  We present an AutoML system called LightAutoML developed for a large European
financial services company and its ecosystem satisfying the set of
idiosyncratic requirements that this ecosystem has for AutoML solutions. Our
framework was piloted and deployed in numerous applications and performed at
the level of the experienced data scientists while building high-quality ML
models significantly faster than these data scientists. We also compare the
performance of our system with various general-purpose open source AutoML
solutions and show that it performs better for most of the ecosystem and OpenML
problems. We also present the lessons that we learned while developing the
AutoML system and moving it into production.
