About a-team Marketing Services
The knowledge platform for the financial technology industry
The knowledge platform for the financial technology industry

A-Team Insight Blogs

Is Big Data Just a Big Distraction?

Subscribe to our newsletter

By Chris Ford, Capco
www.capco.com

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.

Subscribe to our newsletter

Related content

WEBINAR

Recorded Webinar: Streamlining trading and investment processes with data standards and identifiers

Financial institutions are integrating not only greater volumes of data for use across their organisation but also more varieties of data. As well, that data is being applied to more use cases than ever before, especially regulatory compliance and ESG integration. Due to this increased complexity of institutions’ data needs, however, information often arrives into...

BLOG

LemonEdge Seeks to Fill Tech Gap in Private Fund Accounting

As private markets and assets grow in importance to institutional investors, so are the challenges they face; not least of all their data processes. A report by Dynamo Software in February found that the biggest challenges faced by accounting professionals in private equity, venture and hedge funds were tech and data-related; manual data entry and...

EVENT

AI in Data Management Summit New York City

Following the success of the 15th Data Management Summit NYC, A-Team Group are excited to announce our new event: AI in Data Management Summit NYC!

GUIDE

Hosted/Managed Services

The on-site data management model is broken. Resources have been squeezed to breaking point. The industry needs a new operating model if it is truly to do more with less. Can hosted/managed services provide the answer? Can the marketplace really create and maintain a utility-based approach to reference data management? And if so, how can...