AML Data with Python

AI-generated illustration 🚌 Try it yourself — Bus Fare Calculator BD This case study is based on a real, live product. Check it out below. Get Bus Fare Calculator BD → My inbox pinged at 9:17 am on a rainy Thursday. A small boutique in Old Dhaka wrote: “Our site loads in 12 seconds on 3G, sales dropped 30% last month. Can you help?” I was still sipping chai, half‑asleep, and the numbers hit me like a brick. 12 seconds? That’s longer than most people wait for a bus. I pulled up the PageSpeed Insights report – LCP 9.8 s, Total Blocking Time 4 s, and a Lighthouse score of 42. The client had a WordPress theme that hadn’t been touched in three years, a handful of plugins, and a CDN that was basically a glorified static file host. The Hidden Problem: WordPress + Bad Assets ≠ Speed Most indie businesses in Bangladesh think “just install a caching plugin and we’re good”. They ignore three brutal facts: Most visitors are on 3G/4G with data caps – every extra kilobyte costs them. WordPress ...

AI-generated illustration 🚌 Try it yourself — Bus Fare Calculator BD This case study is based on a real, live product. Check it out below. Get Bus Fare Calculator BD → My phone buzzed at 6 am. The client – a two‑person food‑delivery startup in Banani – had just received a 4‑star rating on Google Play, but the real problem was hidden in the analytics dashboard: 8‑second page loads on 3G , a 45 % bounce rate, and a $1,200 daily revenue dip. Why Most Freelancers Miss the Real Caching Question We all love the buzzword offline‑first . We read it on the MDN docs, we brag about it in Upwork proposals, and we sprinkle it into cold‑email pitches. But the default Service Worker template that the CLI hands you is a blunt instrument. It forces a network‑first strategy on every request, assuming the network is always faster. In Bangladesh, that assumption is a lie. My first attempt was to stick the boilerplate in, hope for the best, and move on to the next gig. The result? The PWA still waite...

Photo by shahin khalaji on Unsplash 🚌 Try it yourself — Bus Fare Calculator BD This case study is based on a real, live product. Check it out below. Get Bus Fare Calculator BD → Real‑World Hook I was staring at my inbox on a rainy Saturday in Gulshan, coffee cooling beside my laptop, when the reply pinged. "We love your numbers, but can you guarantee a 90 % Lighthouse score?" The client was a boutique tea shop in Old Dhaka, selling hand‑rolled blends on a clunky WordPress theme. Their page load was 5.6 seconds on 3G, and the Lighthouse Performance tab screamed 38 / 100. I replied with a cold‑email that quoted a $1,200 fix, promising a perfect score in two weeks. They said yes. Two weeks later, the site still loaded slower than a rickshaw on a pothole‑filled road, and the client’s sales dip was 12 %. That $1,200 turned into a $0 win and a bruised reputation. The Hidden Problem Most freelancers treat Lighthouse like a badge‑collector’s trophy. They chase the perfect 100, slap...

Photo by Peo Hedin on Unsplash 🚌 Try it yourself — Bus Fare Calculator BD This case study is based on a real, live product. Check it out below. Get Bus Fare Calculator BD → Real‑World Hook I was staring at my inbox on a rainy Tuesday in Gulshan. One cold‑email reply. BDT 1,200 earned. The subject line? “Your site’s Lighthouse score is 42 % – let’s fix it.” The prospect? A boutique clothing shop on Daraz with a 3‑page static site, hosted on a cheap shared server. Their bounce rate was 78 %, cart abandonment 85 %. I replied, attached a PDF, and waited. Two days later, the owner called. He’d seen the report, was terrified of losing traffic, and asked for a quick fix. I quoted BDT 1,200 for a “quick win”. He said yes. I delivered a PWA‑style service worker, compressed images, and a 1.2 s improvement. The shop’s traffic spiked 27 % in a week. That’s the story that started this deep dive. The Hidden Problem Most freelancers treat Lighthouse scores like a vanity metric. They copy‑past...

AI-generated illustration Bangladesh, 09/28/2026. My phone buzzed at 02:17 am. An alert from our real‑time MFS monitor flashed: BDT 3,245,876 moved across three Rocket accounts in 12 minutes, all under the BFIU’s BDT 100,000 threshold. My gut screamed – this was a structuring ring about to explode. I fired up the back‑testing suite we’d built two years ago, expecting a clean hit list. The report came back empty. Zero alerts. My heart sank. Two weeks later, the regulator knocked. A formal audit discovered that our back‑testing methodology was blind to exactly the pattern we’d just seen. The BFIU cited us for “inadequate validation of detection logic.” I was forced to shut down the alert engine for a week while we rewrote the whole thing. The Hidden Problem: Why Most Bangladeshi Backtests Miss the Real Threat Everyone tells you to “split your data 70/30, train on the past, test on the future.” Sounds neat. In reality, our local MFS landscape throws that rule out the window. Transaction ...

AI-generated illustration High‑Stakes Hook It was 02:17 am on a rainy Tuesday. My phone buzzed with a red badge: “STR # B‑2026‑0147 – BDT 9.8 million structured over 48 hours.” The alert came from the MFS monitoring engine at bKash, but the case file was empty, the audit log showed a dead‑end, and the senior compliance officer was already on a conference call with the BFIU. Within minutes the whole desk was on fire. The senior analyst shouted, “Where are the supporting documents? Why is the workflow stuck?” The system had thrown a “case‑state‑transition error” after the third escalation, and every analyst downstream was staring at a blank screen. The regulator was breathing down our necks, and the potential penalty for a missed SAR could be BDT 5 million plus reputational damage. The Hidden Problem Most Bangladeshi fintechs build a case management layer on top of an off‑the‑shelf ticketing system. They assume the generic “open → assign → resolve” flow will catch everything. In practi...

AI-generated illustration 🚌 Try it yourself — Bus Fare Calculator BD This case study is based on a real, live product. Check it out below. Get Bus Fare Calculator BD → It was a rainy Thursday in Gulshan. My inbox pinged – a reply from a boutique textile shop in Mirpur that had just read my cold‑email. They’d looked at the Lighthouse report I’d attached, saw a 55 % performance score, and asked: ‘Can you fix this? We’re losing customers.’ I replied, "Sure, let’s chat," and booked a Zoom call for 3 PM. Fast forward two weeks: the shop’s PWA now scores 92 % on performance, 97 % on accessibility, and their sales jumped 18 %. The client paid BDT 45,000 – a tidy win for a solo freelancer. The Hidden Problem: Why Most Lighthouse Cold‑Emails Crash and Burn Most freelancers copy‑paste a generic Lighthouse link, write a one‑liner, and hit send. They assume the score alone will close the deal. Reality check: a 55 % score is a red flag, not a selling point. It tells the business they’re ...

🚌 Try it yourself — Bus Fare Calculator BD This case study is based on a real, live product. Check it out below. Get Bus Fare Calculator BD → AI-generated illustration Real‑World Hook It was a rainy Tuesday in Gulshan. I stared at my laptop, coffee cooling, and saw a new notification: "You have a new lead!" The lead was a small boutique bakery, “Sweet Crumbs”, that’d just posted a Lighthouse report with a 62 Performance score. Their owner, Rafiq, was desperate—sales had dipped 12% since the last month, and his site was loading in 6 seconds on a 3G dongle. I drafted a cold email, slapped the Lighthouse score in the subject line, and hit send. No reply. After three more attempts, I realized I’d burned $1,200 of my own ad‑budget chasing a dead‑end. The Hidden Problem Most freelancers think a Lighthouse number is a magic bullet. “Your site scores 45, hire me!” sounds persuasive, but the reality in Bangladesh is messier. Local SMEs juggle: Spotty 3G/4G coverage tha...

🚌 Try it yourself — Bus Fare Calculator BD The app from this case study is live and free on the Microsoft Store. Check real fares and distances between any two points in Bangladesh. Get Bus Fare Calculator BD → AI-generated illustration My phone buzzed at 2 am. A client in Chittagong—owner of a tiny bus ticket kiosk—had just sent a screenshot of his PWA crashing on a 3G phone. The error: Service worker failed to fetch . He was losing 12 % of daily riders because the app wouldn’t load on the cheapest data plan. I had promised a fast, offline‑first fare lookup that would survive Dhaka’s 3G black spots. I was staring at a deadline, a frustrated client, and a pile of assumptions that I’d never questioned. The Hidden Problem Most Indie Developers Overlook Everyone talks about “offline‑first” as a buzzword. The reality in Bangladesh is far harsher: average 3G latency hovers around 2.8 seconds, data caps cost BDT 15 per gigabyte, and many commuters share a single 4G hotspot...

Photo by Mark Chan on Unsplash High‑Stakes Hook It was 02:13 am on a rainy Thursday. The BFIU inbox pinged, a SAR arrived, and the numbers screamed: BDT 4.2 million moved through three Rocket accounts in under five minutes, each just under the BDT 100,000 threshold. My team’s alert list was a sea of noise—1,200 warnings per hour, most of them false. The system timed out, the dashboard froze, and senior management started asking, “Did we miss a structuring ring?” I stared at a blinking red line on a Grafana panel and felt the weight of an audit looming. The Hidden Problem Standard batch‑oriented monitoring works in banks that process a few thousand wires a day. In Bangladesh’s mobile‑financial‑services (MFS) world, transaction velocity is a different beast. bKash, Nagad, Rocket—all push millions of micro‑payments per hour. The BFIU guideline Rule 3.2.1 tells us to watch any series of transactions that cumulatively cross BDT 100,000 within a 24‑hour window, but it does not prescribe ...