Analyzing Data Issues in Finance from an Analytics Viewpoint | Quantzig

Feb 24, 2021

Growing competitive pressures from non-banking financial service providers are driving financial organizations to transform themselves to gain a competitive edge digitally. To become truly data-driven and transform digitally, banking firms must address the data issues in finance that span three key areas- data volume, ubiquity, and user demand.

The diversity of data available today can provide valuable insights to tackle the long-standing issues in finance. Data from mobile apps and online user-generated data in various formats like images, audio, and video can provide businesses with opportunities to gain additional insight and value when combined with new business models. Contact us to know how analytics can help you tackle data issues.

Issues in Finance

Given the ubiquity of big data in finance, today its imperative for financial services companies to capture data on customer information, financial transactions, purchase histories, customer journeys, marketing campaigns, service inquiries, market feeds, social media streams, Internet of Things (IoT) streams, software logs, and other new data sources. By capturing and leveraging these data sets, financial services companies can capitalize on new data-driven business opportunities. But the first step toward addressing data issues in finance revolves around creating a robust foundation that supports the analysis of both business data and big data in finance.

Addressing Data Issues in Finance with Advanced Analytics

Risk modeling and fraud detection

Risk management is one of the most significant issues in finance. Risk monitoring and risk management systems based on real-time big data processing can help mitigate operational risks and combat fraud and other issues in finance while also helping alleviate data asymmetry problems to achieve regulatory and compliance objectives.

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Big data in finance

Big data analytics can help businesses identify new opportunities to improve outcomes on investments through predictive modeling. An in-depth algorithmic understanding and use of big data can result in accurate predictions and enhance the ability to mitigate risks in real-time.

Customer data management

Customers are at the heart of every business around which data insights, operations, technology, and systems revolve. Thus, big data initiatives underway by banking and financial companies are focused on leveraging customer analytics to provide better service to customers.

To learn more about our advanced analytics solutions designed to tackle issues in finance – Request more information.

How Quantzig Can Help Address Data Issues in Finance

The expertise and exposure gained by working with clients from across the globe have helped Quantzig to build advanced analytics solutions to tackle data issues in finance. Our teams specialize in working capital, wealth management, banking, and capital markets, and insurance and have helped businesses tackle the biggest challenges in financial services sector in the past. Even in an uncertain economic environment, we can help you find ways not just to stay afloat but also gain an edge. Whether you’re preparing for regulatory changes, leveraging analytics, digitizing processes, or rethinking your business strategy, we work hand-in-hand with you to resolve complex data issues in finance, identify new opportunities and enhance business value through data-driven insights.

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