The advantages of Big Data are being seen across all industries, and nowhere more so than in the financial sector. Banks need information. They need it in real time, and they need it to be as accurate as possible. Financial institutions are expanding their use of data analytics in key areas, such as customer retention, increasing share of wallet and risk management. These are all vital in an age in which mistrust in the sector is at an all time high, and governments are imposing regulations and rules around competition that have created a more challenging environment than ever to operate in.
The tools for processing this data are improving rapidly, with new technology being released all the time. Unfortunately, finding people with the necessary skills to then analyze this data is becoming increasingly difficult.
This is a situation being experienced across the business world. A report conducted by McKinsey & Company predicts that there would be a shortfall of between 140,000 and 190,000 people with analytical expertise by 2018 in the US alone. IDC has projected similar numbers, estimating that 181,000 will be needed by 2018. According to the Harvard Business Review, ‘data scientist’ is the 21st century’s sexiest job. Salaries are high, thanks in part to the skills gap itself, yet it is still not attracting enough to fill the roles needed by companies.
One of the main issues is in fact the technology itself. Big Data is a highly innovative area, and the software is constantly evolving. It takes time for anyone to grasp the finer details of it’s operation.
The necessary skills needed for analytics in the finance sector are also particularly complex. Thomas Statnick, Global Head, Treasury and Trade Solutions Technology at Citibank, says that: ‘It is difficult to recruit people right out of school for these positions. For big data, it is a hybrid role...business and technology. You have to train them or recruit them from business positions. It takes business, engineering and computer science skills. it is an interesting hybrid of a position, but it is really hard to find those people.’
To train people with business experience, either from college or coming from previous employment, in data science costs money. However, many have reported a lack of returns from Big Data, with business leaders expressing disappointment in the insights that are being found. KPMG has recently released a global survey of 830 senior business leaders that found that, while 97% use data and analytics in their organizations, just 19% say they are very satisfied with the insights the analytics deliver. This is putting some off investing in the area to the degree that is necessary to fully exploit it.
The solution for filling the skills gap starts at university, with banks increasing collaboration with educational establishments to ensure that graduates are coming out with the right skills in place. Bank of America, for one, is working with the University of Virginia Darden School of Business, the McIntire School of Commerce, and the University of Michigan Ross School of Business on programmes that ensures it has a strong pipeline of IT leaders, helping to train them in different IT competencies at the bank, such as risk management, architecture and IT-business integration.
It is not simply a case of financial companies struggling to recruit the right talent either, they are also finding it difficult to retain it. According to Dr.Usama Fayyad, Chairman of Oasis500, a start-up accelerator in the Middle East, and former CDO at Yahoo!: ‘Finding big data talent is difficult, retaining it is nearly impossible. And the role of a data scientist is impossible to fill, especially outside of the US.’ Investment in staff is key, and banks have to be patient with seeing returns. Training is a necessary expense if the insights being garnered are to be leveraged effectively, and a culture in which data scientists feel valued is important to create.