Numerical linear algebra (NLA) forms the computational backbone of modern quantitative finance. Whether it’s solving large systems of equations in risk modeling, factorizing covariance matrices for portfolio optimization, or performing regression in model calibration, efficient and reliable linear algebra techniques are essential. This chapter explores the theoretical foundations and practical C++23 implementations of key matrix factorization methods widely used in finance.