Banks Can Be Inclusive yet Profitable with AI 


According to PWC, a Citi Bank report reveals that addressing racial financial equity gaps in the USA alone could contribute $5 trillion to the gross domestic product within the next five years. However, financial equity extends beyond racial inequity and encompasses various social groups such as women, the poor, elderly, disabled, and displaced and migrant populations amongst others. Achieving financial equity is not just a moral obligation but also an ESG (Environmental Social Governance) requirement under its “social” dimension. Currently, 29 countries and territories have implemented mandatory ESG disclosure regulations, emphasizing the importance of promoting financial equity on a global scale.  

Therefore, many banks are taking steps to be inclusive in their product and service offerings, and the advent of Artificial Intelligence (AI) will drive a transformative phase in achieving this goal, enabling banks to be socially responsible while being profitable. Biases in extending financial services not only affect individuals based on their social circumstances but also customer groups like SMEs and startups, because banks require more resources to serve them effectively. However, AI algorithms can analyze vast amounts of data without human resources as well as bias, enabling fairer credit assessments for your bank to accomplish your inclusivity goals without compromising profitability. 

“Until now, this customer data has had to be examined individually by advisors,” says Murat Cavus, who develops sustainability technologies for Deutsche Bank, highlighting the potential of machine learning in automating the examination of customer data. By utilizing machine learning algorithms, deals can be classified into required parameters, reducing the workload for customer advisors. In investment banking and other financial services, such autoclassification processes can help streamline classification and relieve customer advisors of the impractical manual workloads that restrict finance.  

This article looks at six ways your bank can leverage AI-driven initiatives to ensure equitable capital access for underserved customer groups such as those mentioned earlier. 

1. Enabling Fair Credit Access – Loan Applications

Traditionally, banks have relied on credit scores to assess a borrower’s creditworthiness. However, credit scores can be inaccurate and biased, which can make it difficult for people with limited credit histories or from minority groups to get approved for loans. AI can help your bank to address this problem by considering a borrower’s income, employment history, education, social media activity as well as online reviews, providing a more accurate picture of a borrower’s creditworthiness. This shift will enable your bank to bring in underserved and under-banked communities into the formal banking system. 

ZestFinance is addressing the issue of bias in lending practices by using AI-based software to generate fairer credit models. The software identifies and downgrades credit data that has been found to lead to unfair decisions, reducing the influence of unreliable metrics like credit scores. However, your bank should ensure monitoring AI systems for machine learning bias to avoid perpetuating prejudice, when implementing this strategy. 

2. Empowering Financial Wellness – Credit Score Advice

AI-powered credit score monitoring tools can also be used to analyze a borrower’s credit report and provide personalized insights and recommendations on how to improve their credit score. This will enable your bank to help individuals who are deemed not credit-worthy and improve their financial wellness. 

3. Enabling Money Transfers – Simplifying Cross-Border Transactions

AI-powered solutions can revolutionize the way businesses and individuals, especially cash-strapped SMEs and startups, send and receive money across borders. These innovative solutions can ensure that limited-budget entities can access international money transfers quickly and easily at lower costs than was traditionally possible. 

For example, TransferWise uses AI to compare exchange rates from different banks and financial institutions and then offers its customers the best possible rate. Your banks can consider embedding similar services to help SMEs and startups save significant money on their cross-border payments. 

4. Tailoring Recommendations to Individual Needs – Financial Advice and Customized Products

AI-powered financial planning tools can analyze a person’s and even a business’s income, expenses, and goals to create a personalized financial plan. This can help the low-income groups, other underserved communities, SMEs and startups make better financial decisions and reach their financial goals. 

PwC quotes a collaboration with a top-ranked US bank to leverage AI for customer insights. By analyzing factors like wallet size, product usage, and individual circumstances, the bank has gained a better understanding of customers’ financial needs, to offer suitable products at the right time. 

Deutsche Bank’s “Next best offer” uses AI algorithms to monitor Wealth Management Clients’ portfolios and potential risks. It also suggests suitable alternative products to help clients mitigate those risks. The suggestions are based on the choices of similar customers, increasing the likelihood of successful product transitions for clients. Your bank can use the same principles to support the financial goals of the underserved customer groups. 

5. Enhancing Support and Accessibility – Customer Service

One of the reasons banks hesitate to support certain customer segments is the scarcity of resources. For instance, when it comes to catering to the needs of small and medium-sized enterprises (SMEs), banks must allocate a greater number of human resources compared to large corporations. This is primarily due to SMEs being larger in number and relatively low in per capita revenue generation. 

However, artificial intelligence (AI) can help your bank overcome the resource limitation and improve customer service for typically underserved segments in business as well as individuals who need more support such as the elderly, those who do not have access to branches, etc. 

For example, AI-powered chatbots with natural language processing abilities can answer customer questions, provide information and advice and resolve issues 24/7 in multiple languages. This can help your bank provide better customer service and improve customer satisfaction. 

Capital One has introduced Eno, an AI-powered virtual assistant, to improve customer satisfaction. Eno can be accessed through multiple channels including mobile apps, text messages, emails, and desktop interfaces. It assists users with tasks such as answering questions, detecting fraud, making credit card payments, monitoring account balances, and providing transaction information. Eno’s human-like communication style, which even includes the use of emojis, ensures personalized and seamless interactions with customers, enhancing their overall banking experience. 

6. Streamlining Financial Operations – Account Management

AI is also being used to streamline inclusivity in financial operations such as automated account opening and account maintenance. This can help your bank to improve the efficiency of servicing neglected customer groups and save money as well. 

In conclusion, AI has emerged as banking’s new ally in the fight against financial inequality. Its transformative power will enable your bank to make fair credit decisions and facilitate personalized financial services without the constraints of physical branches and the need for large numbers of credit experts and customer service representatives.

Therefore, AI-driven initiatives have the potential to revolutionize the approach to finance, ensuring equitable capital access for customer groups such as SMEs, startups and disadvantaged communities. By embracing AI, your bank can position itself at the forefront of the industry, gaining a competitive advantage while fostering inclusivity, innovation, and economic growth, without compromising profit. 

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