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<figure id="figure-wqh61tzzwmm689qexu" class=""><img id="wqh61tzzwmm689qexu" src="https://cdn.durable.co/blocks/32KPhBXMhXMkh87QxBd07gzZu2MZGvy0qkwGJSf9G0F3hEn1OnYDwVs4iAZkPrKy.jpg" alt="" title="" class="object-cover bg-gray-100 " style="aspect-ratio: 3/2; object-position: 45% 35%;" data-corners="default" data-aspect="3:2" data-caption="" data-positionx="45%" data-positiony="35%" data-fullwidth="false" data-mce-src="https://cdn.durable.co/blocks/32KPhBXMhXMkh87QxBd07gzZu2MZGvy0qkwGJSf9G0F3hEn1OnYDwVs4iAZkPrKy.jpg" data-mce-style="aspect-ratio: 3/2; object-position: 45% 35%;"></figure>As consumers/end users, we can no longer afford to sit idly by and let others run roughshod over our data.It’s our data and we own it. So, why are we so willing to let go and let others use it under the guise of helping to make your life easier or to be more productive? While that is all good, because who wouldn’t want to offload mundane routine tasks so you can get more “real stuff done?” But that helpfulness and increased productivity shouldn’t require unfettered access to your data and then allow others to do whatever they see fit with it, from using it to “learn” more about your habits and “needs” to help you or selling it to 3rd parties for profit so they can sell you more “stuff.”&nbsp; &nbsp; In the advent of impending agentic AI, which is going to be here sooner than you think, as it’s reported that OpenAI in the next coming weeks will announce a next level breakthrough that unleashes PhD level super agents to do complex human tasks. On the books is a closed door <a data-mce-href="https://www.axios.com/2025/01/19/ai-superagent-openai-meta?utm_source=tldrnewsletter" href="https://www.axios.com/2025/01/19/ai-superagent-openai-meta?utm_source=tldrnewsletter" target="_blank" rel="noopener">meeting</a> scheduled with US government officials in Washington on January 30, 2025.&nbsp; &nbsp; Coupled with the deployments of new AI assistant systems like Google’s scam call protection and Apple Intelligence (refer to my previous post), both put AI EVERYWHERE on your phone – even in the middle of your private messages. Again, refer to my previous post on how to disable Apple Intelligence on your iPhone. So, have you really thought about your privacy? &nbsp; &nbsp; The looming question continues to be this - what are the privacy implications of AI? This keeps me up at night especially due to the recent EU debate over <a data-mce-href="https://www.patrick-breyer.de/en/posts/chat-control/" href="https://www.patrick-breyer.de/en/posts/chat-control/" target="_blank" rel="noopener">mandatory content scanning laws</a> that would require machine learning systems to scan virtually every private message you send. &nbsp;So, what happened to end-to-end encryption and better yet, what does it mean for it in the future?&nbsp; <h3>A 101 Primer on End-to-End Encryption</h3>For the past 10 years or so, it was all the rage as we saw the explosion of end-to-end encrypted communication platforms. Remember prior to 2011, most cloud connected devices uploaded their data in plaintext, and you know the hot mess that ensued from there. For many, their private data was exposed like laundry out to dry on the line for everyone from hackers, subpoenas, warrants or exploited by the platforms themselves. New data storage approaches started to evolve around 2011, and we saw messaging apps like WhatsApp and Apple’s iMessage rolling out default end-to-end encryption for private messaging.How does this work?Simply put, this technology changed key management to ensure that a server would never see the plaintext of your messages. Cool, right? Not too long afterwards, phone designers starting encrypting data stored locally on your phone. The recurring theme for both advancements? Nothing needed to be processed by a server. &nbsp; So, here’s the rub: For data that requires intense processing options are limited. Sure, for cloud backups and private messages it’s easy to hide content from servers. But when you want to do serious compute, the typical phone has a limited amount of processing power, including limited amounts of RAM as well as battery capacity. Case in point, did you see how your battery life significantly took a hit if you didn’t disable Apple Intelligence? Even if you wanted to do something like photo processing on the most tricked out iPhone, it still needs to be plugged in to avoid draining the battery. Not to mention, there’s a cornucopia of variation in phone hardware. There are some tricked out phones with onboard GPUs and neural engines, but they aren’t cheap. Most start around $1,400 and go up from there. Not only are these phones not typical, but they are also cost prohibitive and what’s left will range in their processing capability.&nbsp; &nbsp; Now with the primer on the evolution of end-to-end encryption, how does AI come into play? If you weren’t paying attention because the cat memes got you on Instagram, in 2024 there was a new frontier model released every 2.5 days. These new powerful models have cutting edge capabilities ranging from LLMs that can generate and understand human text to new image processing models that can produce content on their own from text, images, audio, code, 3D and more.We are entering unchartered waters, and no one really knows where this can go or actually knows how useful these models can be to their customers but that hasn’t stopped any and every tech company to find applications for this tech – including phone and messaging companies. The collective rally cry and race to the bottom is – models are the future. Personally, I believe the onslaught of integrating AI into our daily lives via our mobile phones is likened to the amuse bouche. I’m a self-proclaimed foodie so, let me explain. Have you ever been to a restaurant and the chef sends out something called the “amuse bouche?” It’s a French term for 'mouth amuser' and chefs serve this to diners to enjoy while waiting for their food orders to arrive as well as a way of saying 'welcome' to guests and pampering them with something special. &nbsp;Well, consider this the amuse bouche for the main entrée to come – the deployment of AI Agents. &nbsp; &nbsp; Theoretically, with these new agents you don’t need to bother reading and responding to messages on your phone because they’ll read your email and text messages and answer them for you. They can order your food, find you the best deals on shopping – basically anticipate your every want or need. And how can they do this? Unfettered unrestricted access to all your private data coupled with a considerable amount of compute power to process it.&nbsp; &nbsp; So, let’s go back to the end-to-end encryption and data storage primer. The key here is that nothing needed to be processed by a server. But now, these agents will require more compute power than most phones have so they can run these powerful models. And that means, much of the processing as well as the data that needs to be processed will have to be offloaded to remote servers.&nbsp; &nbsp; Huh? Yep, so what happens to all that privacy?&nbsp; &nbsp; This is why I implore everyone to be very careful before enabling all of this cool tech to do cool stuff to that makes your life easier, because the privacy implications are enormous. All of this slickness promised requires compute that will be done off your device which means sending considerably more of your private data to systems that will examine and summarize your data, produce compact summaries of your LIFE. These systems will eventually know everything about you and your friends, because they will have access to our most intimate and private conversations. We are standing at the precipice of the complete death of privacy and now is the time to ask the hard questions about these systems. Especially existential questions like: are they really working for us?&nbsp; &nbsp;&nbsp; When it comes to end-to-end encryption, current messaging systems issue very specific technical guarantees. By definition, an end-to-end encrypted system is designed to ensure that plaintext message content in transit is not available anywhere except for the end-devices of the participants and anyone the participants or their devices choose to share it with. I want to lean in on this because this is super important. If you are 1:1 texting cool but what if you start a WhatsApp group chat and someone else in the group decides to turn on some service that uploads (your) received plaintext messages to WhatsApp. Can you say the message you received accurately describes how WhatsApp treats your data? &nbsp;<figure id="figure-xyhl9qa9d9m688zs1g" class=""><img id="xyhl9qa9d9m688zs1g" src="https://cdn.durable.co/blocks/16GNnayE13BZF9zEUnywmZUgE5bRoPlrO5n3UPmdGds9pSaDiehM14lRH60iO6Za.png" alt="" title="" class="object-cover bg-gray-100 " style="aspect-ratio: 16/9; object-position: undefined undefined;" data-corners="default" data-aspect="16:9" data-caption="" data-positionx="undefined" data-positiony="undefined" data-fullwidth="false" data-mce-src="https://cdn.durable.co/blocks/16GNnayE13BZF9zEUnywmZUgE5bRoPlrO5n3UPmdGds9pSaDiehM14lRH60iO6Za.png" data-mce-style="aspect-ratio: 16/9; object-position: undefined undefined;"></figure>This is where things get even more complicated because now we are talking about informed consent. Consent is both a moral and legal concept and the law is different in every corner of the world. &nbsp; &nbsp; Getting back on my soapbox about being intentional about owning your data and protecting your privacy, some companies will do an admirable job at letting their users know exactly what’s happening as a way to earn trust. Others, well, will bury your consent inside of an inscrutable lengthy riddled with legalese “terms of service” document you never read but click “accept” so you can go about your business. In the EU they’ll probably just invent a new type of cookie banner.&nbsp; &nbsp; We are on an accelerated path to a world where you should expect more and more of your data to be processed by AI and that processing will most likely be done off your device. Altruistic end-to-end encryption services will actively inform you when this happens which presents you an option to opt out. But, if it’s everywhere then our options will probably be limited. &nbsp; &nbsp; I’ve said this and will continue to say it. I am not afraid of technology, I actually geek out over all the new emerging technology coming out. But what worries me and keeps me up at night? These models are not inclusive, they are woefully absent of regulations on ethical development, deployment, and use. It doesn’t really matter what technical choices we make around privacy. It does not matter if your model is running locally, or if it uses trusted cloud hardware — once a sufficiently powerful general-purpose agent has been deployed on your phone, the only question that remains is who is given access to talk to it. &nbsp; &nbsp; And the question you should think about is - will it only be you?

Privacy Implications of AI Agents & Data Processing

<h3>While AI-powered platforms marketed to individual investors may seem appealing, an expert urges caution.</h3>Beyond thrilled to share that I’ve been featured in the tech spotlight with a piece titled “Using AI to Help Trade Stocks”! This <a data-mce-href="https://www.10tv.com/article/tech/using-ai-help-trade-stocks/530-fb9ddd73-2508-4cf2-b9d7-69abde549151" href="https://www.10tv.com/article/tech/using-ai-help-trade-stocks/530-fb9ddd73-2508-4cf2-b9d7-69abde549151" target="_blank" rel="noopener">interview</a> dives into how data-driven insights and advanced algorithms can give traders that extra edge in a fast-paced market.I’m passionate about simplifying AI for everyone—from curious beginners to seasoned pros—and this feature highlights the power of innovative tools we’re building in the finance world.

Using AI To Trade Stocks: CBS 10TV Feature

<figure id="figure-33538jlzjm49zr2ov" data-full-width=""><img id="33538jlzjm49zr2ov" src="https://cdn.durable.co/blocks/9nItQkumJyIMM02JFVq7pC1uVemw3RyrMiIvUz1iPIUAfC5bqf1uIMoehooihI27.png" alt="" title="" class="object-cover bg-gray-100" style="aspect-ratio: 16/9; object-position: 100% 25%;" data-corners="default" data-aspect="16:9" data-caption="" data-positionx="100%" data-positiony="25%" data-fullwidth="true" data-mce-src="https://cdn.durable.co/blocks/9nItQkumJyIMM02JFVq7pC1uVemw3RyrMiIvUz1iPIUAfC5bqf1uIMoehooihI27.png" data-mce-style="aspect-ratio: 16/9; object-position: 100% 25%;"></figure><h3>When beauty is algorithm-made, who gets left behind?</h3>Death by a Thousand Cuts: Fighting Against the Slow surrendering to the Allure to Artificial IntelligenceIt doesn't seem like much to get one small cut. However, a thousand? A thousand cuts have the power to alter everything.Have you ever been up in the middle of the night, bleary-eyed, and engrossed in something you didn't even remember looking for, only to find yourself scrolling endlessly? Maybe it was a curious thought, a little “What if?” that led you down a digital rabbit hole. And there you are, two hours later, wondering how this small act pulled you so far in. This is how artificial intelligence—our ever-present, all-knowing technological companion—seeps into our lives. Not as a loud, booming revolution but as a soft whisper, a slow creep, each new convenience drawing us in just a bit deeper. One swipe, one click, one surrender at a time.AI: The Silent Hand Reshaping BeautyTwo letters, forever changing the world—and, yes, even the way we see beauty. AI has cracked open new doors in the beauty industry, from skin analysis and shade-matching to virtual makeup try-ons. It offers fresh possibilities for people who may have never had access before, bridging gaps for those with mobility or visual impairments. Voice-activated AI can walk you through makeup routines; it even pushes design innovations like easier-to-open packaging and larger fonts. There’s power in this technology, and it’s moving fast.But here’s the truth we don’t always want to look at: with every advance, every “improvement,” something falls by the wayside. While AI reshapes beauty, it also redefines it in ways that leave too many of us out. In a recent study, the Washington Post fed prompts like “beautiful woman” to AI image generators—Midjourney, DALL-E, and Stable Diffusion—and the results were sobering. Picture after picture showed slender, young, and light-skinned women. Only 2% of these images showed visible signs of aging, and a mere 9% showed dark skin tones. Here’s what that means: in AI’s vision, beauty doesn’t look like most of us. It doesn’t see the beauty in our wrinkles, in the richness of dark skin, or the brilliance of bodies that don’t fit narrow standards. I can’t help but wonder, where do I—and so many others—fit into this algorithm’s idea of beauty? &nbsp;The Matrix Effect: Choosing to See RealityAnd that got me thinking. If you’ve seen The Matrix, you know that iconic choice—swallow the blue pill to stay in a blissful slumber, or take the red pill to see the world as it is. Today, the choice isn’t a pill. It’s about how much of ourselves we’re willing to let AI define. Beauty is everywhere—in airports, in coffee shops, in subways, in faces of every complexion and every age. I see it every day in people AI may never recognize if we aren’t careful. And if AI can’t see us, who else won’t?<figure id="figure-2s6b2s7j4im3nnlztl" class=""><img id="2s6b2s7j4im3nnlztl" src="https://cdn.durable.co/blocks/2foc2vFRrOOwjLaZtnn3YdreGHx21VT6URguQN8dP6fJ0DmHXUJGqB4b0PPweZOI.png" alt="" title="" class="object-cover bg-gray-100 " style="aspect-ratio: 16/9; object-position: 70% 50%;" data-corners="default" data-aspect="16:9" data-caption="" data-positionx="70%" data-positiony="50%" data-fullwidth="false" data-mce-src="https://cdn.durable.co/blocks/2foc2vFRrOOwjLaZtnn3YdreGHx21VT6URguQN8dP6fJ0DmHXUJGqB4b0PPweZOI.png" data-mce-style="aspect-ratio: 16/9; object-position: 70% 50%;"></figure><blockquote>People often say that beauty is in the eye of the beholder, and I say that the most liberating thing about beauty is realizing you are the beholder - Salma Hayek</blockquote>Standing at the Threshold: Three Skills for Staying HumanTo keep from being consumed by a thousand tiny cuts, we need three things: deep engagement, relentless curiosity, and a commitment to what makes us profoundly human—our heart.1. Engage Deeply: Learn AI by Using ItLike Neo choosing to explore the unknown, we each have a choice: to truly understand AI or to passively consume it and follow it like sheep. AI isn’t waiting for us to catch up; it’s evolving minute by minute. Personally, I spend two to three hours daily on AI—testing, exploring, learning. Every new feature, each algorithm, reveals both possibilities and hidden risks.Let’s be real—if we’re not using AI, it’s using us. Try the free versions of ChatGPT, Google Gemini, and other tools reshaping the world. Don’t just read about AI; dive in. Play with it. Each experience brings clarity, helping us spot when convenience becomes quiet control or misrepresentation. By engaging actively, we learn to see AI’s edges and to feel when it’s overstepping. It’s how we stay ahead, remaining intentional about what parts of our lives we’re willing to let AI touch. Head over to my website and sign up for my newsletter where there’s an active list, updated daily of resources and free courses you can take to play with and understand the potential power of AI and how you can use it to become the best version of YOU.2. Question Everything: Keep AI in Check with a Rebel’s MindsetIn The Matrix, Neo’s power wasn’t in his strength but in his questioning. That’s the mindset we need. Each time AI “knows” something about us, we should question it. Not to dismiss, but to validate, to seek truth, and stay in control.Once, I asked AI to compare my image to its notion of beauty, only to be reminded of its limitations. It didn’t just fall short; it reinforced biases, giving answers that didn’t represent the fullness of who I am. AI doesn’t question itself, no matter how wrong it may be. So, we must be its counterbalance. History’s changemakers—from Socrates to Rosa Parks—knew the power of asking, “Is this right?” In the AI era, every unexamined answer consumed and actioned as fact, is another cut, another surrender. Let’s make questioning second nature, treating AI as an advisor, not an oracle.Remember, just as with people who may give advice for their benefit rather than ours, AI advice is shaped by datasets that don’t always tell the whole story.3. Preserve Human Connection: The Uncuttable Core AI Can’t ReplicateA basic truth is at the core of The Matrix: human connection is the source of purpose and stability. The many layers of shared experiences, sympathies, and subtleties humans share with one another cannot be replicated by any machine. AI is unable to feel, but it can evaluate data. Although it can mimic speech, it is unable to comprehend our experiences.We must tenaciously defend our humanity as AI takes root. Even if machines are quicker, they are devoid of empathy, intuition, and life experience-based wisdom. We don’t just need smart leaders; we need wise ones. Leaders who rely solely on their intellect must remember that machines will always be “smarter.” Machines have chips; we have hearts.In a world awash in tech marvels, nurturing our humanity isn’t a luxury—it’s essential. Yes, be smart. But be wise. Connect with each other, stay grounded, and refuse to let those thousand cuts erode what makes us distinctly, powerfully human.<span style="font-family: inherit; font-size: calc(18px * var(--body-fontSize, 1)); font-weight: inherit; font-style: var(--body-fontStyle, normal); background-color: rgba(249,250,251,var(--tw-bg-opacity));" data-mce-style="font-family: inherit; font-size: calc(18px * var(--body-fontSize, 1)); font-weight: inherit; font-style: var(--body-fontStyle, normal); background-color: rgba(249,250,251,var(--tw-bg-opacity));">©2025 Yvette Schmitter, All Rights Reserved

AI’s Beauty Standard: Where Do You Fit?

<h3>AI in Finance: Revolutionizing Financial Services Through Ethical Technology</h3>The AI Financial RevolutionAI is a revolutionary force that is changing everything from fraud detection to client interaction in the finance industry today. Imagine a world where your bank account is as alert as a superhero from the Marvel Universe, spotting fraud before it takes place, personalizing services to suit your needs, and making banking as simple as making a coffee order. Nevertheless, tremendous power comes with great responsibility, and the financial stakes for AI are especially high.AI has huge potential in the financial industry. It promises enhanced compliance, proactive fraud detection, and personalized support that transforms routine banking into meaningful encounters. But as much as AI holds the keys to a fairer system, there’s a flip side: poorly designed or biased algorithms can undermine the very trust they aim to build, creating financial harm and further entrenching systemic biases that hit vulnerable communities the hardest – at scale. This is the double-edged sword we must wield wisely.AI's Role In Security: Enhancing Fraud Detection and ComplianceBanks have historically taken a reactive approach to fraud detection, identifying fraud after it has taken place. AI has transformed that playbook today. Advanced algorithms can detect anomalies before they become problematic since they can learn from millions of transactions in real time. When AI notices a pattern that would indicate fraud, such an odd withdrawal from a strange place, it alerts it right away. By increasing public trust and successfully protecting assets, this degree of proactive security turns financial stability from a "maybe" to a "given."AI has changed what used to be an expensive and time-consuming process in compliance. AI transforms compliance from a reactive process to an always-on, active, and persistent safeguard by continuously monitoring transactions for regulatory adherence. This enhances accountability and transparency, which are the cornerstones for restoring trust in the financial services sector.<h3>When AI Goes Wrong: The <a data-mce-href="https://incidentdatabase.ai/cite/92/" href="https://incidentdatabase.ai/cite/92/">Apple Card Gender Bias</a> Incident</h3>However, AI has a darker side, which was made clear in 2019 by the Apple Card. Customers quickly noticed an unsettling pattern when Apple and Goldman Sachs debuted their card: even when their financial profiles were the same or better, women were frequently given lower credit limits than men. Despite their shared wealth, tech entrepreneur David Heinemeier Hansson stated that his wife's credit limit was 20x lower than his. As more women related similar situations, this revelation caused significant outrage.Why? It seemed that the AI algorithms that set credit limits were biased against women. Whether intentional or not, this gender bias had a significant adverse financial impact, reducing women's financial options and perpetuating inequality on an enormous scale. The incident compelled Apple and Goldman Sachs to reassess their algorithms, illustrating the harsh reality of artificial intelligence: even a slight bias in the training data of a model can result in widespread discrimination. In this particular case, human prejudices were merely disguised by technology; it had not been removed.This wasn’t the first, nor will it be the last, time an algorithm exposed inherent biases. AI models trained on historical data reflecting human biases—whether related to gender, race, or income—can inadvertently learn and replicate those biases. A model is just an abstract representation of reality, built on the data choices we make, reflecting our priorities and blind spots. Left unchecked, AI could codify financial discrimination into the very systems designed to democratize access.<h3>The Issue of Exclusion: AI and the Unbanked</h3>The potential for AI to unintentionally exclude people without access to traditional banking services is another significant concern. Due to socioeconomic constraints, inadequate infrastructure, and historical exclusionary practices, formal banking remains out of reach for millions of people worldwide, particularly in rural and low-income areas. These barriers disproportionately affect communities of color and women, who are often the most impacted by financial <a data-mce-href="https://www.fdic.gov/household-survey" href="https://www.fdic.gov/household-survey">exclusion</a>, with challenges compounded by cultural norms and gender inequality. Women, especially in developing regions, frequently rely on cash, informal lending circles, or community networks to meet their financial needs.Since these individuals are "invisible" to the algorithms that drive today's financial systems, which assess risk, creditworthiness, and financial access utilizing indicators like bank activity, credit history, and official transactions, these individuals live in the shadow of datasets. Without these data sets, AI-powered models fail to include many women and underserved people, perpetuating a hard-to-break cycle of exclusion. Building the financial history required to become eligible for loans, credit, or even basic financial services is nearly impossible without access to traditional banking institutions.<h3>The Role of Blockchain in Bridging the Gap</h3>Blockchain offers a promising <a data-mce-href="https://ssir.org/articles/entry/working_toward_financial_inclusion_with_blockchain" href="https://ssir.org/articles/entry/working_toward_financial_inclusion_with_blockchain">solution</a> to this exclusion problem. With its decentralized nature, blockchain enables secure, transparent, and low-cost financial transactions without traditional banking intermediaries, making it especially useful in regions with limited infrastructure.For example, Kenya’s blockchain-based platform <a data-mce-href="https://techpoint.africa/2019/09/30/bitpesa-feature/" href="https://techpoint.africa/2019/09/30/bitpesa-feature/">BitPesa</a> facilitates cross-border payments and remittances, offering faster and more affordable services than traditional methods. This has empowered many, especially women entrepreneurs, to engage in international trade and grow their businesses. During a recent visit to Kenya, I personally witnessed how the Masai tribe utilized these systems to support local economies and uplift communities.<figure id="figure-cke4ttm2u6m4ae8gp3" data-full-width="" class=""><img id="cke4ttm2u6m4ae8gp3" src="https://cdn.durable.co/blocks/8klrnGezPxXDpnhP5gM8tTrIGpXWtx6yMMt91pGBWCDOQL091s4H6XtNFtdFRA7H.jpg" alt="" title="" class="object-cover bg-gray-100 " style="aspect-ratio: 16/9; object-position: 95% 50%;" data-corners="default" data-aspect="16:9" data-caption="Yvette Schmitter with Masai Tribe, Kenya, Africa" data-positionx="95%" data-positiony="50%" data-fullwidth="true" data-mce-src="https://cdn.durable.co/blocks/8klrnGezPxXDpnhP5gM8tTrIGpXWtx6yMMt91pGBWCDOQL091s4H6XtNFtdFRA7H.jpg" data-mce-style="aspect-ratio: 16/9; object-position: 95% 50%;"><figcaption class="body-normal text-gray-500 mt-2">Yvette Schmitter with Masai Tribe, Kenya, Africa</figcaption></figure><h3>Beyond Blockchain: Innovative Solutions for Financial Inclusion</h3>While blockchain is pivotal, other solutions are also closing the financial inclusion gap:1. &nbsp; &nbsp; <a data-mce-href="https://openknowledge.worldbank.org/server/api/core/bitstreams/3a4a072c-94a5-5690-a17d-bb62e45d6896/content" href="https://openknowledge.worldbank.org/server/api/core/bitstreams/3a4a072c-94a5-5690-a17d-bb62e45d6896/content">Mobile Money Services</a>: Platforms like <a data-mce-href="https://link.springer.com/article/10.1007/s11846-022-00564-2" href="https://link.springer.com/article/10.1007/s11846-022-00564-2">M-Pesa</a>, launched in Kenya in 2007, have revolutionized financial access by enabling transactions via mobile phones. This innovation has provided essential services to unbanked populations, with a profound impact on women in rural areas.2. &nbsp; &nbsp; <a data-mce-href="https://www.microsave.net/2021/01/28/addressing-three-key-issues-of-bc-agents-in-india-for-covid-like-challenges/" href="https://www.microsave.net/2021/01/28/addressing-three-key-issues-of-bc-agents-in-india-for-covid-like-challenges/">Agent Banking</a>: In India, the Business Correspondent (BC) model, or agent banking, employs local individuals to offer banking services in underserved areas. By March 2020, over 1.17 million BCs were delivering banking services across India, facilitating financial inclusion, especially during crises like COVID-19.3. &nbsp; &nbsp; Digital Identity Solutions: Establishing a digital identity is crucial for accessing financial services. <a data-mce-href="https://pib.gov.in/PressReleasePage.aspx?PRID=1926374" href="https://pib.gov.in/PressReleasePage.aspx?PRID=1926374">India’s Aadhaar system </a>assigns unique IDs, allowing individuals to open bank accounts and access essential services. In April 2023 alone, Aadhaar facilitated over 1.96 billion transactions, demonstrating its widespread impact on financial inclusion.4. &nbsp; &nbsp; <a data-mce-href="https://www.care-international.org/what-we-do/womens-economic-justice/village-savings-and-loans-associations" href="https://www.care-international.org/what-we-do/womens-economic-justice/village-savings-and-loans-associations">Community-Based Savings Groups</a>: In African and Asian countries, Village Savings and Loan Associations (VSLAs) allow members to pool resources and provide mutual loans. These self-managed groups have supported over 8 million members—primarily women—since 1991, offering critical financial services to those without formal banking.Integrating AI with Alternative Data SourcesAI models must take into account alternative data which reflects the financial habits of individuals outside of traditional banking to be able to better serve unbanked populations. Financial institutions can offer products that are specifically designed for underserved communities and establish more inclusive credit scoring systems with the use of data such as utility payments, mobile phone usage, and community lending trends.<h3>Biases Toward People of Color: A Systemic Challenge</h3>AI holds the potential to eradicate discrimination in finance, but only if it is deployed judiciously. Inequalities are strengthened whenever algorithms trained on historical data inherit preexisting biases. Studies found that compared to their white peers with similar profiles, Black and Latino borrowers are more likely to encounter higher interest rates or loan denials. In one instance, a <a data-mce-href="https://www.philadelphiafed.org/-/media/frbp/assets/working-papers/2024/wp24-09.pdf" href="https://www.philadelphiafed.org/-/media/frbp/assets/working-papers/2024/wp24-09.pdf">study</a> conducted by the Federal Reserve Bank of Philadelphia found inherited biases were mostly to blame for racial differences in mortgage approvals.&nbsp;Consider an AI system assessing loan risk. If the data suggests certain neighborhoods, often home to communities of color, are higher risk, AI will naturally skew its recommendations against these areas. According to <a data-mce-href="https://www.brookings.edu/articles/how-racial-bias-in-appraisals-affects-the-devaluation-of-homes-in-majority-black-neighborhoods/" href="https://www.brookings.edu/articles/how-racial-bias-in-appraisals-affects-the-devaluation-of-homes-in-majority-black-neighborhoods/">Brookings</a>, homes in Black neighborhoods are undervalued by 21% to 23% compared to similar homes in non-Black areas, costing these communities around $162 billion. This undervaluation leads to minority homeowners facing unfavorable loan terms or being denied refinancing options.<h3>Moving Forward: Building Inclusive, Fair AI in Finance</h3>To maximize AI’s strengths while minimizing risks, financial institutions need a multi-pronged approach:1. Diverse Data: AI systems should be trained on representative datasets that reflect real-world diversity. Alternative data sources, such as rental history and utility payments, help provide a fuller picture for those lacking traditional credit history.2. Bias Audits and Transparency: Regularly auditing for biases is essential. Financial institutions must also ensure transparency, allowing regulators and the public to understand AI decision-making processes.3. Inclusive Design Teams: Diverse design teams can identify potential pitfalls and assess how models might impact different groups. This isn’t just ethical; it’s practical for creating accurate AI systems.4. Community Partnerships: Collaborating with nonprofits and community groups can introduce financial services to unbanked communities in accessible ways, while also helping institutions understand these communities’ unique needs.<h3>Building Financial Systems for All</h3>The promise of AI in finance isn’t just about profit; it’s about creating a fairer, more inclusive system that serves everyone. AI’s power, when harnessed for good, can democratize access, but this requires more than good intentions. It requires transparency, vigilance, and a commitment to confronting our data’s hard truths.A diversified strategy that makes use of cutting-edge models and technologies is required for financial inclusion. Digital identification solutions, agent banking, blockchain, mobile money, and community-based savings are all helping to close the gaps in financial inclusion. We can create a financial environment that genuinely benefits everyone, irrespective of their ability to use conventional banking services, by combining these technologies and creating AI systems with inclusivity in mind.As financial institutions increasingly rely on AI, it’s essential to ask hard questions and take bold steps to ensure these tools empower rather than exclude. For example, do you have the right data, or are you substituting stand-in data or proxies to draw statistical correlations? Let’s build a future where financial security, access, and opportunity aren’t privileges but rights. Because when we harness AI for good, we’re not just changing an industry; we’re building a world where we rise the tide so everyone has a seat at the financial table.©2025 Yvette Schmitter, All Rights Reserved

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Yvette Schmitter

My name is Yvette Schmitter, and I’m a dynamic, international motivational, keynote speaker and technology leader on a mission to transform the future of tech into a force that includes and uplifts us all. Drawing from my expertise in AI, cloud computing, and digital transformation, I empower audiences to lead with courage, dismantle barriers, and create solutions that bridge divides and drive lasting impact. Let’s build a future where innovation isn’t just progress—it’s progress for all. Join me in shaping the future we all deserve. My mission is to redefine the future of technology by championing innovation that includes and empowers all. As a trailblazer in the tech industry, I lead with purpose and passion, ensuring that every room where decisions are made is filled with diverse perspectives, so that technology truly serves humanity—not just a privileged few. By breaking down barriers and building bridges, I’m committed to creating a tech landscape where every voice is heard, every experience is valued, and every community has the opportunity to thrive.


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