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The very act of diversifying trade patterns itself does not come without any risk, as transport costs are likely to grow, and companies are forced to operate in unfamiliar markets with unfamiliar bureaucracy. Add in currency and creditrisks, and it’s by no means an easy pivot to make.
Identify opportunities for innovation. Innovation continues to be a source of promise for Big Data. Success stories of Big-Data-enabled innovation remain relatively few at this stage. Success stories of Big-Data-enabled innovation remain relatively few at this stage. Prepare for cultural and business change.
” For example, if a person was deemed a low creditrisk, granted a loan, and then defaulted on that loan that would be a false positive. The model falsely predicted that the person had low creditrisk. And it needed to operate alongside existing data science workflows so the innovation process is not hindered.
Ash Gupta is President of Global CreditRisk and Information Management at American Express, and Guy Peri is Chief Data Officer and Vice President of Information Technology at P&G. Their fundamentally sound innovation practices provide a foundation for evolution. Address applications that benefit you and the customer.
Think of the colleges that are increasingly able to identify students at risk of dropping out and intervene before they do. Or lenders’ enhanced abilities to gauge creditrisk. Energy, agriculture, insurance, retail, human resources — no industry is unaffected. But this shift shouldn’t just be about capabilities.
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