By Oliver Paterson, Director of Product Management, VIPRE Security Group

Most organisations today are Microsoft software houses. Microsoft 365 is the go-to productivity suite, offering comprehensive tools, flexible licensing, and built-in security features. Employees live and breathe in Outlook, and so many different technologies seamlessly integrate with this indispensable communication tool to deliver productivity gains to business professionals.

However, email-borne cyber threats continue to surge. Malware delivered via email is exponentially increasing. .eml attachments, which often get overlooked in phishing emails, are growing. Cybercriminals are resorting to email scams, alongside phishing emails, and with the arrival of generative AI technologies, users are increasingly finding it challenging to spot these “expertly” written, persuasive emails too. 

The reason for this growth in email-led attacks? Cybercriminals are exploiting the ubiquity of Microsoft – and indeed our trust in the software. It is no wonder that today Microsoft is the most spoofed URL.

Microsoft, a software powerhouse, but not an email specialist

Microsoft is undeniably a technology powerhouse, but its primary focus or specialty isn’t email security. Historically centered on infrastructure, operating systems, and cloud services, email security is a small part of its vast ecosystem. For example, while the company offers features like SafeLinks and SafeAttachments to protect against phishing scams, these are often limited to the priciest licenses. As a result, many organisations aren’t able to benefit from the depth of functionality that is needed for robust email protection.

The shortcomings of Microsoft’s security tiers

Microsoft offers a range of security packages for its Microsoft 365 and Office 365 suites, from E1 and E3 to the premium E5. While this tiered approach allows organisations to tailor licenses to employee roles, it also introduces vulnerabilities. Higher-tier subscriptions like E5 provide advanced security, but they’re costly. Lower-tier licenses often lack critical protections against impersonation and zero-day threats—gaps that cybercriminals eagerly exploit.

Furthermore, Microsoft’s user caps (e.g., 300 users on Business Premium) sometimes can lead organisations to make risky compromises in pursuit of cost savings. This mix-and-match strategy can result in blind spots, as lower-tier subscriptions typically lack advanced threat visibility tools, hampering investigation and response times.

Configuration conundrums

The Microsoft security portal, while comprehensive, is also complex. Take Link Protection (aka Microsoft SafeLinks) as an example. This feature needs enabling in multiple locations, and with Microsoft’s routine updates, these settings can be moved, altered, or even disabled by default. Such inadvertent misconfigurations not only pose security risks but also burden IT teams with constant vigilance and reconfiguration.

Static intelligence versus real-time threats

Microsoft’s reliance on third-party security feeds means its threat intelligence is often outdated. The company’s vast and complex platform requires time-consuming updates, and with email security being just one part of its portfolio, critical updates may not always be prioritised. A delay of even a day or two is all a zero-day attack needs to succeed.

A layered approach to email security

So what can organisations do? In an era where a single email can cripple a business, firms need to bolster Microsoft 365’s standard security. By understanding its limitations and layering on specialised protection, organisations can fortify their email defenses, with additional, advanced security capabilities, without breaking the bank. Due to the relentless onslaught of threat actors,  such caution is essential.

Capabilities such as Link Isolation and Sandboxing are vital today to protect against zero-day threats. Link Isolation renders malicious URLs harmless, while Sandboxing automatically isolates suspicious files in a virtual environment for safe analysis. These methods provide real-time monitoring and intelligence, enabling proactive defense.

No matter how advanced technology gets, it alone can’t solve everything. User awareness is key, and “in-the-moment” training trumps the typical periodic sessions for cybersecurity education. When users are immediately informed why an email or attachment was blocked, along with the telltale signs of malice, the lesson is more likely to stick.

Many organisations, and especially the smaller and growing firms, can’t afford top-tier Microsoft licenses for all employees or indeed maintain in-house IT teams to address the gaps in security capabilities. Partnering with third-party security services providers across different aspects of the function is a viable option as no single software or platform can provide all the security techniques and capabilities. This approach is not only more cost-effective but also provides the technological expertise needed for protection in today’s rapidly evolving threat landscape. Reducing reliance on a single security provider is an astute approach to minimising business risk.

by Nada Ali Redha, Founder of PLIM Finance

Artificial Intelligence (AI) has transformed countless industries, and fintech is no exception. The evolution of AI technology is revolutionising how financial services operate, particularly in the Buy Now, Pay Later (BNPL) space. As the Founder and CEO of PLIM Finance—a BNPL service that specialises in the medical aesthetics industry—I have witnessed firsthand how AI can be leveraged to enhance both user experience and operational efficiency.

In the BNPL sector, AI and machine learning are essential tools for understanding and predicting consumer behaviour. BNPL providers often face the high-risk challenge of defaults, where consumers fail to make their scheduled payments. This is a critical issue for any BNPL provider, as defaults can impact the company’s profitability and reputation.

At PLIM Finance, we use AI-driven tools to manage defaults and failed payments. The power of AI in this context lies in its ability to learn from historical data and predict payment failures with remarkable accuracy. By analysing patterns in consumer spending, repayment behaviours, and other relevant factors, AI systems can forecast which payments are most likely to default. This predictive capability allows us to take proactive measures to manage and reduce defaults, safeguarding both our customers’ financial health and our own.

While we do not currently use AI to assess creditworthiness at PLIM Finance, AI’s potential in real-time risk assessment is unquestionable. Traditional credit assessment methods rely on static data, such as credit scores and income statements, which may not always reflect a consumer’s current financial situation. AI, however, can offer a more dynamic and holistic approach.

AI-driven systems can continuously analyse a variety of data sources, including transaction histories, spending patterns, and even social behaviours, to build a more comprehensive risk profile for each customer. This enables BNPL providers to make more informed lending decisions, tailoring financing options that align with each user’s ability to repay. Although PLIM has yet to implement AI in creditworthiness assessment, we recognise its potential to improve decision-making processes over traditional methods.

AI has a crucial role in combating fraud within the financial services sector, including BNPL platforms. Fraud detection is a multi-faceted challenge that requires constant vigilance and real-time analysis. AI is uniquely equipped to tackle this problem due to its capacity for processing vast amounts of data quickly and identifying suspicious patterns or anomalies that could indicate fraudulent activity.

At PLIM Finance, we leverage AI’s ability to apply collective data learning to make real-time decisions, thus reducing the likelihood of fraudulent activities going unnoticed. For instance, AI can detect unusual spending patterns or behaviours that deviate from a user’s normal financial activity, triggering alerts for further investigation. This proactive approach has proven to be highly effective in minimising financial losses and ensuring a safer environment for our users.

One of the most impactful benefits of AI in the BNPL space is the enhancement of customer engagement and satisfaction. AI allows companies to offer personalised, tailor-made services that resonate with each consumer’s specific needs. In the context of PLIM Finance, AI helps us recommend financing options based on individual preferences and past behaviours, streamlining the user’s journey.

Higher customer satisfaction often translates into increased loyalty and trust in the brand. By utilising AI to provide relevant recommendations and support, we can meet our customers where they are in their financial journey, helping them make informed decisions. This, in turn, creates a positive user experience that distinguishes our services from those of traditional lending institutions.

Despite its numerous benefits, implementing AI in BNPL services is not without challenges, especially concerning data privacy, algorithmic fairness, and transparency. One of the primary concerns in any AI application is bias in the data. AI systems learn from historical data, which may not be entirely representative of the diverse range of consumers who use BNPL services. Until we can source data from a wide variety of demographic and socioeconomic backgrounds, there is a risk that AI-driven decisions could inadvertently favour certain groups over others.

Transparency in AI decision-making is another ethical consideration. Customers need to trust that their data is being used responsibly and that AI algorithms are making fair, unbiased lending decisions. To address these concerns, it is crucial to maintain transparency about how AI models are built, what data they use, and how decisions are made. Additionally, complying with data privacy regulations, such as the General Data Protection Regulation (GDPR) in Europe, is essential to protect consumer rights.

AI’s role in the BNPL industry will continue to evolve as technology advances and more data becomes available. At PLIM Finance, we are excited about the future possibilities that AI presents, from more accurate risk assessment to enhancing customer satisfaction. By continuously improving our AI-driven tools and addressing the ethical challenges associated with their use, we aim to create a more inclusive, secure, and user-friendly BNPL experience.

In conclusion, the impact of AI in the fintech industry, particularly in the BNPL space, is profound. It offers solutions to key challenges, including managing defaults, fraud detection, and customer engagement, all while providing an opportunity to enhance the overall user experience. However, as we embrace these technological advancements, it is equally important to navigate the ethical concerns thoughtfully, ensuring that AI serves as a tool for positive financial inclusion.

By Joman Kwong, Strategic Solutions Manager, Financial Services, at Laserfiche

If the mortgage process wasn’t already complex enough, the current state of the UK economy is adding even more fuel to the fire. First-time buyers are likely to spend over one-third of their pay on mortgage payments. And with advanced technologies becoming increasingly accessible and integrated into consumers’ lives, people have little patience for outdated technology and unnecessarily disjointed processes. In fact, 64% of consumers are now more likely to choose fintechs over traditional banks.

Yet, digital transformation in the mortgage industry remains a challenge. Leaders are likelier to stick with tried-and-trusted processes, particularly when sensitive information is at stake. The mortgage industry is also an archaic one, with loans first offered in the UK around the 12^th century.  But now, 21^st century technology is set to bring this historic industry into the present, making legacy processes and tenuous paperwork a thing of the past.

By utilising the vast array of digital tools on offer, mortgage providers can refresh their systems and processes to provide a better, more streamlined customer experience. Lenders can expedite mortgage processes when every decision is backed by precise data collection and analysis, and systems are in place to organise, access and manage customer information.

Utilising AI to free up time for human employees

Many financial institutions have already started to integrate artificial intelligence (AI) into their systems and processes to great effect. AI makes it easier than ever before to streamline capturing and classifying data to make content searchable from one centralised, organised place. Employees no longer need to trawl through documents manually but can rely on AI to source documents by using keywords, metadata, annotations, file names and more.

Employees take back valuable time when they are no longer bogged down with manual tasks; for example, filling out and filing documents can now be automated. The result is more time,      headspace, and energy to provide personalised customer service. Tools such as AI-powered chatbots are also becoming increasingly popular as an in-app banking feature, providing customers with 360 support anytime, anywhere. Chatbots can also facilitate more personalised, guided experiences when customers are reviewing forms or searching through websites, ensuring that they feel supported every step of the way.

The role of hyperautomation in breaking down siloes

Many mortgage lenders and financial institutions have already invested in automation but currently utilise single-point solutions that are earmarked for specific tasks. The result can be disjointed end processes, resulting in slower services for end users. Hyperautomation, therefore, can play a fundamental role in improving the total experience within financial institutions. End-to-end solutions make it easy to automate manual tasks and expedite data entry and approval routing. Leaders are no longer hampered by siloed data and unstructured data sets, which can lead to issues such as multiple versions of pieces of digital content with no ability to track them.

Hyperautomation reduces the likelihood of important documentation – such as sales contracts and datasheets – getting lost in the ‘digital noise’. It brings together business processes across different applications and departments to ensure better useability for employees and customers alike.

In the mortgage sector, hyperautomation tools can also make it possible to fill the gaps between mortgage origination and other business applications, expediting underwriting and mortgage review workflows. For example, by deploying a process orchestration engine, a mortgage lender could provide an accessible interface where customers or brokers could easily submit a mortgage application with all the supporting documents. After the first round of interviews, the provider could then route data into the core banking software and loan origination system for processing, eliminating any duplicate or manual data entries. Feeding data directly to the core banking software in this way also provides employees quick and easy access to customers’ personal information, all via one single interface. Hyperautomation will drive improved visibility across every process, speeding up operations and driving better CX as a result.

Streamlined customer experiences stem from connected processes

When customers are looking to obtain a mortgage, they are still faced with many time-consuming manual tasks such as document collection and income verification. Customers understandably become frustrated with disjointed verification processes, where they are asked to input the same security information multiple times. Fragmented processes occur due to a lack of data integration.      Organisations can avoid the risks associated with data being stored in multiple places when every system and process is connected. Connecting every system and process also encourages customer loyalty and satisfaction because applications work efficiently, intuitively and with the click of a button.

So, what does this look like in practice? Mortgage providers can create a ‘single source of truth’ by bringing together loan origination systems with core banking software, so that mortgage specialists can access real-time information without needing to jump between applications. From augmenting credit checks to speeding up underwriting procedures to streamlined review and approval processes, the opportunities for transformation are endless.

Looking towards the future of the mortgage sector

We’ve seen how AI-empowered tools can help customer service representatives quickly retrieve a document or copy of a signature directly from a cloud-based system. As operations within the sector digitally transform, the benefits will be felt by all stakeholders, from employees to customers to shareholders. Process automation tools are already helping innovative financial institutions enhance the customer experience as they integrate unparalleled levels of connectivity into their offerings.

A process as complex as securing a mortgage will never be hurdle-free, but introducing digital tools will help make the journey towards attaining a mortgage significantly smoother. And it’s not just customers that will benefit. A well-equipped workforce that has easy access to systems that organise and manage data can provide a more efficient service, boosting both productivity and customer satisfaction. The time to invest in tools that will help supercharge how you provide your financial offerings is now. The business benefits will be felt for years to come.