Women in Pakistan remain significantly under\u2011represented in formal finance and the digital economy. Only 12% of the women are banked as opposed to 42% men in the country. Deep gender gaps in account ownership, digital access and economic participation mean that the coming wave of AI-driven financial services risks amplifying existing inequalities unless we act now. For a deep dive into numbers, please refer to GSMA\u2019s mobile gender gap report 2025, Karandaaz Financial Inclusion Survey (K-FIS) and World Bank\u2019s Pakistan Development Update Report April 2025.<\/p>\n\n\n\n
According to State Bank of Pakistan (SBP) targets and national diagnostics, Pakistan launched the Banking on Equality agenda in 2021 precisely because women are disproportionately under\u2011served by the financial system and require targeted policy measures to close the gap. The global and regional evidence is clear1<\/a><\/sup>: without sex-disaggregated data, fairness testing and deliberate design, AI models reproduce historical bias instead of expanding opportunity.<\/p>\n\n\n\n When I opened the doors of WIN<\/strong>2<\/a><\/sup> Incubator – Pakistan\u2019s Micro Finance Industry\u2019s First Women Incubator<\/strong> – at Mobilink Bank a year ago, I didn\u2019t expect a single neat narrative to emerge. I expected messy, brave entrepreneurship: mothers building home\u2011based supply chains, young women quietly scaling cosmetic micro\u2011brands via social media platforms. What arrived in the First Cohort surprised me: ambition, humility and grit! This was further amplified in Cohort Two where I saw a wave of founders embedding AI into their business models. Currently, ten of our startups are embedding AI into their business models.<\/p>\n\n\n\n That pivot, from analog resilience to digital ambition, is the hinge on which financial inclusion and gender justice can swing. To make that hinge real, the WIN Incubator functions as a practical lab where women founders pilot ideas, generate women-specific data signals, and graduate with stronger business plans, market connections, clearer pathways to finance, and the operational confidence to scale. Over the course of the year, we have graduated more than 30 startups. More than a training programme with access to network and finance; WIN is a living dataset and a talent pipeline: graduates feed the bank\u2019s product and R&D teams so those teams reflect the Examples of promising WIN start-ups embedding AI into their business models are:<\/p>\n\n\n\n These startups may still be in the early days of AI, but what sets them apart is that they\u2019re being led by women founders. Women founders, by design, are more likely to embed gender-disaggregated data into their models, reducing bias at the very foundation of their technologies. This not only makes their solutions more inclusive but also creates a powerful multiplier effect for the communities they serve.<\/p>\n\n\n\n This is my story as the Head of Strategy & Sustainability at Mobilink Bank: of building the Micro-Finance Industry\u2019s first incubator for women micro\u2011entrepreneurs, of leaning into the Central Bank\u2019s gender agenda, of translating the lessons learnt into inclusive AI by advocating for credit scoring models that recognize women\u2019s realities, datasets that capture gendered nuances, and digital tools that don\u2019t just enable women entrepreneurs but embed them in the digital footprint, amplify their reach and ripple impact across communities rather than gatekeeping inequality.<\/p>\n\n\n\n The policy moment in Pakistan is unambiguous. The Central Bank\u2019s \u2018Banking on Equality\u2019 framework sets clear operational targets – from workforce gender ratios to active women digital accounts – and positions sex\u2011disaggregated monitoring as a governance requirement. Mobilink Bank leaned into this policy direction early on. For the last two years, Mobilink Bank has consistently topped Banking on Equality metrics. Earlier this year, the Bank also become a signatory for the Women Entrepreneurs Finance Code (WE Finance Code), committing to Across the Asia Pacific, regulators and industry leaders are learning a hard lesson: innovation without governance often amplifies existing inequalities. Banks are the natural stewards of fairness because they hold three crucial assets – trust, distribution and data. But those assets carry responsibility. If banks apply AI to underwriting using male\u2011skewed histories or incomplete samples, they risk automating exclusion. A practical solution to this problem is simple to its core: measure sex\u2011disaggregated baselines, collect representative data, adopt fairness\u2011aware algorithms and deploy human oversight and remediation.<\/p>\n\n\n\n Globally, there are already early signs of how gender-disaggregated data can be embedded into AI models in banking. Lendingkart in India<\/strong>3<\/a><\/sup>, for instance, applies machine learning to alternative datasets such as GST filings, bank statements, and e-commerce sales to underwrite small businesses. In partnership with Women\u2019s World Banking, its models were stress-tested for gender bias, leading to adjustments that ensured women-owned enterprises were not systematically disadvantaged. Similarly, TymeBank in South Africa<\/strong>4<\/a><\/sup> has deployed AI-enabled credit scoring and Buy Now Pay Later (BNPL) models that draw on transaction flows, mobile usage, and behavioural data. Working with CGAP, the bank conducted gender-disaggregated audits of these models, re- When I write of Mobilink Bank, I include JazzCash\u2019s 50 million\u2011strong customer base: a distribution advantage that can make inclusive AI not just possible, but scalable. Here are the five priority actions that Mobilink Bank can take going forward based on the global use cases shared earlier.<\/p>\n\n\n\n Bringing women into the AI and digital finance economy is an economic multiplier: it creates jobs, raises household welfare and strengthens resilience. Mobilink Bank has the regulatory alignment, the distribution reach, and a testbed in the WIN Incubator to begin exploring this journey. The next step is careful experimentation – piloting, validating, and learning – before moving to scale. Done right, this disciplined approach will make \u2018Creating a Women-First AI Moment\u2019 possible: turning gender data gaps into verifiable digital value for women and the wider economy.<\/p>\n\n\n\n The author is Senior Vice President, Strategy & Sustainability at Mobilink Microfinance Bank. The views expressed in this article are the author\u2019s own and do not necessarily represent those of Mobilink Microfinance Bank.<\/em><\/p>\n\n\n <\/p>\n","protected":false},"excerpt":{"rendered":" Women in Pakistan remain significantly under\u2011represented in formal finance and the digital economy. Only 12% of the women are banked as opposed to 42% men in the country. Deep gender gaps in account ownership, digital access and economic participation mean that the coming wave of AI-driven financial services risks amplifying existing inequalities unless we act […]<\/p>\n","protected":false},"author":74,"featured_media":55133,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_oasis_is_in_workflow":0,"_oasis_original":0,"_oasis_task_priority":"","_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_feature_clip_id":0,"_jetpack_memberships_contains_paid_content":false,"footnotes":"[{\"content\":\"Reports: Gender Parity in the Intelligent Age 2025; UN Women How AI Reinforces Gender Bias 2025\",\"id\":\"0c2c28bb-98e8-461a-b436-ab125c646ece\"},{\"content\":\"WIN \u2013 Women Inspirational Network is a program aimed to address gender disparities and foster a more inclusive economic environment\",\"id\":\"849364f7-3544-4317-b0ea-fd928407340f\"},{\"content\":\"Women World Banking<\/a>\",\"id\":\"f96e671a-0d20-4bd8-a3e2-5853305756fa\"},{\"content\":\"CGAP<\/a>\",\"id\":\"03d6c3f2-3eca-4ebd-b990-2077d5b0fe96\"},{\"content\":\"BBVA<\/a>\",\"id\":\"b522d2cf-3e6d-4d75-9e8b-ef9cac10ea03\"}]","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","enabled":false},"version":2},"jetpack_post_was_ever_published":false},"categories":[3732],"tags":[],"algolia_discover_type":[],"class_list":["post-55131","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-changetheface"],"yoast_head":"\n
customers they serve. This practical laboratory is what makes WIN not just an incubation success, but a strategic lever for Mobilink Bank\u2019s women-first AI ambition.<\/p>\n\n\n\n\n
expand credit and products for women entrepreneurs and to adopt gender\u2011disaggregated data practices. These steps are not symbolic. They rewire incentives, embed measurement and create the preconditions for responsible, inclusive AI.<\/p>\n\n\n\n
weighting risk predictions to improve access for women while maintaining portfolio quality. BBVA<\/strong>5<\/a><\/sup> in Spain and Mexico<\/strong> has gone further by embedding gender fairness testing into its AI-driven credit risk engines. In collaboration with Women\u2019s World Banking, BBVA reviewed how approval thresholds and repayment predictions differed for men and women and adjusted its models to expand lending to women entrepreneurs without raising default risk.<\/p>\n\n\n\n\n