Machine Learning in Finance
Machine Learning will be the next best thing happening in Big data.
Businesses looking out for forefront help in preparing of data and carry out predictive analysis? Want to match up to the future challenges easily?
Machine Learning is one of the hottest topics which will be playing a very indispensable role in shaping the Big Data.
Due to availability of massive amount of data with the advanced and affordable computing power, Machine Learning has become more prominent in Finance these days. And Machine learning eventually will be the foremost thing for the new data revolution.
Why Machine Learning in Finance?
Machine learning is all about comprehending the massive amount of data and further how to carry out a specific task from it. Hence “Machine learning in finance” is like a “Cherry on a cake!” Since financing is all about intelligently handle all the huge and complex volumes and variety of information.
So putting hand in hand with Technology and Finance, let’s take a look at how Machine Learning is used in Finance –
The Algorithmic Trading:
The use of Algorithms for Trading is what we call Algorithmic Trading. This Trading makes use of immense formulas with a combination of mathematical models to make secured and proper decisions of buying and selling of finance securities on exchange. It also uses the High Frequency Trading in which one can make thousands of trades per second. Algorithmic Trading can also be used in different situations like order execution, trend setting strategies and arbitrage.
This is one of the best way of benefiting Finance with Machine Learning.
Underwriting is mainly found in Loans, Insurance and stock markets.
Well, let that be a risk of any venture, a loan, an investment or any other risk in the financial world, Underwriting is one of the mains function for carrying the disciplines of all sort.
Banks and insurance companies have an access to terabytes of consumer’s data which machine learning algorithms can be versed on, then these algorithms can perform the automated tasks like for eg looking for exceptions, matching data records, calculating likewise for a person’s feasibility for applying loan.
Machine learning algorithms can easily perform this task of underwriting tasks that took ample of hours for a human to do in past.
Preventing Money Laundering:
It is clear that many banks and financial institutes have a lot to do. Giant banks plan to incorporate machine learning technology into their infrastructure in a bid to combat money laundering. Also by utilizing software related to machine learning, banks can evaluate billions of data from internal and external sources. Machine learning has also allowed financial institutions to come over traditional business model to a more dynamic and predictive ones. Some bank are applying this technology to automate pre-compliance checks for traditional paper based trade finance transactions.
One of the main reasons for leveraging machine learning in finance is the massive problems of fraud when it comes to finance. Machine learning plays an ideal role for combating fraudulent financial transactions. Since machine learning system is having ability to scan through a vast data, also can detect unusual activities and track them easily.
To give an example: Identity Mind Global has patented a software driven machine learning called DNA, this software uses more than 50 data points to establish an individual’s identity.
When it comes to data security, it is one of the top priority of financial institutions and are mainly concerned about it. To meet and fight against the cyber-attacks taking place nowadays, one cannot rely upon the yesterday’s security software. It requires some advanced technology to face it. And this intelligent pattern analysis when combined with big data gives Machine learning technology a “go forward force” over the tradition ways used in financial institutions.