6 Ways AI Spearheads Inclusive Lending

The financial services industry is enormous; even a slight change in its landscape can impact the world. Financial services refer to a wide range of services, including insurance and payments to digital banking. Many depend on this industry, from stakeholders and legacy banks to emerging fintech challengers. For this reason alone, the financial services industry needs to rise with the tide to ensure nobody is let down. 

For a long time, the financial services industry has had to deal with many criticisms, including accusations of biased lending. Fintechs have been attempting to tackle this problem for some years now by promoting the potential of artificial intelligence (AI) and machine learning (ML) in financial lending.

AI’s role in the digital era is significant. AI gradually gaining traction in the banking, financial services, and insurance (BFSI) industry is further proof that this statement is true. 

Financial services are undergoing an AI revolution

According to Emergen Research’s report, the banking industry’s global AI will reach a market value of USD 130 billion by 2027.

Financial institutions can employ AI to make smarter, more profitable lending decisions. All parties benefit from inclusive lending.

  • For lenders: inclusive lending is a winning combination of a cutting-edge social strategy and a powerful marketing tool. 
  • For borrowers: provides a better likelihood of getting a loan and a more accurate assessment of their financial capability. 
  • For the financial industry: increases access to finance without jeopardizing lenders’ and borrowers’ financial soundness. 

According to IDC’s Fintech and Digital Banking 2025 (APAC) research, by 2025, 60% of banks in the region would utilize AI or ML to make data-driven decisions, up from 48% in prior years.

WeBank from China uses ABCD (AI, blockchain, cloud computing, and big data) technology to streamline operations and improve efficiencies. AI is applied to their machine-learning-powered AI ecosystem and for marketing and asset & risk management. It is the world’s largest digital bank and generated US$ 570 million in profit within one year. 

Singapore’s UOB has launched TMRW, a mobile-only bank powered by AI on the traditional bank side. It offers many solutions for the millennial market, including an AI-enabled virtual chat assistant called TIA and a seamless banking experience where users can open a bank account in under ten minutes.

Forecasts from Statista suggest that by 2030, the use of AI in the banking industry will generate around 99 billion USD in value in APAC alone.

6 ways AI supports inclusive lending

Financial services providers can use AI in innovative ways to reduce bias in lending. Here’s how: 

  1. Facilitates access to a wide variety of financial products 

Financial institutions’ stringent approaches to quantify risk and analyze data have limited the number of loan products available to customers. They can now increase the number of products thanks to Big Data capabilities, adapting their offerings to match the demands of the actual market. Big Data and AI complement each other as the more data supplied to AI, the better it gets. Big Data is meaningless if it is not analyzed using the software.

  1. Automating internal services to put the client first

AI enables businesses to automate procedures, making the process faster than ever before. From filling out an application form to managing an account to coordinating repayments and evaluating risk, AI allows financial companies to concentrate more on their consumers.

  1. Streamline the application process for easier accessibility

For some people from minority groups, applying for a loan is a hurdle. Complicated terminology and lengthy forms make things difficult to understand, and some people quit before they can even start. AI-based chatbots can assist in making the process more accessible by giving customers more ways to get in touch, offering round-the-clock support, providing support in several languages, and more.

  1. Optimizing the credit scoring process

Credit scoring processes need to be simplified. When AI technology is carefully chosen and implemented, it assists lending organizations in optimizing their credit scoring process, creating personalized loans, and providing scoring devoid of human bias.

  1. Analyzing new demographics

The usual lending procedures make it difficult for students, pensioners, and daily wage workers to obtain loans. With assistance from AI, creating alternative score systems for individuals based on payment histories, expenditure, and other factors is easy. Fintech firms can consider these factors and provide loans without worrying about the dangers of fraud.

  1. Eliminates the possibility of loan stacking

Loan stacking is a frequent practice in the lending industry, in which borrowers take out numerous loans from various lenders. Lending applications will need AI skills to profile user behavior, including analyzing enormous volumes of client data and transactions to identify trends that might lead to fraud.

There’s no doubt that AI is a potent tool for revolutionizing fair lending procedures. When utilized wisely, this technology has the potential to provide more qualified people with loans to help them improve their financial status.


Inclusivity has overtaken profit as the way forward in banking today. Credit providers can reach a bigger market and deliver more services to lower-income individuals, minorities, and other underrepresented groups by concentrating on sustainable, inclusive lending led by AI technology.