
According to GlobalData forecasts, the total artificial intelligence (AI) market will be worth $908.7 billion in 2030, rising from $81.3 billion in 2022 at a compound annual growth rate (CAGR) of 35.2%. In the finance world, this rapid growth will have an acute impact.
Analysis of vast quantities of customer data means AI solutions can tailor financial products to individual needs, revolutionising access for underserved consumers. By using this data, AI delivers hyper-personalised financial solutions, ensuring products are designed to match unique circumstances and preferences. The ability to deeply customise offerings empowers institutions to connect with customers in ways that were previously impossible, bridging gaps in financial inclusion. On top of this, AI-driven tools can provide 24/7 support, making the transition to digital banking platforms smooth and easy.
But will AI’s potential advantages be evenly distributed? Finance can seem prohibitive for would-be consumers who lack the knowhow to access it or whose records may be counting against them. The scrutiny these consumers face from banks and other lenders has historically left them locked out of many financial products altogether. AI could help to smooth out kinks in the relationship between lenders and borrowers, benefitting both. It all depends on how it is deployed.
AI and inclusive finance
AI technologies are already reshaping how creditworthiness is assessed, loans are priced, and products are tailored to meet diverse needs. In doing so, they are opening new pathways to financial inclusion, creating a system that is more transparent, equitable and efficient.
Loan pricing and personalisation is one outstanding example. The static, broad-brush, one-size-fits-all approach that characterised loan pricing in the past has marginalised those with “thin” or unconventional credit profiles, such as self-employed workers, immigrants, or individuals with irregular income streams. Today, AI is breaking down these barriers by incorporating real-time market data, behavioural insights and individual financial circumstances into dynamic models. Financial institutions can offer highly customised products that align with each borrower’s unique situation instead of simply rejecting “nonstandard” borrowers.
This shift toward personalisation has had measurable impacts. One UK high-street bank, for instance, saw a 300% increase in loan sales among mobile users after introducing real-time personalised offerings. Similarly, a leading European bank reported a 9% increase in unsecured loan volumes within a year of adopting AI-driven tech. With individuals gaining access to previously prohibitive housing, education and business opportunities, banks can use AI to strengthen their relationships with clients and spread the net of economic opportunity. It illustrates how AI is improving customer experience and deepening relationships between banks and their clients through the medium of financial access.
Regulatory compliance is another area where AI is making significant inroads. In the UK, the Financial Conduct Authority’s (FCA) Consumer Duty regulations have introduced new standards for fairness and transparency. They require financial institutions to ensure products offer value and meet customer needs. Similar regulations, such as Fair Lending laws in the United States, have intensified the focus on non-discriminatory practices and equitable access to credit. AI-driven tools are helping lenders navigate these complex regulatory landscapes. By providing clear, data-backed insights into how loan terms are calculated and ensuring consistency in decision-making, banks can demonstrate that the prices they offer are both fair and aligned with the customer’s specific financial profile.
Such transparency fosters trust between institutions and clients while mitigating reputational risks associated with regulatory non-compliance. Early evidence from the UK suggests that the introduction of Consumer Duty is driving meaningful change, with investments in customer service provision rising rapidly. Many are pumping cash into AI and advanced analytics to ensure their pricing models and lending practices meet and exceed new standards.
Behind the scenes, AI is also transforming the operational backbone of financial institutions. Traditionally, pricing decisions and adjustments relied heavily on IT teams and manual processes. Modern AI systems have streamlined these operations, empowering decision-makers to implement updates quickly and independently without the need for lengthy manual processing. This agility enables banks to respond rapidly to market changes, optimise customer segmentation and refine pricing strategies in real-time. By reducing reliance on outdated processes, AI is fostering a leaner, more adaptive banking industry.
Ultimately, AI-driven pricing and personalisation strategies are also enhancing profitability. By increasing approval rates for tailored loan products and aligning terms with borrowers’ repayment capacities, banks are reducing default risks and expanding their customer bases. Furthermore, the cost savings achieved through automation and improved decision-making allow institutions to reinvest in innovation, creating a virtuous cycle of growth and inclusion: a win-win for both banks and customers.
The road ahead
While AI’s potential is undeniable, challenges remain. Concerns around the ethics of AI, such as the risk of algorithm bias, remain an important consideration. To address this, the financial industry is increasingly prioritising “explainable AI”—ensuring that decisions made by AI systems are transparent and can be justified to regulators and customers. Institutions must invest in robust integration strategies that align AI technologies with their broader goals. Success will depend not on the sophistication of the tools on paper, but on how effectively these tools are rolled out and utilised across teams and departments.
Where next for AI in finance? Further expansion seems inevitable, and evolving regulatory frameworks and consumer expectations mean financial inclusivity will have to be a key component of this. The UK’s Consumer Duty, for example, is not a one-time exercise but an ongoing commitment to prioritising consumer interests. Lenders can use AI to fulfil this mandate systematically and sustainably.
The pivotal impact of AI on financial inclusion represents a broader cultural shift within the financial sector toward a more consumer-first mindset. By leveraging AI, institutions can deliver fairer, more accessible products that not only meet diverse customer needs but also build trust and loyalty. For countless would-be consumers previously excluded from financial opportunities, this transformation offers the promise of a more equitable and inclusive future.
To learn more about personalisation in finance, inclusion and the overarching role of AI, leading industry software providers Earnix have prepared a free eBook unpacking the current landscape for consumer loans. Fill in your details on this page to find out more.