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Big Data – Banks need to mine this wealth to unlock growth

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The Banking Industry has evolved leaps and bounds over the past decade with proliferation of digital data from smart devices, internet of things and Blockchain. Most digital data is unstructured (emails, videos, weblogs, chat, documents, etc) making Big Data the apt platform for building new age applications. Winning in this digital marketplace will be underpinned by “how Banks can derive value from data”.

Banks are rapidly transforming themselves into “data-driven” organizations, treating data as a corporate asset, underpinning their business strategy and day-to-day decision-making. They are investing in Big Data platforms that combine structured and unstructured data and leveraging analytics to obtain powerful insights to drive enriched customer experiences, improve operating efficiencies and reduce risk. The convergence of machine and human intelligence is disrupting traditional decision-making by equipping organizations with knowledge and insight to predict and prescribe business outcomes. Advances in Big Data and Analytics are leading to new products and differentiated services making Banks smarter, agile and more competitive.

There are multiple areas that Banks can explore to drive enhanced value and growth:

Consumer and Commercial Banking

• Customer lifetime value analytics, customer call center analytics and deposit growth analytics

• Voice of customer analytics to measure customer sentiment in the social media and help that influence the strategy

• 360 view of customers to enable cross-sell and upsell

• Democratizing customer servicing leveraging Artificial Intelligence

• Real-time personalized offers by analyzing customer profile and historical purchase behavior

• Analyze multiple service delivery channels to uncover consumer behavior patterns and understand channel profitability

• Measuring campaign effectiveness to continuously refine the marketing strategy
Fraud and operations

• Reducing financial losses through real time fraud detection and prevention
Governance, risk and compliance

• Supporting new regulatory and compliance requirements through stronger policies, procedures and governance practices leveraging newer technologies

• Predictive credit risk models that tap into large amounts of payment data to prioritize collections

• Optimizing delinquency models that can predict the probability of loan default
Capital markets, cards and payments

• Augmenting card and customer data with new-age parameters to derive competitive product pricing models, innovative loyalty schemes, assess creditworthiness for underwriting and recommend optimal lines of credit

• Deriving deeper insights into portfolio performance, liquidity positions and working capital requirements

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Article Credit: ET Tech

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