Egypt has made progress in extending accessibility to banking services in the last decade.
Based on the Central Bank of Egypt, 74.8 per cent of Egyptians were able to open a transactional account in the month of December 2024. This is an increase of 204% over the year 2016. The figures are even more striking for females: 68.8% now have an account, which is up by 295% over the same time frame.
This development is evidence of a national commitment to financial inclusion, which includes changes to the regulatory framework, such as opening accounts using only the identification of a national. It also highlights the work of private sector firms that are using technology to create economic opportunities for a multitude of people.
However, having an account at a bank is only the initial step. Financial inclusion is the possibility to use, access and profit from a wide variety of services, from savings programs to credit and payment investment products. While the availability of these services is increasing but extending credit to low-income individuals is a significant issue for financial institutions as well as governments that want to increase access to financial services.
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What is the role of credit in achieving more prosperity
Credit can be a catalyst for long-term prosperity. It directly assists the creation of wealth through allowing people to take advantage of long-term opportunities for economic growth.
Instead of paying rent every per month, to an landlord individuals can apply for a mortgage, and then make monthly payments toward the purchase of their home. Families can help fund their children’s schooling, and women can take out loans to establish their own companies and achieve greater financial freedom.
However, for many across Egypt and across the world access to credit remains beyond reach. The traditional credit scoring models depend on formal financial records and manual underwriting can be a costly and unreliable route.
In the end, a lot of banks and lenders are hampered in their ability to provide loans to the underbanked or new-to-credit groups. The chicken-or-egg problem most severely affects low-income, rural and financially disadvantaged communities which includes youth and women.
A more comprehensive and intelligent solution
Innovative companies are increasingly turning to AI (AI) to address the shortcomings of traditional financial models.
In countries where credit histories that are formalized are in short supply and credit bureau coverage is insufficient AI-based models provide an attractive alternative. What makes these models stand out is their capacity to discern not just individual actions as well as social and behavioral networks.
By integrating a variety of real-time data sources AI-powered credit scoring algorithms can increase approval rates, decrease risks and provide credit to people who were previously unable to access credit through conventional credit scoring systems.
This is a positive improvement for financial inclusion, particularly in situations in which traditional methods don’t scale.
The credit-scoring model’s workings
MNT-Halan is Egypt’s fastest-growing fintech firm and the first MENA-based tech unicorn created an AI-powered alternative credit scoring tool which uses transactional and behavioural data to assess users – the majority of whom have not been involved in formal credit systems prior to. By using this model that is unique to the company, MNT-Halan has automated more than 50 percent of its credit approvals and has have achieved an approval rate of 60% for previously ineligible users.
The solution makes use of information taken from Halan superapp that provides payment as well as savings, investment, and e-commerce through a single digital platform. The integrated platform generates an array of user-generated data including transactions, payments history, and interactions with the app. This data is fed directly to the AI engine.
Through observing how people use these services What they do – when frequently they pay for purchases, repay balances, or use apps, the model develops individual and dynamic profiles.
The multi-dimensional model allows MNT-Halan to evaluate risk better than traditional systems, even in absence of financial data in the form of formal.
For instance an individual who was previously unbanked who started using the Halan app’s online shopping feature to purchase wholesale food items. Based on the behavioural information that it was determined that the AI scoring algorithm was able to determine a credit score, and also give the customer the consumer finance limit.
The individual was granted the Halan Card, and was later able to make use of its secured investment products. This was a long financial experience that was made possible by AI and fueled by data.
Responsible AI in Action
Implementing AI in areas with high impact, such as credit scoring demands strong frameworks for managing risk. If not planned properly they could exacerbate the very inequities they are designed to reduce.
By actively developing accountable AI guidelines and regularly conducting audits businesses can assure that AI is used in a fair and ethically. MNT-Halan follows five principles when it comes to its application of AI:
- In fairness: Models are specifically designed to include non-banked and new to credit users making use of alternative data, and are constantly checked to ensure that there is no bias in different segments.
- The ability to explain: Credit decisions are easily explained by transparent scorecards that provide insight into what data elements are included in the algorithm, and how they are weighed against one another to make an ultimate decision.
- Privacy: All information is collected with the consent of the user and in accordance the Egyptian Personal Data Protection Law (PDPL).
- Evaluation: These models are regularly checked for accuracy and are regularly audited to ensure they’re performing and fairness, based on actual results.
- Human oversight: Uncertain or sensitive cases are reviewed by hand to ensure that the automation does not outweigh human judgement.
Importantly, users can opt-in to data sharing and are able to opt out at any point. The opt-in model is based on confidence and consent among the customers of the products.
Expanding financial inclusion across Egypt and beyond
The use of AI credit scoring models has already helped millions of people in Egypt gain access to financial services that they’ve been unable to access for years. But the possibilities don’t end when it comes to national borders.
As per the UN Economic and Social Commission for Western Asia 64% of adult residents across the Arab region are not banked and only 29 percent of women own an account. Since the launch of operation in Turkey, Pakistan, and the United Arab Emirates last year, MNT-Halan is working to improve access to credit in regions of Middle East and North Africa region.
To achieve true financial inclusion for these people requires more than offering bank access. The smart application of AI will to ensure that information availability don’t exacerbate existing inequalities in financial services access, which is a vital instrument to boost economic growth for those who were previously excluded from formal economics.
