Veracity of data for finance: New vocabulary

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Managing and augmenting the veracity of this data is essential for harnessing its power in every sector of the economy by 2015.

Managing and augmenting the veracity of this data is essential for harnessing its power in every sector of the economy by 2015.

What it means

Financial decisions require confidence in the veracity of data on which they are based. The challenge is that by 2015, 80 percent of the world’s data will be uncertain.

Data uncertainty arises from many sources and in many ways: as inconsistencies, ambiguities, technical errors, time delays, assumptions, and even sarcasm and outright deception.

The challenge is how to deal with uncertainty when analyzing big data. How do we represent uncertain data, reduce the uncertainty of data, and reason about that data in a way that allows us to make sound business decisions? New approaches are emerging to account for uncertainty in data at a giant scale.

Why it’s important

CFOs likely have more experience in dealing with uncertain data than any other c-suite member. But there is a difference between accounting for model assumptions and incorporating vast oceans of the new data types now appearing into sound corporate decision making. And the most explosive data growth is coming from uncertain sources – natural language text, images, videos, audio and sensors that are often in unpredictable environments. This data is expected to grow by 800 percent over the next five years, and 80 percent of it will be uncertain. [Source: Gartner 2010 Top IT Trends list].

This uncertainty matters when an organization’s value depends on its ability to derive insight from data. When facing decisions on risk, transforming business models, and finding new opportunities for growth, it needs the richest and most up-to-date view of the world possible. And that view cannot come solely from clean, structured data. Consider fraud detection in the insurance industry. Incorporating unstructured data from customer correspondence, voicemails and external records on the Internet provides additional context that can help identify whole new patterns of fraud. Or consider algorithmic trading that constantly monitors social media to spot trends and initiate trades in fractions of a second. Big data is changing the very basis of competitive advantage.

What will change

Data veracity is a challenge. Even in traditional domains where relevant data is largely captured in databases—such as sales, customer service and billing—data has many inconsistencies.

Managing uncertain data at scale requires a new approach to organizing the billions of data fragments associated with people and entities, gathering evidence from multiple sources, and creating context to gain insights and drive financial decisions. That’s a particular challenge for CFOs, who are constantly balancing the need for strategic insight with the traditional need for back-office accounting, reporting and compliance.


The veracity of data is increasingly important in a world where uncertain data dominates and organizations are valued on their ability to turn data into insights. By nature, CFOs tend to dislike uncertainty. In the era of big data, organizations must approach uncertainty differently—embrace it and determine how to use it to advantage.

As companies implement new approaches to automating the management of uncertain data, it’s also an opportunity to make data more useful. People often aren’t able to process the massive amounts of data they encounter. By capturing, sharing and visualizing the uncertainty in data, we can engage the business, improve the quality of insights, and increase trust and understanding in data-driven decisions.

Key questions to ask

  1. What else can our data tell us if we triangulate it with _______? (e.g. social media data or market data)
  2. If we could capture and understand it better, what external data might help us reduce risk?
  3. Correlation helps in prediction. Do we know how our data correlates with _______? (e.g. economic indicators, weather or seasonality)
  4. Do we have the skills in the finance or CIO function to create a strategy for increasing data veracity?

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