“In 2019, the Chartered Financial Analyst (CFA) examination is set to add questions on artificial intelligence, automated investment services and mining unconventional sources of data, “quoted leading news websites.
Does this indicate the beginning of a new trend? Quite possibly. From a “Nice to have” skill, Big data Analytics is fast becoming a “Must-have” skill in the kitty of finance professionals.
Businesses do not operate in a one-dimensional world today. There are multiple aspects to be considered and millions of comparisons to be made before arriving at any management decision. A decade back, the functions of finance managers were merely restricted to checking accounts, comparing the historical performance with the forecasted performance and analysing the Variance. While “How much variance” was accurately answered, “Why the variance” would still remain a question. Water-tight functioning pattern is so yesterday! Today, the results have to be interpreted against the backdrop of other findings such as customer preferences, markets, economic data and many more. Only then is the process of strategic decision making deemed complete. Big data analytics is one of the major enablers of multi-dimensional comparison of data.
Not only the finance and accounts vertical of companies, but the hard core financial services providers like banks, financial institutions and insurance providers are making increased use of Big data and Business Analytics in most of their operations. The below graph substantiates this fact.
According to IDC, mobility, cloud and big data analytics will form 30% of the total IT expenditures of global financial services in 2020 from 25% in 2015.
Reasons why financial services industry requires Big data:
- Increasing Revenue and profitability: Sifting through vast volumes of data helps businesses to focus on target products or potential earning areas. This way service providers such as banks, financial institutions, and insurance companies can design and launch their products for maximum revenue and profitability.
- Enhancing customer engagement and loyalty: Big data is a mine of information, which when analysed thoroughly can help to draw meaningful insights about customer behaviour. The loan repayment frequency, preferences towards certain loans or credit cards, spending and investment habits can help financial institutions or finance & accounting (F&A) verticals of companies to build better relations with customer and design processes for maximum customer satisfaction.
- Optimizing Assets and risk mitigation: Banks and financial institutions are always exposed to increased levels of risk due to loan defaults, risky assets or non-performing investments. Good use of data analytics can help banks to analyse the risk elements, interest rate cycle or assess the overall market conditions to make informed choices and make strategic steps to minimize the risk exposure.
Big Data Analytics application in new age financial processes
Real life cases of banking/finance verticals employing Big data Analytics:
Big Data Analytics in Financial services is here to stay
As the technology is rapidly moving into new frontiers, there is immense scope for applications of analytics. Most industry analysts opine that this has the power to bring about serious transformation in the business.
Staying abreast with the new developments is the need of the hour, and candidates who are contemplating of a career in finance should definitely consider business analytics to add a feather to their cap. Moreover, it won’t be long that every finance professional is expected to be adept at business analytics skills. It seems that the ‘big data’ boom has a lot in store through the finance industry too.