A working portfolio, not a résumé.
Thirty AI initiatives at Askari Bank — eleven live, eight in testing — built, deployed and run in-house. Code we own. Models we can inspect. Infrastructure we run.
Sep 2024 – Present
Askari Bank.
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I built the bank's centralised AI function from a standing start — hiring the team, setting the operating model, and taking the bank's first AI systems into production in-house. The unit is small and in-house by design: we build the models the bank runs, keep the code and weights where we can inspect them, and operate the infrastructure ourselves rather than renting a black box.
That shapes what we ship: production GenAI inside a regulated environment — open-source-first, self-hosted, and instrumented before it scales. Voice banking, cash optimisation, compliance screening, and document work are live; each one earns its place by replacing a capability the bank used to buy.
I also serve as Secretary to the President & CEO's "Bank of the Future" forum — setting the agenda and benchmarking the bank's AI transformation against the digital-first playbooks that reset the standard for the industry.
The discipline is the same one I brought from the lab: measure before you procure, keep data inside the bank's network, and let the numbers — not the vendor — decide.
VP & Unit Head — AI & Machine Learning · Jan 2026 – Present
Unit Head — AI & Machine Learning · Oct 2025 – Jan 2026
Senior Data Scientist · Sep 2024 – Oct 2025
A team I hired and lead — thirty AI initiatives, eleven already live, every one built and run in-house. Code we own, models we can inspect, infrastructure we run ourselves.
The programme
VoicePay
Banking for people who cannot type: 14 voice tasks in Urdu, English, Punjabi and Pashto. More than 20,000 people use it every day, and every one of the bank's 2.3 million customers can.
Askari Buddy
A 24/7 assistant on the bank's website. Roughly 1,500 calls a month moved off the phones, across 20,000 messages and 8,000 conversations.
Cash Optimisation
PKR 3B of surplus branch cash released in just 1 quarter. It forecasts what every branch needs and moves the rest back to work.
A private AI copilot for the whole bank
The bank's own assistant for every employee, running on models the bank hosts itself. Nothing leaves the building.
AI email triage
500+ customer emails a day read, sorted and routed to the right owner, answered within SLA.
Conversation intelligence
AI that listens to service calls, scores their quality, and spots the product each customer is likely to need next.
An AI financial-crime stack
165,000+ names screened every day at full coverage, by six tools across sanctions, adverse media, trade-based money laundering and fraud.
Credit scoring for farmers
A scorecard that lets the bank lend to farmers on data rather than paperwork, widening credit to people banks usually miss.
The full portfolio
Conversational AI
8- Askari Buddy, the website assistantLive
- Branch operations assistantLive
- IT and information-security assistantLive
- WhatsApp banking assistantIn testing
- Compliance advisory assistantIn testing
- Credit-risk assistantIn testing
- Bank-wide AI copilotIn testing
- AI-assisted account openingIn build
Voice & conversation
3- VoicePay, voice bankingLive
- Call-quality monitoring and agent scoringIn testing
- Cross-sell from customer callsIn build
Financial crime
6- Adverse media searchLive
- Sanctions and watchlist reconciliationLive
- Trade-based money laundering analyticsLive
- Fraud case summarisationLive
- Terrorism-incident searchIn build
- Financial-crime case managementIn build
Documents & email
5- AI email triageLive
- Case-handling automationIn testing
- Automated cheque processingIn build
- Trade-document data extractionIn build
- Documentation drafting and reviewIn build
Prediction
5- Cash optimisationLive
- Credit scoring for farmersIn testing
- Churn and dormancy predictionIn build
- Smart recovery managementIn build
- Undrawn-commitment reportingIn build
Operations
3- Lease and property managementLive
- Capex and opex trackingIn testing
- Customer-information platformIn build
Consulting
9- ECG heart-signal classification with neural networksDelivered
- Machine learning on wearable biosignalsDelivered
- Single-cell RNA data clusteringDelivered
- Street-sweeper efficiency predictionDelivered
- Snowflake data architecture for analyticsDelivered
- AWS data lakehouse for a US consultancyDelivered
- Employee-retention model for an HR-tech startupDelivered
- Financial-data (XBRL) parsing and validationDelivered
- Cross-market product matching for a European retailerDelivered
Infrastructure & operations
The systems above run on a production AI platform the unit built and operates itself: a self-hosted, containerised setup on Docker infrastructure we manage, with GPU inference on dedicated VRAM held with a service provider. Nothing leaves the bank's network for a model call, and the models stay ours to inspect and retrain.
Capacity was engineered empirically rather than bought to spec. We proved that production load was constrained by system memory, not VRAM, and re-architected accordingly — a decision worth more than PKR 100 million against the alternative.
An AI function is an operating model, not a pile of models.
01
Scored, not argued
Quantitative use-case scoring replaced subjective High/Medium/Low prioritisation. Executive leadership now uses it for portfolio-level investment decisions.
02
One platform, not twelve
Shared inference, retrieval, and observability rather than a bespoke stack per project. New systems inherit the platform instead of rebuilding it.
03
Governed before release
A standard security and governance review runs before anything ships. No model reaches production without it.
04
Measure before you procure
Benchmark the real bottleneck before signing anything. That discipline is why the portfolio runs on models we own rather than licences we rent.
The remit, not just the build.
- Hired and leads a six-engineer team, running up to ten interns alongside it at peak
- Owns the annual AI/ML budget and every AI procurement decision
- Secretary to the President & CEO's “Bank of the Future” forum
- Designed and runs an AI internship programme fielding over a thousand applicants a year
Built to survive a regulator.
- NIST AI Risk Management Framework
- OWASP LLM Top 10
- Model risk management
- Responsible AI & regulatory response