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An Alternative Method for Vintage Forecasting Using SAS®

About this paper

The ability to anticipate, track and control behavior of a group of accounts established during the same time period (i.e. "vintage") underpins marketing activity and risk management policy at financial institutions. This paper presents a technique that treats the components of the vintage as a set of predictions and forecasts from a cross-vintage data stream. This methodology includes a variety of analytical techniques, including time series analysis, dynamic segmentation and clustering, vintage "profiling" and forecast reconciliation. An integrated approach to vintage curve modeling unifies internal bank drivers, external economic factors and past performance into one cohesive strategy – free from internal biases and more closely aligned with market reality. This methodology can serve to provide critical insight that supplements an institution's sales and operations planning process.

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SAS는 분석 부문의 선두 기업입니다. SAS는 8만여 곳 이상의 기업에 혁신적인 분석, 비즈니스 인텔리전스(BI), 데이터 관리 소프트웨어와 서비스를 제공함으로써, 고객사가 신속하고 정확한 의사결정을 내릴 수 있도록 지원합니다. SAS는 1976년부터 전 세계 고객사에게 ‘THE POWER TO KNOW’에 입각한 서비스를 제공하고 있습니다. THE POWER TO KNOW®.

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