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5 Ways Smart Data is Enhancing the Future of Search-Based Analytics

The face of the financial industry has and continues to change rapidly as technology advancements create opportunities to reduce costs, increase revenue, and simplify the entry process into new markets. Relatively new tech like blockchain, machine learning functions, and artificial intelligence are all beginning to have an impact on the industry. In addition, Big Data is providing firms with more information than ever before. The dilemma is, most of them don’t know what to do with all of it.

There is a growing need for a method to aggregate data and impose business strategy onto emerging technologies. While Big Data and machine learning provide data sets that were previously unreachable, they also created a need for ways to intelligently engage with that information. An emerging solution called Smart Data has the potential to solve these problems and help firms adapt faster to developments in fintech. I recently connected with Patrick Koeck, Chief Operations Officer at Creamfinance, a leader in the Smart Data movement, to find out more.

Q: What is Big Data lacking in and what it can do for financial institutions?

Koeck: Big data contributes a high volume of information, and can be assessed on its velocity, veracity, and value. While data delivered at a high velocity may have high accuracy, or veracity, its value is limited by the institution’s capability to compile and evaluate it.

Big Data is bulky and it lacks the precision needed for many important financial decisions. Smart data gets to the core of the information, allowing executives to zero in on important issues rather than waste time on extraneous or distracting information.

I’m not advocating for Big Data to go away, I just think it has a time and a place. Aggregation of that data is what the finance industry needs, and that’s where Smart Data delivers.

Without a way to process and derive meaningful insights, Big Data is just a seemingly endless line of random information.

Q: What is Smart Data?

Koeck: Smart data sifts through the mire of Big Data and only selects data sets with high value to the institution.

The whole point is to solve business problems – large and small. Information that doesn’t contribute to this goal can be sidelined. Since Big Data does not focus on any particular subset of information, Smart Data usage translates into focus on quality instead of volume.

Qualitative data analysis opens up opportunities for firms to speed up the data delivery process, which allows for more time to develop creative solutions.

It’s also important to emphasize the gravity of data-driven decision-making. Firms have been leveraging various forms of Big Data for the better part of a decade, and many of them are beginning to seek out ways to improve its effectiveness and ease of use. By eliminating the irrelevant data, firms will be able to contextualize their findings and use them to make better business decisions.

Q: What are Search Based Analytics?

Koeck: Searched Based Analytics are platforms, or search engines, for Big Data application and are therefore connected to raw data instead of processed data like typical BI software. It provides faster access to data and a great variety of content, but is also a little slower at “digesting” data simply due to its volume. It is raw and it’s big, so naturally search based analytics, much like BI, can be given to non-technical people only with a proper training.

As for monitoring usage and personal reports, it could provide substitutional uplift to the employees as they become independent in their work. However, once again, it is worth noting that being exposed to large amounts of raw data can fail to pass the test of user-friendliness, usability, and accuracy.

Q: How is Smart Data Changing the industry?

Koeck: Smart Data is shifting the focus from quantity to quality information. Personal finance is a prime example as to how Smart Data can revolutionize current practices. We identify statistical patterns in online data and combine this with credit intelligence from traditional sources to uncover precise credit and repayment trends. Behavior patterns differ across demographics and regions. Creamfinance is able to approve most personal loans on the day of inquiry, with a high rate of success. Don’t believe that is possible? Creamfinance has grown from a small financial startup to a multinational firm operating in 6 countries across Europe and is opening in South America before the end of the year.

Big data gets jumbled and less useful as it increases in volume. Smart Data’s value, on the other hand, increases with volume, because all the data points have already been selected based on their value. In some ways, Smart Data gets smarter with volume. Trend analysis and comparisons are also made easier with valuable data points already selected for rapid access. Overall, Smart Data makes it easy to leverage data for real results.

Creamfinance is using Smart Data to change the way short-term loans work for consumers. Since firms aren’t currently effective at assessing risk quickly they often miss opportunities to provide loans to low risk customers.

By refining our algorithms on a regular basis we are able to expedite the loan approval process while maintaining the highest standard of risk management.

About the author

Nick Hastreiter

I write about the future of business. I approach this by interviewing founders, CEO's, and other game changers to share their vision for the future of their industry.

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