Company: T-Mobile US, Inc Company background:
T-Mobile US, Inc. is America’s supercharged Un-carrier. Through our Un-carrier strategy, we have disrupted the wireless communications services industry by actively engaging with and listening to our customers and focusing on eliminating their existing pain points. This includes providing added value and what we believe is an exceptional experience while implementing signature Un-carrier initiatives that have changed the wireless industry. We ended annual service contracts, overages, unpredictable international roaming fees and data buckets, among other things. We are inspired by a relentless customer experience focus, consistently leading the wireless industry in customer care by delivering award-winning customer experience with our “Team of Experts,” which drives our record-high customer satisfaction levels while enabling operational efficiencies.
With America’s largest, fastest, most reliable and most awarded 5G network, the Un-carrier strives to offer customers unrivaled coverage and capacity where they live, work and travel. We believe our network is the foundation of our success and powers everything we do. Our “layer cake” of spectrum provides an unmatched 5G experience to our customers, which consists of our foundational layer of low-band, our mid-band and our millimeter-wave (“mmWave”) spectrum licenses. Our layer cake broadens and deepens our nationwide 5G network, enabling accelerated innovation and increased competition in the U.S. wireless and broadband industries.
As of December 31, 2022, we provide wireless communications services to 113.6 million postpaid and prepaid customers and generate revenue by providing affordable wireless communications services to these customers, as well as a wide selection of wireless devices and accessories. We also provide wholesale wireless services to various partners, who then offer the services for sale to their customers. Our most significant expenses relate to operating and expanding our network, providing a full range of devices, acquiring and retaining high-quality customers and compensating employees. We provide services, devices and accessories across our flagship brands, T-Mobile and Metro by T-Mobile, through our owned and operated retail stores, as well as through our websites (www.t-mobile.com and www.metrobyt-mobile.com), T-Mobile app, customer care channels and through national retailers. In addition, we sell devices to dealers and other third-party distributors for resale through independent third-party retail outlets and a variety of third-party websites. Contact: Qing Ye Title: Principle Data Scientist
Country: United States Award Category: Innovative Problem Solver Tell us about the business problem you were trying to solve?
Two main problems:
1) Monthly Current Expected Credit Loss (CECL) model with 25 regressions using one massive sequential do-loop and cost 24+ hours system CPU time. Obviously it is too much long for business operation.
2) T-Mobile’s $750 Million Asset-Backed Bond Sale TMUST 2022-1 with critical deadlines from agency, auditing and lawyer. How did you use SAS to solve that business problem? What products did you use and how did you use them?
1) CECL model, using SCAGRID functions and optimized parallel processing, the total CPU time is significantly reduced from 24+ hours to 4 hours (83% executive time saved)
2) T-Mobile’s Asset-Backed Bond Sale: Converted all excel manual work into SAS automation, Work time from three work days to 6 hours (70% executive time saved)
What were the results or outcomes?
1) Generated the forecasting %write-off$ of AR balance from month 1-25 from monthly CECL model to support the Accounting team's business operation and booking.
2) Automation work for Stratification package; Cumulative Gross Loss (CGL) package and prepayments timing curves, other support analytic packages. Why is this approach innovative?
Qing Ye is the Frist one in the T-Mobile Finance department who applied these SAS procedure and parallel processing on the Expected Credit Loss model, and the First one who converted all complicated time-consuming Excel manual work into SAS code plus output delivery automation. Over 80% executive time was saved.
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