Data Driven Digital Transformation
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Aligning your business to the data driven economy, how data is the new oil, importance of algorithms in a data driven world and their benefits for different industries, and new use cases of digital data.
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Future and scope of big data analytics in Digital Finance and banking.
Big data analytics is a powerful tool for banking and finance that can increase revenue, enhance customer engagement, and optimize risk. For example, Reliance Jio was able to gain 100 million users in a short time by collecting customer data to design profitable plans. Banks like ICICI have used analytics to improve debt collection, reduce turnaround time, and automate loan allocation. Leading banks now use analytics to personalize customer service, connect with customers on important dates, and provide a unified customer view across channels. As big data applications and analytics continue to grow, it presents career opportunities for finance professionals to adopt these new skills.
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Big Data Analytics in light of Financial Industry
Big data and analytics have the potential to transform economies and competition by delivering new productivity growth. Effective use of big data can increase operating margins over 60% for retailers and save $300 billion in US healthcare and $250 billion in European public sector. Companies that improve decision making through big data have seen a 26% performance improvement over 3 years on average. Emerging technologies like self-driving cars will rely heavily on analyzing vast amounts of real-time sensor data.
Data Analytics for Finance
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Insurance value chain
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Role of business analytics in the banking industry
Banking analytics can help banks improve customer segmentation, acquisition, and retention. It also enhances risk management, customer understanding, and fraud prevention. Examples show how analytics helped a bank reduce customer churn by 15% through targeted campaigns, increase bank revenues by 8% by correcting unnecessary discounts, and increase products per customer three times over through microsegmentation. In conclusion, analytics provides banks marketing advantages and helps optimize risk, compliance, and decision-making.
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Future and scope of big data analytics in Digital Finance and banking.
Big data analytics is a powerful tool for banking and finance that can increase revenue, enhance customer engagement, and optimize risk. For example, Reliance Jio was able to gain 100 million users in a short time by collecting customer data to design profitable plans. Banks like ICICI have used analytics to improve debt collection, reduce turnaround time, and automate loan allocation. Leading banks now use analytics to personalize customer service, connect with customers on important dates, and provide a unified customer view across channels. As big data applications and analytics continue to grow, it presents career opportunities for finance professionals to adopt these new skills.
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How can you utilize Big Data in the Financial Industry? To leverage Big Data - entrepreneur and finance expert Jonah Engler, has put together this presentation to help the slideshare community understand the value - and HOW TO - use big data in the financial campaigns.
Jonah Engler is a financial expert and stock broker based in NYC. Leveraging his experience in finance, Engler has gone on to have success in the franchise, coffee, startup industries and more. To connect with Jonah - checkout his profile on LinkedIn: https://www.linkedin.com/in/jonahengler
Role of business analytics in the banking industry
Banking analytics can help banks improve customer segmentation, acquisition, and retention. It also enhances risk management, customer understanding, and fraud prevention. Examples show how analytics helped a bank reduce customer churn by 15% through targeted campaigns, increase bank revenues by 8% by correcting unnecessary discounts, and increase products per customer three times over through microsegmentation. In conclusion, analytics provides banks marketing advantages and helps optimize risk, compliance, and decision-making.
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2) Adoption of Hadoop for risk applications is still in early stages, with a focus on regulatory reporting. Capital markets has led adoption so far.
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Data Driven Digital Transformation
- 1. Aligning your Business to the Data Driven Economy Anil Chopra VP-Research and Consulting CyberMedia Research
- 3. Data is the New Oil Data is to the new economy what oil was to the old Organizations that are able to collate and analyze their data gold mine to draw insights from it will thrive Quantitative and structured data like name, address, etc. not enough to gauge human behavior Unstructured data is critical, as info like social media profile, smartphone usage habits, online reviews, etc. puts context into what people really want and help you understand them better Traditional Market research no longer enough to understand customers Interconnections between IoT devices will further create billions of new relationships that will not be driven by data, but by algorithms.
- 4. Welcome to the Algorithm Economy! Algorithms form core of all insights and actions from data, and will power all M2M communication using IoT. New products and services based on sophisticated algorithms to emerge. Algorithms already used extensively in digitally led companies
- 5. Every Industry Stands to Benefit Manufacturing • Predictive Maintenance (repair, re-build, or replace?) • Compare failure rates of parts from different manufacturers • Balance supply with demand by analyzing demand for your products • Hire skilled workers vs new and train them Healthcare • Identify, evaluate, and compare treatment options • Analyze vital statistics from bedside medical devices • Predict possible disease outbreaks and dive into their root cause Education • Gauge education effectiveness • Plagiarism detection • Predict student’s future performance • Scheduling algorithms to optimize teaching policy BFSI • Anti-money laundering • Chatbots • Algorithmic Trading • Fraud Detection • Customer Recommendations • Improve pricing accuracy on insurance products • Portfolio management
- 6. It’s Not Just About Data, but What You Do With It! Use Cases are Growing Customer Service Customized Loyalty Programs Speech Analytics TV Analytics Predictive Analytics Weather Analytics Contextual Analytics
- 7. Summary Data is the common denominator to convert your digital vision into business results Customer intelligence paramount in the digital age to enhance their experience, understand their needs, analyze their journeys across channels, increase loyalty, etc. You need an analytics-based business strategy and the relevant tools to convert data into information. Use external data sources like data.gov.in from the Govt. of India Start adopting an insights driven culture--move from gut-feel culture to an 'insights-driven' one
- 8. Thank you! “War is 90% Information” ~Napoleon Bonaparte