The cost of failure to adapt with modern technology can go as big as US$6.2 billion. No less than the fortress-like JP Morgan investment bank could attest to this.
When the JP Morgan scandal started in 2012, the blame was immediately placed on its French trader, Bruno Iksil, otherwise referred to as the “London Whale.” He got his nickname based on the size of his positions which basically distorted the markets due to his large bets on derivatives.
JP Morgan immediately admitted to losing $2 billion but after intensive investigation and the need to settle lawsuits filed against the bank, the amount tripled and may even go higher, according to Bloomberg. What is even more surprising after the results of the investigation came up is the fact that the huge loss was mainly due to an Excel error, a rookie analyst mistake.
This spreadsheet error which caused billions of dollars in losses involves the Value at Risk (VaR) model used in hedging strategy. It is operated manually using Excel spreadsheets. It is processed using copy-pasting of data and formulas from one to the other spreadsheet. The procedure should have automated portions but never really happened, as a report showed.
Unfortunately, the use of spreadsheet among banks is surprisingly still a common practice today, where vital statistical calculations are executed utilising an intricate series of Excel spreadsheets. These are linked together by numerous (up to thousands) cell-reference formulas that are run by manually entered series of input parameters. Any analyst familiar with this procedure is aware of the risks involved, including its exposure to errors when copy-pasting data. This makes the entire process very fragile.
Fortunately, the advent of modern analytics allows banks and other sectors to do away with Excel spreadsheets and consider adapting with the comforts of modern technology. Today, innovative approaches to web-based data cleaning are readily available and affordable. Trifacta is a leading big data company that pioneers in data wrangling technology, which allows automated cleaning, preparation, analysis, enrichment and integration of big data. There is no need to manually operate the system on a daily basis.
The use of Excel spreadsheets is no longer feasible in this modern era. The huge amount of disparate data being processed daily can hamper business performance if companies will continue relying on Excel. Spreadsheets are manually operated, not scalable and are difficult to use when collaborating or integrating big data.
Companies should learn from the mistakes on JP Morgan. It would be a wise move for any business to start evolving with the times and invest on modern analytics. These are now available in the form of software and can be accessed and operated by data analysts. There is no need to hire highly-paid expert big data analysts to run the system.
I will be writing about another banking issue that can be mitigated by big data analytics in my next article. I will showcase how big data identified the causes of the credit card fraud that creates fear among Visa card users.