Built by People Who Know Finance
We started burstinggleam in 2019 because we saw too many financial institutions struggling with outdated credit assessment methods. There had to be a better way to evaluate risk using modern technology.
That was the simple idea that got us moving. And honestly, it still drives everything we do.
Where We Actually Came From
Three of us met while working at a mid-sized bank in Bangkok. We spent our days reviewing loan applications and credit scores, always feeling like the traditional methods missed important patterns in the data.
Late one night in 2018, over terrible office coffee, we started sketching out what a machine learning approach might look like. Not replacing human judgment entirely, but giving analysts better tools to work with.
By early 2019, we'd built our first prototype. It wasn't perfect. But when we tested it against historical data, the patterns it found were genuinely useful. That's when we knew we had something worth pursuing full-time.
What We're Actually Good At
After six years of refining our approach, we've gotten pretty specific about what we do well. These aren't marketing claims. They're just the areas where our clients consistently tell us we've made their work easier.
Pattern Recognition
Our models find relationships in financial data that traditional scoring misses. We've trained them on diverse datasets from across Southeast Asia, which gives them context most generic tools lack.
Implementation Support
We don't just hand you a model and disappear. Our team works alongside yours during rollout, helping interpret results and adjust parameters based on what you're actually seeing.
Regional Expertise
Working primarily with Thai financial institutions has taught us about local market dynamics, regulatory considerations, and the specific challenges teams face here. That context matters.
Meet Thanawat Preecha
Machine Learning & Financial Risk Specialist
Thanawat heads our training programs and works directly with financial teams implementing our scoring models. Before joining burstinggleam, he spent eight years in credit risk analysis at two major Thai banks.
What makes his teaching approach different is that he's been in the exact position our clients are in. He knows what it's like to present machine learning insights to skeptical loan committees. He understands the pressure of defending a scoring model's recommendation when it contradicts conventional wisdom.
His workshops starting in September 2025 focus on practical application rather than abstract theory. You'll work with real anonymized datasets, encounter actual edge cases, and learn how to explain model outputs to non-technical stakeholders. Because that's what you'll need to do in your actual job.
Want to Talk About Your Scoring Needs?
We're happy to discuss whether our approach might work for your institution. No pressure, just a straightforward conversation about what you're dealing with.
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