AFTAs 2016: Most Cutting-Edge IT Initiative: Sell Side—Credit Suisse
Credit Suisse is the latest organization to win the sell-side most cutting-edge IT initiative category for its CPA analytics offering.
The importance and popularity of analytics systems have been evident across both sides of the capital markets for some time now, so it’s a testament to the capabilities of Credit Suisse’s Client Predictive Analytics (CPA) suite that the Waters judges have selected it as the most cutting-edge IT initiative for the past 12 months.
With previous winners in this category including alternative trading systems, a dark pool with a speed bump, and an alternatives house client portal, the Swiss bank’s CPA solution is a prime example of a large banking institution streamlining internal technology operations.
Credit Suisse has created a set of predictive analytics capabilities that excel in optimizing both human and economic capital resources, based on a big-data platform that leverages machine learning and statistical monitoring, Cloudera Hadoop, Alteryx and Tableua technologies.
Technical innovation is a key element within this category and the CPA suite achieves this through several distinct functionalities, covering enhanced client targeting and outreach, real-time labor time study and coverage management, intelligent resource optimization modeling, and maximizing the value of the bank’s client relationship networks across its operations.
Client targeting is enhanced by a Dynamic Call List, which utilizes machine-learning algorithms applied to client and market data, including historical trading, public filings, online readership, call reports, and sales feedback. All of this combines to inform decision making and remove legacy processes, such as maintaining multiple call lists and client-tier spreadsheets.
Technical innovation is a key element within this category and the CPA suite achieves this through several distinct functionalities, covering enhanced client targeting and outreach, real-time labor time study and coverage management, intelligent resource optimization modeling, and maximizing the value of the bank’s client relationship networks across its operations.
The suite’s time modeling leverages data across electronic communications lines—email, chat, phone calls, calendars and events—to predict the amount of time personnel spend with clients, providing analysis on how to drive changes in client coverage.
Intelligent resource modeling aims to maximize returns on institutions’ right-sizing available portfolios of financial and human resources by optimizing the use of balance sheets and risk-weighted assets, while the suite’s client relationship network allows users to leverage its big-data platform, databases and visualization tools to create and manage all analysis on clients or individuals.
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