Data Science in Finance

sIn our first blog, we introduced the buzz word - Big Data and briefly mentioned about how banks and insurance companies are making use of Big data or Data Science. In this blog we will mention how some of these organizations are leveraging the capabilities of Big Data. To begin with, I would say that the financial sector can be broadly classified into the following categories: banks, investment funds, insurance companies and real estate or Asset Management(Investopedia.com, 2007). Traditionally, these businesses can serve either a retail customer or a commercial customer or both.

As in the financial sector, which operates in terms of transactions, covering risk is the most important aspect of their business. Data can help these companies in minimizing the risk. It is interesting to see some of the top aspects in which Big Data has changed the way finance industry operates. Although they all are linked up to some extent, I will still categorize them separately to mark some dist

          

1. Transparency : Historically, the big financial transactions were based on relationships. People used to do business with the people they trusted. As the data about financial market was made public, investors were able to identify the potential risks of working with particular organizations. As more and more data is added to the arsenal, it becomes difficult for the fraudulent companies to cover up. It also leads to sound investment decisions and these can be made based on company performance.
2. Risk Analysis : Lenders can now approve credit applications on the spot. This is enabled by big data. Banks are able to create a risk profile of a customer by checking customer credit reports, spending habits, credit card repayment history. Another example would be to prevent fraudulent transactions on credit cards. Based on a user past transactions, banks can identify if the on coming transaction may be a fraudulent transaction and additional security can be added for such transactions.
3. Fin-tech or Algorithm based trading : Real time stock market information, news feeds, and social media generate a lot of unstructured data. This data can be fed to a machine learning algorithm to predict the market movement. This helps investors in making safer investments while trading in the stock market. People are writing algorithmic codes to trade automatically as the market moves. The thinking part is done by the algorithms. One of the articles from the wall street journal published recently states that “computerized trading strategies, or algorithms, are remaking the $12.7 trillion Treasury market, emulating earlier sea changes in stock and currency trading” (Burne, 2015).
4. Consumer Analytics : Financial companies who had been keeping their data in silos, were for long worried about the challenges of integrating the data and process this humungous amount of data and the costs associated with it. With the onset of Big data technologies, they now are able to leverage the benefits of insights provided by this data and use it to know their customers much better. This not only helps in keeping their customers loyal but also helps in tapping on the customers of their competitors if they are missing on this advantage.

Some of the challenges that these companies are trying to address are mentioned below:

·       Integrating large volumes of structured data with unstructured market data.

·       Real time analysis of counterparty exposures and unstructured markets to evaluate market risk.

·       Dynamic economic environments, ongoing regulatory changes declining economies and upcoming trends require improvement to IT systems which require further investments.

Big Data technologies when used, can help address these challenges and provide value to the companies. The table below summarises how can the financial services industry use big data

Fig 1 How companies in Finance Sector can use big data

Bibliography

Investopedia.com (2007) ‘Financial sector’, in Available at: http://www.investopedia.com/terms/f/financial_sector.asp?layout=infini&v=5C&adtest=5C&ato=3000 (Accessed: 29 May 2016).In-line Citation:(Investopedia.com, 2007)

Razin, E. (2015) Big buzz about big data: 5 ways big data is changing finance. Available at: http://www.forbes.com/sites/elyrazin/2015/12/03/big-buzz-about-big-data-5-ways-big-data-is-changing-finance/3/#68cf1435a482 (Accessed: 29 May 2016).

In-line Citation:(Razin, 2015)

Burne, K. (2015) The new bond market: Algorithms trump humans. Available at: http://www.wsj.com/articles/the-new-bond-market-algorithms-trump-humans-1443051304 (Accessed: 29 May 2016).

In-line Citation:(Burne, 2015)

Bibliography: www.pwc.com (no date) How can financial services sector unlock the value? Available at: https://www.pwc.com/us/en/financial-services/publications/viewpoints/assets/pwc-unlocking-big-data-value.pdf (Accessed: 29 May 2016). In-line Citation: (no date)