The leading knowledge platform for the financial technology industry
The leading knowledge platform for the financial technology industry

A-Team Insight Blogs

Is Big Data Just a Big Distraction?

By Chris Ford, Capco

Everyone is talking about big data. But the hype around the big data concept clouds a clear discussion on the current and actual needs of the financial services sector. The temptation of any new technology is to embrace it and then go looking for a problem to solve. More appropriately, banks should identify a prioritised business agenda, and then go looking for the right solutions.

Generally speaking, data housed by financial institutions just isn’t large or complex enough to require new technology. Big data may be intriguing, but for financial services it is a solution that is mismatched to the majority of problems that banks face. If your bank cannot reliably identify the same customer across lines of business, you are probably not ready for big data. If your bank cannot determine the profitability of targeted products and offers over their lifetime, you are probably not ready for big data.

The majority of information held by financial institutions comes in the form of structured data, most notably the information about its customers and their relationship to the accounts and products offered. In my experience, the volume and complexity of these data sets, even for the largest banks in the world, does not require new technology. Sure, new big data technology could be used to store, extract and process this data, but why implement a costly new system when conventional technology could be used as a cheaper and less risky solution?

One reason why big data solutions may seem appealing is that many institutions simply do not have effective strategies in place to properly manage their existing data, and in response believe the only solution is new technology. As a counterpoint to that idea, I work with one of the financial world’s most sophisticated analytics groups, and they make tremendous use of their data to understand customers, the marketing effectiveness, the profitability and risk – all because they made a significant investment in conventional technologies. As a point of comparison, the group I am referring to stores and exploits tenfold more data than similarly sized competitors. As this group demonstrates, there is no need for big data technology to gain these insights; traditional tools do work, and can be used extremely well with the right strategy in place. As outliers, there are some niche domains in financial services where big data technology is more apt to be applicable such as fraud detection based on customer behavior and time-sensitive risk calculations in capital markets. Opportunities in these areas should be evaluated in the context of a solid business case.

This then begs the question: if structured data can be generally managed without the use of big data solutions, what about unstructured data? After all, organisations such as Google and Facebook are using big data technology to gain incredible insight from the massive amounts of unstructured data they receive every day. For banks who are high up on the data management maturity curve, there are emerging big data investment opportunities. Software firms like Attensity are delivering integrated analytics solutions that interpret public-domain social media data in the context of channel activity. The key question for banks considering this technology is whether it addresses an actual priority. For most banks, our hypothesis is that there will be lower hanging fruit elsewhere.

Simply put, while the concept has its place in many industries, the financial sector shouldn’t jump at the chance to be an early adopter of big data technology. With other industries testing the waters, financial services can reduce the risks associated with early adoption by allowing others to oversee its development and let the industry as a whole mature. At the same time, we are urging our clients to focus their efforts on developing an effective data management strategy and better leverage the proven, cost-effective tools they already have. Big data may have a transformative effect on the financial industry in the future, but right now for most banks, it’s just an unnecessary distraction.

Related content


Recorded Webinar: Best practice timestamping and clock synchronisation

Don’t miss this opportunity to view the recording of this recently held webinar. Timestamping and clock synchronisation have been embedded in the EU by Markets in Financial Instruments Directive II (MiFID II) and are also a requirement of the US SEC Consolidated Audit Trail (CAT). The webinar will discuss how well firms have realised the...


Alveo Integrates ULTUMUS Index and ETF Managed Data Service with Prime

Alveo and ULTUMUS, an exchange-traded fund (ETF) specialist, have partnered to bring together Alveo’s data mastering solution, Prime, and ULTUMUS’s global ETF and index managed data service. The partnership aims to enable Alveo customers to integrate index and ETF information more quickly, and allow ULTUMUS’s clients to enhance their data mastering and data integration capabilities....


RegTech Summit APAC Virtual

RegTech Summit APAC will explore the current regulatory environment in Asia Pacific, the impact of COVID on the RegTech industry and the extent to which the pandemic has acted a catalyst for RegTech adoption in financial markets.


Entity Data Management Handbook – Seventh Edition

Sourcing entity data and ensuring efficient and effective entity data management is a challenge for many financial institutions as volumes of data rise, more regulations require entity data in reporting, and the fight again financial crime is escalated by bad actors using increasingly sophisticated techniques to attack processes and systems. That said, based on best...