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.
