Big Data and data analytics are enabling the financial services industry to monitor results – and possibly predict them.
Big Data is playing a growing role in financial services in several ways. Specifically, predictive analytics and real-time decision making is becoming more of a reality to financial advisors and their clients, even in a sector where past performance is no indicator of future behavior.
Making financial decisions, whether it’s to purchase a stock or give a loan, requires data points, and the more data available to the client or bank, the more accurate of a decision that can be made. Big Data has opened the spigot as it were, bringing in a flood of information.[…]The flood of data is forcing changes at banks in a number of ways. Kaushik Deka, CTO of Novantas, which specializes in banking industry analytics, said the number of data sources has exploded, both in structured and unstructured data. That has put a little stress on the models that requires a new way of thinking.
“Now they have to think how they deliver insight back to banks and customers. It’s forcing them to think in new ways and how to harmonize different data sources to utilize new analytics,” he said.
The focus is more customer-centric, whereas before it was more product-centic. “It’s all about customer behavior analytics and data related to the customer. Banks have moved from product pricing to customer-centric pricing,” he said.
The other change is around the delivery of analytics. It used to be a batch process would be run on models on a weekly or monthly basis and decisions were made weekly and monthly. Now the real time nature of positioning has come into play.
“Models are run more frequently and decisions are made more frequently. There is still an element of human judgement made in decision making. We did not take human element out of the equation. With expertise, decision making has changed from batch to real time,” said Deka.
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