasingly popular. The main attraction for both employers and employees is the EV salary sacrifice scheme.

By participating in an EV salary sacrifice scheme, both employers and employees can enjoy cost savings and contribute to environmental sustainability along the way! This article will delve into the specifics of how these schemes operate, the financial advantages they offer, and the broader positive impacts on sustainability.

We will provide a comprehensive overview of the mechanics behind EV salary sacrifice schemes and discuss the various ways in which they benefit both employees and employers, ultimately supporting the transition to a greener future in the UK.

What is an EV Salary Sacrifice Scheme?

An EV salary sacrifice scheme is a flexible financial arrangement that permits employees to lease an EV through their employer. The key feature of this scheme is that the leasing cost is deducted directly from the employee’s gross salary before tax and National Insurance contributions are applied. By reducing the taxable income, employees can benefit from substantial savings on both tax and National Insurance payments. This arrangement not only makes EVs more affordable for employees but also aligns with governmental incentives to reduce carbon emissions.

For employers, implementing an EV salary sacrifice scheme can lead to cost efficiencies as well. The reduction in National Insurance contributions on the employee’s reduced gross salary can offset some of the costs associated with administering the scheme. Additionally, such programmes can enhance the overall benefits package offered by the employer, making the company more attractive to prospective and current employees.

Benefits for Employees

1. Tax and National Insurance Savings

By opting for an EV salary sacrifice scheme, employees can benefit from reduced tax and National Insurance contributions. Since the lease payments are made from the gross salary, the taxable income decreases, resulting in substantial savings.

2. Access to Premium EVs

Leading salary sacrifice car schemes often provide access to high-end electric vehicles that might be otherwise unaffordable. Employees can enjoy the latest EV models with advanced features, contributing to a more enjoyable and environmentally friendly driving experience.

3. Lower Running Costs

Electric vehicles typically have lower running costs compared to traditional petrol or diesel cars. With savings on fuel, reduced maintenance costs, and exemptions from certain charges (such as London’s Congestion Charge), employees can enjoy significant long-term financial benefits.

4. Environmental Impact

Driving an electric vehicle reduces the carbon footprint and supports the UK’s goal of achieving net-zero emissions by 2050. Employees can take pride in contributing to a cleaner environment.

Benefits for Employers

1. Attract and Retain Talent

Offering an EV salary sacrifice scheme can enhance an employer’s benefits package, making it more attractive to potential recruits. It also helps in retaining current employees by providing them with valuable and cost-effective benefits.

2. Cost Neutrality

For employers, EV salary sacrifice schemes are often cost-neutral. The savings on National Insurance contributions can offset the administrative costs of running the scheme, making it an economically viable option.

3. Corporate Social Responsibility (CSR)

Implementing an EV salary sacrifice scheme demonstrates a commitment to sustainability and corporate social responsibility. This can improve the company’s public image and align with broader environmental goals.

4. Employee Well-being

Providing employees with a cost-effective means to drive electric vehicles can contribute to their overall well-being. With lower running costs and the convenience of driving a new EV, employees may experience reduced financial stress and increased job satisfaction.

How to Implement an EV Salary Sacrifice Scheme

1. Assess Feasibility

Evaluate whether an EV salary sacrifice scheme is feasible for your organisation. Consider the number of interested employees, potential cost savings, and administrative requirements.

2. Choose a Provider

Select a reputable provider that offers a range of electric vehicles and comprehensive support services. Ensure they can handle the administrative tasks and provide a seamless experience for both the employer and employees.

3. Communicate the Benefits

Educate your employees about the advantages of the scheme. Highlight the financial savings, environmental impact, and access to premium EV models. Provide clear guidance on how they can participate in the programme.

4. Monitor and Review

Regularly review the scheme’s performance to ensure it continues to meet the needs of your employees and the organisation. Gather feedback and make adjustments as necessary to enhance the programme’s effectiveness.

Conclusion

The EV salary sacrifice scheme offers a win-win situation for both employers and employees in the UK. With significant financial savings, access to premium vehicles, and a positive environmental impact, it’s an attractive option for forward-thinking organisations. By implementing such a scheme, employers can demonstrate their commitment to sustainability and employee well-being, while employees can enjoy the benefits of driving an electric vehicle at a reduced cost.

Adopting an EV salary sacrifice scheme is a step towards a greener, more sustainable future for everyone.

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Business

Machine Learning Interpretability for Enhanced Cyber-Threat Attribution

Source: Finance Derivative

By: Dr. Farshad Badie,  Dean of the Faculty of Computer Science and Informatics, Berlin School of Business and Innovation

This editorial explores the crucial role of machine learning (ML) in cyber-threat attribution (CTA) and emphasises the importance of interpretable models for effective attribution.

The Challenge of Cyber-Threat Attribution

Identifying the source of cyberattacks is a complex task due to the tactics employed by threat actors, including:

  • Routing attacks through proxies: Attackers hide their identities by using intermediary servers.
  • Planting false flags: Misleading information is used to divert investigators towards the wrong culprit.
  • Adapting tactics: Threat actors constantly modify their methods to evade detection.

These challenges necessitate accurate and actionable attribution for:

  • Enhanced cybersecurity defences: Understanding attacker strategies enables proactive defence mechanisms.
  • Effective incident response: Swift attribution facilitates containment, damage minimisation, and speedy recovery.
  • Establishing accountability: Identifying attackers deters malicious activities and upholds international norms.

Machine Learning to the Rescue

Traditional machine learning models have laid the foundation, but the evolving cyber threat landscape demands more sophisticated approaches. Deep learning and artificial neural networks hold promise for uncovering hidden patterns and anomalies. However, a key consideration is interpretability.

The Power of Interpretability

Effective attribution requires models that not only deliver precise results but also make them understandable to cybersecurity experts. Interpretability ensures:

  • Transparency: Attribution decisions are not shrouded in complexity but are clear and actionable.
  • Actionable intelligence: Experts can not only detect threats but also understand the “why” behind them.
  • Improved defences: Insights gained from interpretable models inform future defence strategies.

Finding the Right Balance

The ideal model balances accuracy and interpretability. A highly accurate but opaque model hinders understanding, while a readily interpretable but less accurate model provides limited value. Selecting the appropriate model depends on the specific needs of each attribution case.

Interpretability Techniques

Several techniques enhance the interpretability of ML models for cyber-threat attribution:

  • Feature Importance Analysis: Identifies the input data aspects most influential in the model’s decisions, allowing experts to prioritise investigations.
  • Local Interpretability: Explains the model’s predictions for individual instances, revealing why a specific attribution was made.
  • Rule-based Models: Provide clear guidelines for determining the source of cyber threats, promoting transparency and easy understanding.

Challenges and the Path Forward

The lack of transparency in complex ML models hinders their practical application. Explainable AI, a field dedicated to making models more transparent, holds the key to fostering trust and collaboration between human and machine learning. Researchers are continuously refining interpretability techniques, with the ultimate goal being a balance between model power and decision-making transparency.

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