Stibo Systems Blog

To make money from data requires insightful data.

Data monetization is generally understood as the “process of using data to obtain quantifiable economic benefit” (Gartner Glossary, Data Monetization). Three typical ways to achieve this, include:

• Using data to make better decisions and thus enhance your business performance
• Sharing data with business partners for mutual benefit
• Selling data as a product or service

Whichever way you choose, data monetization gets more profitable if you can provide context to the data and make it insightful. The more insight your data provides, the more valuable it is. Take as an example a person about whom you know the job title. That is basic master data. Adding to that information the insight that the person has recently changed jobs, can open new business opportunities or guide your marketing efforts to be more targeted. Perhaps the job change entails a salary increase, a change of location, new business connections, etc.

In this article, you will find some data monetization examples and use cases and learn how master data management, specifically multidomain master data management can help provide data insight.

In short, master data management (MDM) can help build insights by adding context to information and creating 360° views of customers and businesses. Multidomain MDM is characterized by common governance of different data domains, thus revealing enhanced insights at the intersections of those domains.

• Learn more about Multidomain MDM

 

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Unified and enriched customer information can enhance your data analytics and provide actionable customer insight for corporate and investment banks

Relationship managers need insightful customer information upon which they can take action. Sometimes a single piece of unique information can give relationship managers in corporate and investment banks the edge they need to decide how to move an opportunity forward, or indeed avoid being exposed to risk. The availability and trustworthiness of that piece of information relies on the quality and richness of the data that is being analysed.

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The unique identification of a customer and the processing of complete, accurate and timely customer data are of vital importance in the corporate and investment banking service industry. However, many banks struggle to keep up with the changing demands and preferences of their corporate customers.

A recent survey found that 46% of corporate customers are less than satisfied with their banker’s ability to support new customer on-boarding with more than 60% of issues linked to accuracy, documentation and duration¹; areas in which timely access to complete, accurate and insightful information is key. Banks wishing to identify growth opportunities by industry, by segment and by product find it challenging to support their relationship managers with reconciled information from across the entire business.

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Although it’s been almost 28 years, since Bill Gates said, “Banking is necessary. Banks are not” (1990), they are more relevant than ever. The banking industry has in a lot of ways already felt the shaking in its foundation during some years, as innovative digital financial services providers – the so-called FinTechs - have entered the market and now to a certain degree compete with traditional brick and mortar banks. (Learn more about it in the blog post: Traditional banking vs new financial disrupters: Who’ll win the data battle?)

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A new breed of financial services providers is currently disrupting the industry - delivering a whole new way of meeting the needs of today’s consumers.

Crowd-sourced investment funds, independent online investment and wealth management advisers, and mobile-only banks such as Atom and Monzo live on their customer's laptops and mobile devices, offering more flexibility, agility and convenience than their physical counterparts.

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