Once a potential use for Big Data and analytics is identified, Citigroup carefully assesses that opportunity in terms of benefits and cost. As Michael Simone, managing director of data platform engineering at Citigroup, told me, “There are a variety of factors that are taken into consideration, which is why not all of them make it through the gate. Sometimes after going through all of the paper exercises of understanding it, we may realise that there are other ways to accomplish this and moving to Big Data just because it is Big Data may not be the right fit.”
One area of Citi’s operations where Big Data analytics has been implemented successfully is in customer retention and acquisition. This involves analysing data and targeting promotional spending using machine learning algorithms. Another is to scan transactional records to spot anomalies, which in the case of Citi’s customers, can mean incorrect, unusual or fraudulent charges. The costs resulting from these anomalies are far easier to manage if the problem is spotted quickly – or even before it happens, through predictive modelling.
The technical details
As the foundation for its Big Data strategy, Citi has invested in its own integrated Big Data platform architecture, which Simone refers to as its Virtual Enterprise Data Lake. The platform is primarily built on Hadoop, and datasets are sourced from different applications that ingest multi-structured data streams from transactional stores, customer feedback, and business process data sources.
As Simone told me, “Our core platform is predicated on the value of open source with integration of very capable pure play Big Data solutions. As a result, we have a set of open source vendors with whom we work closely.” These vendors are picked for their ability to demonstrate “deep integration” rather than “bolt-on” capability with the technology they provide, but also for their ability to adapt to Citi’s “rigorous requirements”.
Ideas and insights you can steal
What really impresses me about Citi’s approach to Big Data is their careful assessment of the benefits and opportunities of using data. Many companies fall into the trap of “data for data’s sake”, which may lead to some cool insights, but rarely results in meaningful improvements. In this way, taking a strategic approach is vital if you are to get the most out of Big Data.
You can read more about how companies are using Big Data to drive success in Big Data in Practice: How 45 Successful Companies Used Big Data Analytics to Deliver Extraordinary Results.
Bernard Marr is a bestselling author, keynote speaker, and advisor to companies and governments. He has worked with and advised many of the world's best-known organisations. LinkedIn has recently ranked Bernard as one of the top 10 Business Influencers in the world (in fact, No 5 - just behind Bill Gates and Richard Branson). He writes on the topics of intelligent business performance for various publications including Forbes, HuffPost, and LinkedIn Pulse. His blogs and SlideShare presentation have millions of readers.