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What financial services firms need to know about digital transformation

Source: Finance Derivative

By Winnie Palmer, EMEA Head of Marketing, Seismic

The financial services (FS) industry has undergone a tremendous amount of change over the last two decades. Technology has accelerated product and service innovation, yet the spread that traditional lenders and money managers can command has been going down – putting a considerable amount of pressure on revenues.

What’s more, clients are increasingly demanding highly personalised experiences at a similar standard to what they are used to from digital-first firms like Amazon and Netflix, while new channels such as social media are becoming increasingly important.

FS firms have responded to these market shifts with increased investments into digital products and systems, accelerating their digital transformation journey. Ironically, this is causing a new challenge in organisations’ ability to deliver meaningful client experiences as the amount of digital content explodes. It is simply harder than ever for clients to sieve through the vast amount of competing information. That said, clients are indeed looking for content on digital channels of their choice, with two out of three buyers now preferring remote interactions and digital self-service at all stages of the buying cycle. This begs the question how can FS firms ensure that their content will cut through the clutter and resonate with each client’s individual needs?

The good news is that technology continues to offer greater capabilities for FS firms. For example, the ability to analyse patterns, personalise recommendations and disseminate intelligence is greater than ever before. The most successful FS firms are using these technologies to increase their operational efficiency and advisors’ effectiveness to deliver superior client experiences. So, when we consider the future of the FS industry, how must firms adapt as competition increases and client expectations continue to evolve?

Building for success

Establishing a culture of continuous learning and development is critical to the long-term success of any digital transformation project. This can help FS firms truly differentiate themselves and their advisors from the competition, enabling their client-facing teams to replicate the organisation’s star players and enhance their level of performance.

Firms should focus on making coaching and training readily available through cwhenever and wherever they are needed. By delivering timely, data-informed recommendations and insights, these platforms can enable financial advisors and money managers to improve their learning speed and knowledge retention. This in-the-moment coaching provides them with the ammo they need to craft and deliver content that truly delights and engages clients.

For example, training programmes delivered through interactive lessons embedded with practice sessions and playbooks that are based on what’s proven to have driven impact in past client scenarios – all tailored to the specific advisor – can help FS teams deliver more engaging and impactful experiences. Leveraging granular performance data, digital platforms can provide insights and recommendations to guide advisers on what to say, do, and show clients at certain stages of the sales cycle. As well as ensuring more effective interactions, this dynamic approach to skill development means advisors can spend more time engaging with clients as they continuously learn and develop.

This is all key to building long-term relationships in today’s FS market. By establishing a culture that focuses on continuous learning powered by intelligent and data-informed training and coaching platforms delivered at the moment of need, FS firms can be confident that their advisors are equipped with the most relevant skills and knowledge – no matter where they are in their career.

Driving operational efficiency at scale

Modernising and optimising data processes through automation is another vital cog in the digital transformation machine. The strict regulatory nature of the FS sector means that compliance risks are a key concern. Leveraging technology can enable FS firms to systematically ensure governance and compliance both company-wide and at an individual level – all while reducing costs and increasing their advisors’ productivity.

Centralising these data processes supports FS teams when working with a wide range of assets such as quarterly reports, fact sheets and meeting reviews. Advisors can quickly modify any information based on materials dynamically served from a single source of truth whenever it’s needed without impacting compliance in order to accelerate the approvals process. Integrating these systems across sales, content training and CRM tools will further improve the user experience, ultimately helping financial advisors be more productive and focused on revenue-driving activities.

These technology platforms can also provide key data insights using AI capabilities to help identify behaviours, patterns, and new revenue opportunities from large data sets that would be impossible to analyse manually, thereby driving further impact, faster.

For example, FS firms can leverage these insights to improve the effectiveness of each piece of content they share with clients. Using the data collected from previous interactions, sellers can gain visibility into what has worked, what needs improving, and where clients have engaged with content the most. Armed with these engagement insights from specific scenarios, firms will have a better understanding of the most impactful content, along with when and how it should be delivered. Also, by linking content investment directly to sales performance, organisations can be more intelligent in identifying cost saving opportunities while maximising effectiveness.

Superior client experiences

As financial advisors engage more with the younger generation of tech savvy clients, they need to be able to communicate and interact with these clients in the way they desire, delivering more personal experiences and dynamic interactions. In today’s competitive FS marketplace, this is key to meeting the expectations and needs of the modern client.

This is where content engagement data has a vital role to play. Knowledge of exactly how, when and where customers are interacting with pieces of content allows FS professionals to provide a more agile and responsive experience. It lets them tailor each interaction – whether through e-mail, digital sales rooms, social media, or in-person meetings – to the individual.

The key data insights and recommendations that powerful cloud-based platforms provide allow advisors to build meaningful relationships, even in digital and remote environments. Being able to build trust with clients by demonstrating that they understand their unique needs and situation will help advisors engage more effectively and put them ahead of the competition.

Establishing these trusted relationships with younger generations will be invaluable over the years to come as they inherit wealth from their parents and build their own. In what has become a digital marketplace, FS firms must help their teams engage prospective clients with the right content, at the right time, in the right channels – all in a compliant manner. This can only be achieved by tapping into data insights and technologies that enable hyper-personalisation consistently at scale.

This three-pronged approach that focuses on continuous learning, enhanced operations and powerful client experiences must be at the core of any FS firms’ digital transformation strategy. This is what will enable truly holistic transformations, unlocking new revenue generating opportunities and giving firms the tools to succeed in today’s complex and competitive FS environment.

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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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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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