Our listening and scoring platform delivering Intelligent Analytics services.
The universe of data is growing at an exponential rate, and today’s AI, cognitive and predictive systems are hungry for more. The big challenge is finding the data and signals that drive optimal business decisions.
KPMG Signals Repository can help. Leveraging the latest decision science, Signals Repository continuously harvests a broad variety of signals from public and private sources to help organizations get the edge in their decision-making.
With KPMG Signals Repository, structured and unstructured data is transformed into complex expressions, creating tens of thousands of signals when used by machine learning and other AI systems, and helps our clients significantly improve the accuracy in predictions. Signals Repository is an accelerator for data scientists and next generation developers. By creating a ‘big data fabric’ of exogenous and endogenous data, organizations can find the right data and signals to enable their AI and machine learning technologies to achieve unprecedented accuracy in predictions and business execution outcomes.
To optimize any business activity, you need to understand all of the data available to you — from your own internal and customer data to competitor and market data. We work with organizations to identify and collect the right signals from the growing universe of data including structured and unstructured data.
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What is the Signals Repository? A collection of sources (data) that is harnessed to interpret the impact of internal and external factors (signals) on a company’s execution, to help organizations derive insights from the patterns (indications), and to accelerate and affect meaningful decision-making on a continuous basis. Leveraging KPMG Signals Repository, it’s easy to “listen” to the tens of thousands of Signals around us and then use Machine Learning to make sense of it all.
With the majority of Signals geo-tagged and the majority of sources captured over time, the KPMG Signals Repository is especially helpful when building predictive services that leverage temporal-locational understanding; this is made for improved Machine Learning and better outcomes. Our services are customized to handle different requirements around input, analysis and results so that the services meet the needs of the business
Identify unique drivers of demand for each trading area, then use to select locations that maximize revenue
Found local market dynamics that contribute to higher employee attrition plus drive intelligently recommended fixes
Pinpoint local competitive offerings that leach individual customer engagement and generate smart interventions
Continuously monitor entire United States, market-by-market to detect and highlight unusual market performance
Watch local events, e.g. school calendars and road construction, to spot and alert to conditions that will shift demand
Augment traditional property & casualty underwriting models to include customer-specific exogenous factors
Isolate trading area attributes that “pull through” demand for each asset type, then leverage to “outfit” each location
Complement top-down Revenue Forecasting services with a bottoms-up equivalent and blend the 2 to improve accuracy