This paper presents a novel heuristic for correcting scan pose estimations after loop closing in SLAM using 3D laser scans. Contrary to state of the art approaches, the built SLAM graph is sparse, and optimization is done without any iteration between the SLAM front and back end, yielding a highly efficient loop closing method. Several experiments were carried out in an urban environment and evaluated against ground truth. The results are compared to other state of the art algorithms, proving the high quality, yet achieved faster by an order of magnitude.