A regional healthcare provider carried several legacy loans with high effective rates and rigid structures. By using Lumina Fintech’s AI credit assessment and AI loan matching, the provider identified refinancing opportunities, restructured its facilities with more suitable lenders, and is on track to save an estimated RM4.5M in interest and fees over the life of its loans.
projected savings in interest and fees after refinancing high-cost facilities using AI insights
Over years of expansion, the provider had accumulated a mix of term loans and revolving facilities arranged at different times and rates. With interest costs rising and covenants tightening, the finance team wanted to know whether better structures were possible—but manually comparing refinancing options across lenders would be complex and time-consuming. They needed a way to quantify potential savings and identify which loans to restructure first.
Lumina Fintech imported the provider’s existing loan schedules, repayment history and financial statements into the AI credit assessment engine. The platform simulated multiple refinancing paths, showing how changes in tenure, lender and pricing would impact total interest paid. Using AI loan matching, we then identified lenders comfortable with the healthcare sector and designed a phased refinancing plan that minimised disruption.
RM4.5M in projected savings over the full term of the refinanced facilities, based on lower rates and optimised tenures.
A clearer, data-backed refinancing roadmap that allowed management to phase changes instead of renegotiating everything at once.
Reduced concentration risk by diversifying lenders, while keeping covenants aligned to operational realities.
Finance leaders now use Lumina’s AI credit assessment regularly to test new borrowing and investment scenarios before committing.
A weekly, executive-level decision mechanism to guide the process and solve problems as they arise.
"I hired Lumina Fintech for a small project & was very happy. He not only answered all my questions, but he didn't treat me like a 'small project'. I was very satisfied & would recommend."
