{"paper":{"title":"Financial Forecasting and Analysis for Low-Wage Workers","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.AP","authors_text":"Jinfeng Yi, Karthikeyan N. Ramamurthy, Kryn Anderson, Kush R. Varshney, Lingfei Wu, Raya Horesh, Wenyu Zhang","submitted_at":"2018-06-14T04:49:50Z","abstract_excerpt":"Despite the plethora of financial services and products on the market nowadays, there is a lack of such services and products designed especially for the low-wage population. Approximately 30% of the U.S. working population engage in low-wage work, and many of them lead a paycheck-to-paycheck lifestyle. Financial planning advice needs to explicitly address their financial instability.\n  We propose a system of data mining techniques on small-scale transactions data to improve automatic and personalized financial planning advice to low-wage workers. We propose robust methods for accurate predict"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.05362","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}