With the use of big data the finance services sector has been able to emerge as the winner being aided by it in different segments of it. Undoubtedly, big data now is playing a pivotal role in transmuting completely the entire financial services landscape for the better.
- The banks and other financial institutions are now finding it easier and they can make better decisions when it comes to trading and investing. This is because machine learning can do much more than the money market traders in a much more organized and precise manner.
- With the help of big data, machine learning and artificial intelligence the finance services providers can now look far beyond simply analyzing the buying and selling costs to define the best stock options.
- It can take different other factors into account such as the political, economic and social trends to make better decisions on the stock options given.
- It can even analyze the operation and business policies of different trending companies taking help of the social media.
- The most significant benefit of using big data is that it provides the analytical results based on the current matters helping the finance institutions to make better decisions in real time.
These are a few things that are impossible for a human especially when such large volumes of data is involved and required to be analyzed quickly and accurately to make sure not to fall behind or out of the competition. However, some amount of human intervention is required to accumulate and evaluate such large amount of data. Big data in this way is simplifying the role of a typical investor making it more of that of a data analyst.
Help in tax reform
Irrespective of the type of industry, where large amounts of data is involved and needs to be collected and recollected on a daily basis with detailed accuracy, big data analytics is the best tool to use. It is extremely useful and largely applicable in taxation where large amount of data is stored and worked upon every day.
Whether it is for business or for personal reasons, taxes are paid every year. There is a huge volume of financial data of the tax payers recorded from past years to this date and it needs to be analyzed which is a daunting task for any human.
- Software like big data can easily handle such pressure and access such large amount of data both from the tax filing records of the previous years as well as that of the current year. Here we have a good example of tax filing in Hong Kong.
- Another significant aspect is that it eliminates the chances of any human error in the analysis though it will not be able to eliminate the human errors made earlier.
A report prepared by the tax experts at Villanova University sheds some light on the new role that a tax professional will play in the years coming up with the use of big data analytics. It is said that the ‘Master of Taxation’ will need to collect, manage, and organize the data to find out the analytic potential with the help of the modern technology so that it is leveraged accurately, responsibly and most professionally.
Investigation and credit card fraud detection
There is a trail of data left behind when any financial transaction takes place. Therefore, it is required by the financial institutions and the banks need to assess and monitor the data to understand the behavior and buying habits of a customer.
- With the proper analytical results they can know their amounts if spending each month, the type of products they prefer to buy and even the shops that they prefer to buy it form.
- Big data and other machine learning analytics will also help them to know other important facts such as the lost or stolen information of a credit card or detect any unnatural transactions that are contradictory to the buying habits of a customer.
- In such cases it will alert the bank of that person instantly in order to put a hold on such transactions and prevent fraud.
Credit cards involve and produce a large amount of data that can be misused by anyone. Fraud in credit cards has become rampant as customer information and data can fall into wrong hands very quickly. With such useful software available, the law enforcement can also use it to prevent such illegal activity to stop a fraud before it even starts helping the finance industry by a great deal.
Helping in risk analysis
Financial institutions can now ensure privacy and security in a much better way using big data as that will help them in their risk assessment process. The predictive analytics of big data will help them to run far more accurate risk management much faster than a human.
It will take all the necessary aspects into consideration and help the financial institutions to make a sound and foolproof financial decision in much lesser time. Consider a simple bank loan. In here the analytical tool will take into account factors such as:
- The current economy
- The customer segmentation
- The capital for a business loan
- The financial health for a personal borrower and many more factors apart from the FICO score.
This will ensure proper loaning decision is made. Any financial decision made on the basis of intuition, guesswork and human instinct will typically be wrong and land both the lender as well as the borrower in hot water. The lender will need to consider proper collection methods to recover the amount loaned to the borrower and the debtors on the other hand will have to look up at Nationaldebtrelief.com and other sources to repay their debts and prevent filing for a Chapter 7 or a Chapter 13 bankruptcy.
Therefore, in the finance world, big data has made a huge impact helping the players and different finance machinery to make a decision not based on ‘what feels right’ but on ‘what is right.’ since machine learning is an unbiased big data technology has become the integral part of the financial services industry.