Flaiver designs and builds credit-risk and regulatory platforms for lenders and investment fund managers — forecasting, stress testing and portfolio data, engineered end to end.
From macroeconomic expected-credit-loss forecasting to million-row portfolio data — the tools risk teams use every day, designed to be clear under pressure.
Macroeconomic default-rate, loss-given-default and expected-credit-loss forecasting across weighted stress scenarios, with history and forecast on one clear chart.
Loan-level datasets at scale, ready in minutes. Plug in via native connectors to your existing data tables, then browse, filter and query millions of records with risk-banded flags.
Configure severity, weights and time-to-peak per scenario, with real-time updates to expected credit losses. Understand what's driving month-to-month movements, with sensitivity and attribution analysis.
Browse, filter and query loan-level datasets with the kind of density banking analysts expect — without the clutter. Sticky identifiers, risk-banded flags and instant query building.
Rate movements, unemployment, GDP and other macro drivers, streamed live via API. Always current, ready to feed straight into your scenarios and models.
Built on hardened Django authentication with session security, CSRF protection and role-based access — the standards banks require, handled properly.
I’ve spent a quarter of a century building software, and more than a decade of that deep inside financial institutions — where I learned that credit-risk systems fail not from a lack of maths, but from a lack of a consistent framework for applying it.
Flaiver is where those two careers meet: banking-grade rigour, delivered as software that people genuinely want to use. I design, engineer and ship it end to end.
Whether it’s a credit-risk platform, a regulatory model, or a legacy system that needs rescuing — I’d be glad to hear about it.
michelle@flaiver.ai