White paper: data science for banking and insurance
Over the course of many centuries, the banking and insurance industries have developed processes, products and infrastructures that have shaped the economic history of humankind.
But now, they are threatened with extinction by challengers 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 start-ups like Credit Karma, Lending Club, Square, Lemonade, TransferWise and GoFundMe; and even, through the internet of things (IoT), wholly unlikely competitors like manufacturers of consumer and industrial goods.
Banks and insurance companies can fight back by accelerating the digitisation path they have been on for some time, and enriching it with the tools of the newcomers’ trade – namely, data science, big data and algorithms. As they do so, they should also make maximum use of their unique assets, including talent with much sought- after expertise in mathematics and statistics, deep subject matter knowledge sorely lacking in many data science endeavors, a massive, largely untapped reservoir of customer data, and a network of physical branches and offices that can deliver a human edge in the quest for meaningful, multi-channel and multi-sensory customer experiences.
However, 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.
The disruptive threat is real, but the battle is not lost. Download this white paper for practical advice on surviving and thriving in the era of internet giants and fintech start-ups.
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