Published by Gbaf News
Posted on December 6, 2016

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Published by Gbaf News
Posted on December 6, 2016

Florian Douetteau, co-founder and CEO of Dataiku
Traditional companies in banking and insurance can use data science to survive the era of internet giants and financial technology startups.
Over the course of many centuries, the banking and insurance industries have developed processes, products and infrastructures that have shaped the economic structure of humankind. But now, they are being challenged by industry outsiders who appeared on the world stage a mere couple of decades ago, and some who emerged just a scant few years ago, but who nonetheless are already rewriting the rules of financial services. These challengers include Internet-era giants like Google, Amazon, Facebook, Apple, Baidu and Alibaba; nimble digital startups like Credit Karma, Lending Club, Square, Lemonade, TransferWise and GoFundMe; and even, through the Internet of Things, wholly unlikely competitors like manufacturers of consumer and industrial goods.
Ultimately, GAFA (Google, Amazon, Facebook, Apple) has a Big Data and algorithm advantage. However, banks and insurance companies can fight back by accelerating their digitization path and utilizing their own advantages in big data and data science. Specifically, traditional banks and insurers can leverage existing assets that give unique advantages over non-traditional challengers in their industries, namely:
Traditional banks and insurers are at an advantage here, if they make optimal use of their network to build relationships. Regional managers at companies like Bank of America and M&T Bank are, for example, seeing a real evolution as their physical branches morph into advising centers for customers, with one regional M&T manager noting a swing in service activity underway from 80% transactions and 20% expert advice to 20% transactions and 80% expert advice.
Success depends on the speed with which traditional banks and insurers respond to these new challengers, in their skillful exploitation of their competitive assets, and in assembling the right people, data, tools and processes to get the job done.
Equipped with the right people, processes and tools, traditional banks and insurance companies can not only avoid the fate of becoming the backend plumbing for GAFA and fintech challengers, they can appropriate the advantages of these newcomers and merge them with their own to become the new marketplace innovators of the 21st century.
To learn more about how Data Science can play a role in traditional Banking and Insurance download the free whitepaper from Dataiku here: http://pages.dataiku.com/advanced-analytics-for-banking-and-insurance2-0
Florian Douetteau, co-founder and CEO of Dataiku
Traditional companies in banking and insurance can use data science to survive the era of internet giants and financial technology startups.
Over the course of many centuries, the banking and insurance industries have developed processes, products and infrastructures that have shaped the economic structure of humankind. But now, they are being challenged by industry outsiders who appeared on the world stage a mere couple of decades ago, and some who emerged just a scant few years ago, but who nonetheless are already rewriting the rules of financial services. These challengers include Internet-era giants like Google, Amazon, Facebook, Apple, Baidu and Alibaba; nimble digital startups like Credit Karma, Lending Club, Square, Lemonade, TransferWise and GoFundMe; and even, through the Internet of Things, wholly unlikely competitors like manufacturers of consumer and industrial goods.
Ultimately, GAFA (Google, Amazon, Facebook, Apple) has a Big Data and algorithm advantage. However, banks and insurance companies can fight back by accelerating their digitization path and utilizing their own advantages in big data and data science. Specifically, traditional banks and insurers can leverage existing assets that give unique advantages over non-traditional challengers in their industries, namely:
Traditional banks and insurers are at an advantage here, if they make optimal use of their network to build relationships. Regional managers at companies like Bank of America and M&T Bank are, for example, seeing a real evolution as their physical branches morph into advising centers for customers, with one regional M&T manager noting a swing in service activity underway from 80% transactions and 20% expert advice to 20% transactions and 80% expert advice.
Success depends on the speed with which traditional banks and insurers respond to these new challengers, in their skillful exploitation of their competitive assets, and in assembling the right people, data, tools and processes to get the job done.
Equipped with the right people, processes and tools, traditional banks and insurance companies can not only avoid the fate of becoming the backend plumbing for GAFA and fintech challengers, they can appropriate the advantages of these newcomers and merge them with their own to become the new marketplace innovators of the 21st century.
To learn more about how Data Science can play a role in traditional Banking and Insurance download the free whitepaper from Dataiku here: http://pages.dataiku.com/advanced-analytics-for-banking-and-insurance2-0