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.

Philip Sheen, Head of Public Sector UKI at UiPath

By its nature, the digital transformation of the public sector has been gradual and guarded. Public sector organisations and governments have limited budgets, lean teams, and a responsibility to act in the interest of the citizens who use supplied services. This context means that the implementation of innovative technologies and ultimately transformation has been conservative by comparison to some other industries.

We are starting to see this approach shift. As more organisations implement and benefit from artificial intelligence (AI) powered solutions, public sector bodies are now considering how and where they can best use AI, with AI-enabled automation now very much part of their future.

As the UK public sector looks to AI and automation to improve the way it works and the services it provides to its citizens. With careful change management it is possible to tackle doubts and allow public sector organisations to realise the power of technology, with people at the centre.

Automation for civil servants

A core challenge for the UK civil service is how it can make efficiencies in customer engagement and cost saving while still enhancing outcomes for citizens. Doing so is a tricky balance, but AI-enabled automation provides a solution.

AI powered automation can help improve the efficiency of government services and free up civil servants’ time to focus on valuable, non-repetitive, tasks. However, many aren’t implementing it, citing reasons such as lean teams, complicated processes and disparate, legacy technology as blockers. It can seem that the adoption of automation feels a long way off.

By removing human and system latency, working across tech platforms and ecosystems to bypass constraints, and orchestrating and providing experiences which better blend together for the end user, the modernisation of the civil service is in reach through automation.

This is especially important in the sector given it often deals with and provides services for some of the most vulnerable in society. Vulnerable citizens need specialised support, whether that’s through faster loan approvals, special assistance with applications or providing accessible services. Not only can automation help make these services a reality, but also free up worker time so they have more time to think about and create more accessible options for those who need them.

Automation for healthcare

Patient waiting lists and waiting times in the UK have soared since COVID. The volume of people on the list for elective treatment has tripled since 2013. Patients are being failed and change needs to happen – AI-enabled automation can help.

The administrative burden in healthcare is high. By driving uniformity across core processes, making the back and middle office more effective – replacing manual processes and tasks and improving workflows – and reducing the resources allocated to these activities, automation can make administrative and support tasks quicker, error free and less costly. The overall impact of this is improved wait times and even better speed and precision in diagnoses.

Automation is a proven pathway to better patience care and experience within the healthcare sector.

Automation in policing

Smaller budgets and targets to keep the police workforce lean has left the industry looking to improve officer and system efficiency. Automation has the ability to help change this, empowering officers with the enhanced skills needed to deliver the best services for the citizens who need them, while focusing on a core part of their job – keeping citizens safe.

This technology can be used in numerous ways, including uploading witness statements to Crown Prosecution Services (CPS) on the go so officers can move from one incident to the next more easily; ensuring paperwork is filled out correctly the first time to avoid mistakes in cases and documents being rejected; and even the automatic redaction of sensitive data in relations to Suspicious Activity Reports (SARs) and Freedom of Information (FOI) requests.

Automation can also support officers when it comes to threat harm risk assessments. By working across constabularies and local authorities, automation can highlight vulnerable individuals, allowing officers to spot and evaluate patterns and react to their situation appropriately.

Looking to an impactful future

Use of AI and automation in public services all comes back to the impact it has on people, whether that is across safety, health or social care. When embedded into organisations and leveraged in the correct way the benefits can be experienced for both citizens and civil servants, but the urgency for change is now.

Source: Finance Derivative

Tetyana Golovata, Head of Regulatory Compliance at IFX Payments

Regulation plays a critical role in shaping the fintech landscape. From Consumer Duty and FCA annual risk reporting to APP fraud, the tectonic plates of the sector are shifting and whether you consider these regulations as benefiting or hindering the industry, businesses are struggling to keep up. 

According to research by fraud prevention fintech Alloy, 93% of respondents said they found it challenging to meet compliance requirements, while in a new study by Davies a third of financial leaders (36%) said their firms had been penalised for compliance breaches in the year to June. With the FCA bringing in its operational resilience rules next March, it is more important than ever to ensure your company makes the grade on compliance. 

Lessons from history

Traditionally, FX has struggled with the challenge of reporting in an ever-developing sector. As regulatory bodies catch up and raise the bar on compliance, responsible providers must help the industry navigate the changes and upcoming deadlines.

Fintechs and payments companies are entering uncharted waters – facing pressure to beat rivals by offering more innovative products. When regulators have struggled to keep up in the past, gaps in legislation haveallowed some opportunists to slip between the net, as seen in the collapse of FTX. Because of this, implementation and standardisation of the rules is necessary to ensure that innovation remains seen as a force for good, and to help identify and stamp out illegal activity.

Culture vs business

Culture has become a prominent factor in regulatory news, with cases of large fines and public censure relating to cultural issues. As the FCA’s COO Emily Shepperd, shrewdly observed in a speech to the finance industry, “Culture is what you do when no one is looking”.

Top-level commitment is crucial when it comes to organisational culture. Conduct and culture are closely intertwined, and culture is not merely a tick-box exercise. It is not defined by perks like snack bars or Friday pizzas; rather, it should be demonstrated in every aspect of the organisation, including processes, people, counterparties, and third parties.

In recent years, regulatory focus has shifted from ethics to culture, recognising its crucial role in building market reputation, ensuring compliance with rules and regulations, boosting client confidence, and retaining employees. The evolving regulatory landscape has significantly impacted e-money and payments firms, with regulations strengthening each year. Each regulation carries elements of culture, as seen in:

• Consumer duty: How do we treat our customers?
• Operational resilience: How can we recover and prevent disruptions to our customers?
• APP fraud: How do we protect our customers?

Key drivers of culture include implementing policies on remuneration, conflicts of interest, and whistleblowing, but for it to become embedded it must touch employees at every level.

This is showcased by senior stakeholders and heads of departments facilitating close relationships with colleagues across a company’s Sales, Operations, Tech and Product teams to build a collaborative environment. 

Finance firms must recognise the trust bestowed on them by their customers and ensure the protection of their investments and data is paramount. Consumer Duty may have been a wake-up call for some companies, but progressive regulation must always be embraced and their requirements seen as a baseline rather than a hurdle.

Similarly, the strengthening of operational resilience rules and the upcoming APP fraud regulation in October are to be welcomed, increasing transparency for customers. 

Compliance vs business 

Following regulatory laws is often viewed as a financial and resource drain, but without proper compliance, companies are vulnerable to situations where vast amounts of money can be lost quickly.

A case in point is the proposed reimbursal requirement for APP fraud, which will mean payment firms could face having to pay compensation of up to £415,000 per case.

Complying not only safeguards the client and their money, but also the business itself. About nine in ten (88%) financial services firms have reported an increased compliance cost over the past five years, according to research from SteelEye.  Embedding compliance earlier in business cultures can be beneficial in the long run, cutting the time and money needed to adapt to new regulations and preventing the stress of having to make wholesale changes rapidly. 

Building a cross-business compliance culture 

Compliance is a key principle at IFX, and we strive to be a champion in this area. In response to these challenges, the business restructured, establishing dedicated risk and regulatory departments, along with an internal audit function. 

Regulatory compliance aims to support innovation by developing and using new tools, standards, and approaches to foster innovation and ensure product safety, efficacy, and quality. It has helped the firm to navigate the regulatory landscape while driving growth and maintaining high standards.

This organisational shift allowed each business line to own its own risk, with department partaking in tailored workshops designed to identify existing, new, and potential risk exposure. Shared responsibility for compliance is the only way to create a culture which values it. We see this as a great way for organisations to drive innovation while sticking to the rules.