The importance of AI and machine learning in credit lending

From facial recognition to fraud detection, artificial intelligence (AI) is enabling service providers and institutions across the world to speed up complex processes, mitigate risk, and transform how we live, work, and manage our money. Like fintech itself, AI is the smart solution to the complex problems which affect end users across the world. 

AI in fintech is an industry which has already witnessed huge investment, and even bigger growth. In 2021, AI in fintech was valued at approximately $8 billion globally – and it is estimated that by 2031, it will be worth approximately $61 billion.

But what does this mean for lending solutions? How are credit lenders harnessing the power of AI and machine learning to drive accurate, efficient, and inclusive lending? And what does the immediate future hold for service providers, and their end users – particularly those in emerging markets? 


  1. The rise of machine learning

A key avenue of growth for AI in fintech will be the continued evolution of machine learning, which is a subset of AI. However, whereas AI leverages computer science to simulate human intelligence and decision-making, machine learning allows machines to learn and adapt from data sets without explicit instructions. Over time, as new data is provided, machine learning continues to increase the accuracy of its algorithms. 

So, when it comes to lending solutions, machine learning has an important role to play. It can transform how credit and financial service providers process, analyse, and implement data, to drive better long-term decision-making. Its usage can therefore drastically speed up processing times and reduce inefficiencies.

  1. Enhanced risk management

The use of AI in fintech is also proving an important tool for calculating and predicting risk in credit scoring – even for end users without a credit history. 

Traditionally, personal credit scores are produced based on information such as previous loan payments and applications. In contrast, credit scores can also be produced by using alternative data which comes from non-traditional sources, such as mobile wallets and Know Your Customer (KYC) data. 

In both cases, AI is a critical tool for processing huge amounts of data in real time with greater accuracy than ever before. This allows creditors to widen their pool of potential borrowers, to service those who may have previously been rejected for a bank loan, those who have not yet had the opportunity to build up a credit history, and those who have been turned away because they do not have all the necessary paperwork available to process a loan application. By leveraging predictive analytics to simplify the credit decision-making process, AI is enabling creditors to optimise risk management strategies, lower the likelihood of loss, cut costs, and also enhance the customer experience.

  1. Greater focus on financial inclusion 

When looking to the future, we also need to consider the impact on those who providers and institutions ultimately serve – the end user. 

Financial inclusion is undoubtedly the cornerstone of a more equal global economy. And the positive impact of AI and machine learning is becoming increasingly significant in markets which have traditionally been financially underserved. 

It is currently estimated that almost one in two people in Africa live in poverty. This means that, for many people across the continent, rapid, responsible, and reliable access to products such as cash loans can be vital for keeping children in formal education and small businesses afloat. 

Today, more and more companies are harnessing AI to bring more people into the global economy by providing innovative lending solutions, powered by efficient and insightful data processing and analysis. This people-first approach to innovative technologies is helping financial service providers across the world to create better opportunities for those end users who need safe access to credit the most. 


AI and machine learning have the potential to transform the way that credit lenders process data, and drive more informed decision-making. It is currently estimated that thanks to AI and machine learning, by 2032 financial corporations will be able to reduce costs by 22% across a range of resources, from customer service to loan decision-making. Its impact on credit solutions not only makes lending more efficient, accurate, and cost-effective for service providers and financial institutions – when leveraged properly, it can be instrumental in the promotion of global financial inclusion.

Since our launch in 2012, financial inclusion has been at the heart of Ezra’s global mission – to bring more underserved, underbanked individuals across emerging markets into the global economy.

We source relevant and insightful alternative data sets, to determine the right algorithm for each partner’s needs. We then leverage the power of AI and machine learning to design innovative lending services and produce proprietary lending products. We also ensure that each of our machine learning models takes into account ethics codes, edge cases, and all regulatory frameworks. We also continue to monitor our models beyond launch, to promote long-term product success and support adaptability. 

Because of this, our products and services accurately profile more than 100 million end users per month – including those without a credit history. This meant that, in 2022 alone, we were able to process two billion loan applications in emerging markets across the world.

To learn more about how our products and services can benefit your business, please get in touch today.