Every year, over 700,000 workers, students, and apprentices from low‑income countries arrive in the EU needing €2,500–€12,000 upfront to cover visa fees, language tests, qualification recognition, and relocation. No one finances this. Banks won't touch it. Families go into debt.
the company Advance is our answer: an income‑share agreement product that finances migration costs and collects repayments via employer‑mediated payroll, once the worker is placed and earning. The SAM is €6.4B/year in the EU alone. Nobody has built this. You will.
Tasks - What you’ll do
* Build the ISA underwriting model — default probability by borrower profile, income trajectory assumptions, and loss‑given‑default curves — without credit bureau data
* Set income‑share rates and repayment caps by borrower cohort
* Stress‑test the portfolio against macroeconomic shocks, default clustering, and income interruption events
* Structure the warehouse debt facility — tranche sizing, loss triggers, investor reporting
* Define the path to ABS securitisation at scale
* Lead regulatory classification of the product under BaFin and AFM consumer credit frameworks
* Co‑own the company as a founding team member
Requirements - What you bring
* Part‑qualified or fully qualified actuary (SOA, IFoA, or DAV) — or equivalent depth in structured credit, consumer lending, or quantitative risk
* Hands‑on experience building credit scorecards, PD/LGD models, or pricing models — not just studied them
* Comfort underwriting thin‑file or no‑file borrowers — emerging‑market or migrant lending experience is a strong differentiator
* Working knowledge of structured finance mechanics: waterfalls, tranching, loss absorption, warehouse facilities
* Founder mindset — you want to build, not maintain
Benefits
* Greenfield category — not many comparable ISA products for this market in Europe
* Cofounder equity + reasonable comp
* Structural collection advantage that no standalone lender can replicate
* Direct path to ABS and institutional debt capital at scale
How would you build a default probability model for a worker from the Philippines entering the German labour market, with no German credit history? Walk us through the variables, data sources, and assumptions.
#J-18808-Ljbffr