How AI Tech Can Enhance Women’s Security in Financial Transactions

May 16, 2024

In my experience of living and working from India, I’ve noticed that when it comes to finance, women encounter myriad obstacles. These include higher susceptibility to scams as well as the challenges brought about by inequalities in financial literacy between men and women. 84.7% of men and 70.3% of women in India are literate. In a large section of the country, women shoulder the responsibilities of raising the family and often grapple with the risk of being targeted by fraudulent schemes due to various factors, including societal norms and vulnerabilities. 

The limited access to financial education and resources results in lower levels of financial literacy in women as compared to men. Disparities in income and employment opportunities further widens the gap. Collectively, these challenges necessitate tailored solutions which will enhance inclusivity and financial security.

AI technology can serve as the perfect champion for women’s causes in this context. It can offer solutions that will help bridge the above-mentioned gaps and provide a safer environment for women. 

Let’s look at the different ways AI can make a difference.

Digital Financial Capability

AI technology can serve as a crucial enabler in transitioning women from traditional banking to digital financial services, facilitating convenience and accessibility. Through AI-driven interfaces and personalized assistance, women can navigate digital platforms with more confidence, regardless of their prior banking experience or technical proficiency. 

These tools offer intuitive features, such as simplified user interfaces and real-time support. By bridging the digital divide, AI can promote financial inclusion by allowing women to participate more in the digital economy.

Bias Mitigation

AI and machine learning algorithms can reduce biases inherent in current lending practices, thereby promoting fair and equitable access to financial services for women. Traditional lending models often perpetuate gender biases, resulting in disparities in loan approval rates and terms.

AI-driven solutions can analyze vast datasets and identify patterns of bias, allowing financial institutions to adjust their algorithms and decision-making processes accordingly. By removing discriminatory factors and adopting more inclusive criteria, AI can foster a level playing field where women have equal opportunities to secure loans and access other financial products. This not only enhances financial inclusion but also promotes economic empowerment and stability among women.

Risk Assessment and Credit Scoring

Traditional credit scoring methods have been criticized for their potential biases, which can disproportionately disadvantage women, particularly those with limited credit history or career interruptions because of childcare. However, AI technology is driving innovation in this area by facilitating the development of more sophisticated risk assessment models. 

Unlike traditional models that rely heavily on credit history and income, AI-powered algorithms can analyze a broader range of factors to assess creditworthiness more accurately. This includes considering non-traditional data points such as education, employment history, and even social media activity. By adopting a more comprehensive approach to credit scoring, AI holds the potential to promote fairer access to credit and financial services for women. 

Additionally, AI-driven risk assessment models can help lenders better understand the unique financial circumstances of women, thereby reducing bias and ensuring more equitable outcomes in lending decisions.

Financial Inclusion

As I said above, AI technology can play a pivotal role in driving financial inclusion. Other than risk assessment, AI can help design products and services that cater specifically to the needs of women. Through data analytics and machine learning algorithms, AI can gain insight into women's financial behaviors, preferences, and challenges. Armed with this knowledge, financial institutions can develop tailored solutions, such as microloans for women entrepreneurs or flexible savings accounts for working mothers. 

Moreover, AI-powered chatbots and virtual assistants can provide personalized guidance and support, enhancing the overall banking experience for women. 

Fraud Detection

AI-driven fraud detection systems are transforming the landscape of financial security, particularly for women. By leveraging vast datasets and sophisticated algorithms, these systems can swiftly identify unusual spending patterns or transactions that deviate from a user's typical behavior. One can enable real-time alerts and safeguards against unauthorized account access or money laundering attempts.

Fraud detection AI is particularly relevant for India due to several factors that uniquely affect us, ranging from our large and diverse population to the rapid digitization of our financial services. Let me list some of them here:

  1. Growing Digital Economy: India has seen a tremendous surge in digital transactions, especially following initiatives like Digital India and the implementation of systems like UPI (Unified Payments Interface). With the increase in digital transactions, there is a corresponding rise in the potential for fraudulent activities, making advanced fraud detection systems essential.
  2. Diverse Financial Landscape: India’s financial sector is diverse, with a mix of traditional banking systems and modern fintech solutions. This diversity can create complex patterns of transactions that are challenging to monitor without the help of AI, which can analyze large datasets quickly and efficiently.
  3. High Volume of Transactions: India's population of over 1.3 billion people results in an enormous volume of financial transactions daily. AI systems are capable of handling and analyzing these vast quantities of data in real time to detect and prevent fraud.
  4. Inclusion of Underbanked Populations: As financial services expand to include previously underbanked sections of the population, there's a higher risk of fraud due to the lack of familiarity with digital financial services among new users. AI can help by detecting irregular activities that may indicate fraud, protecting inexperienced users from potential threats.
  5. Mobile and Internet Penetration: With increasing mobile and internet penetration across the country, more people are accessing financial services through their smartphones. AI can enhance the security of mobile transactions by identifying unusual behavior or discrepancies that indicate fraud.

Given these factors, AI in fraud detection can not only enhance security for consumers but also support the overall growth and stability of the country’s digital economy.

Behavioral Biometrics

Behavioral biometrics is a cutting-edge approach to identity verification. By analyzing unique user behaviors such as typing patterns or mouse movements, this technology offers a sophisticated layer of security. Even when logging in from a new device or location, behavioral biometrics can accurately verify a person's identity with remarkable precision. 

This capability can be a big relief for women, significantly reducing the risk of identity theft and unauthorized account access. Behavioral biometrics can serve as a robust safeguard overall, increasing user trust in digital banking platforms.

Financial Literacy Tools

We now come to our final point. In my view, AI financial literacy tools can be particularly useful in our country because of our vast diversity in languages, cultures, and levels of financial inclusion. Here are some key ways AI can address these challenges effectively:

  1. Multilingual Support: AI can provide support in multiple languages, enabling personalized financial education for users in their native language. This is crucial in India, where there are 22 officially recognized languages and hundreds of dialects. AI-driven tools can automatically translate and adapt content to local languages, making financial education accessible to a broader audience.
  2. Cultural Relevance: AI can customize educational content to fit cultural contexts and specific regional needs. For example, the way financial concepts are explained in urban areas might differ from rural settings. AI can analyze these nuances and tailor content accordingly, which enhances understanding and engagement.
  3. Scalability: AI can handle thousands of interactions simultaneously, making it possible to reach a large number of users across the country. This scalability is essential in a populous nation like India, where reaching remote or underserved areas with traditional educational resources can be challenging.
  4. Interactive Learning: AI-powered tools can make financial education more engaging through interactive quizzes, virtual simulations, and gamified learning experiences. This interactivity can increase retention and make learning about finance more appealing, especially to younger demographics.
  5. Support for Non-Literate Users: Advanced AI tools, including voice recognition and response technology, can assist users who are unable to read or write. Through spoken instructions and feedback, these tools can extend financial literacy to illiterate or semi-literate populations.

Overall, AI technology can be a powerful tool in addressing the unique challenges that women face in financial transactions. From targeted scams to disparities in financial literacy and access, women navigate a complex landscape where traditional solutions often fall short. Here, AI-driven solutions can offer an opening, promising to bridge these gaps and create a safer, more inclusive, financial environment for women.

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