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CIO Applications Weekly Brief

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Editor's Pick (1 - 4 of 8)
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Driving Innovation through Business Intelligence

Driving Innovation through Business Intelligence
John Matelski, CIO and Director of Information Technology, DeKalb County Government

Business Intelligence a Top Priority in 2016, Again?

Business Intelligence a Top Priority in 2016, Again?
Ben Stewart, CIO, Stant USA Corporation

Unleashing the Power of Analytics in Academics

Unleashing the Power of Analytics in Academics
Leebrian E Gaskins, AVP-IT & CIO, Texas A&M International University

Why Current Business Intelligence Tools Are Missing the Mark

Why Current Business Intelligence Tools Are Missing the Mark
Steve Brennan, VP, Data Strategy and Analytics, Carhartt

Bust the myths of Self-Service Business Intelligence

Bust the myths of Self-Service Business Intelligence
Raj Polanki, US Head of Analytics & Data Science, Wacker Chemical Corporation

The First Steps to BI Adoption

The First Steps to BI Adoption
Kjersten Moody, Chief Data and Analytics Officer, State Farm

AI-enabled business transformation: Closing the gaps

AI-enabled business transformation: Closing the gaps
Shilpa Yelamaneni, Director of Data Science and Advanced Analytics, Ecolab

Applying Deep Learning to Streamline Healthcare Administration

Applying Deep Learning to Streamline Healthcare Administration
Sanji Fernando, SVP Artficial Intelligence & Analytics Platforms, Optum

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Transforming Financial Services with BI

By CIO Applications| Friday, November 30, 2018
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As more and more organizations across industry verticals implement business intelligence (BI) to enhance their efficiency and reduce their workload, financial institutions are also no longer far behind in the technology race. Analytics and the use of machine learning have helped banking and financial institutions sort the data to increase its client retention capabilities. Big data is fed into BI solutions to discern the customers who are willing to carry on their business with the institution and those most likely to end their contract. These insights can be leveraged by banks and finance companies to offer more attractive incentives to drive customer satisfaction and increase loyalty.

The data analysis regarding discounts and other incentives has helped banks reduce financial loss and increase their profit margins by eliminating the unnecessary offers to clients that cannot pay back loans. Moreover, business intelligence analysis provides banks with the advantage of deciphering customer preferences and expectations from their credit and debit card statements, attraction to specific bank features, investment trends, point-of-sale data, online banking statements, and mobile payments. With these insights, the banks can build a customer-centric business model to match their customer preferences.

Even though it is hard for financial institutions to analyze the exponential amount of unstructured data and maintain data privacy, the positive effects outweigh the whole challenges of using data analytics.   

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