  In this paper we present SPot, an automated tool for detecting operating
segments and their related performance indicators from earnings reports. Due to
their company-specific nature, operating segments cannot be detected using
taxonomy-based approaches. Instead, we train a Bidirectional RNN classifier
that can distinguish between common metrics such as "revenue" and
company-specific metrics that are likely to be operating segments, such as
"iPhone" or "cloud services". SPot surfaces the results in an interactive web
interface that allows users to trace and adjust performance metrics for each
operating segment. This facilitates credit monitoring, enables them to perform
competitive benchmarking more effectively, and can be used for trend analysis
at company and sector levels.
