Finance is one of the most sought after and highly acclaimed sectors in the world of business. In the previous days, a lot of manual effort and labour used to go for finance management, and the process was extremely time-consuming as well. But, now, with the help of data science, it has become easier to analyse financial data more quickly and efficiently. It also helps finance companies make better and improved data-driven business decisions. The demand for skilled data science professionals is thus sky-high! It’s a great career option and comes with a lucrative salary and the prospect to upskill constantly. Many institutes are offering data science certifications and data science aspirants are going gaga over this programme.
Data science is a real problem-solver because nothing can go wrong when things work with proper information and accurate predictions. That’s why the finance sector could not keep away from seeking the aid of data science. Data science helps the finance sector by managing areas, such as risk analytics, fraud detection, algorithm trading, personalized financial services, and many others. Presently, the finance sector is so dependent upon data science, that the industry will practically collapse if they stop using data in their business.
There are many applications of data science in finance, but here, we are going to discuss four of them.
- Risk Analytics
Every organization, company, and industry has to face risk at some point or the other because no business is completely risk-free. That’s why data-driven risk analytics has become an integral part of the finance sector. It is crucial for companies to detect and analyse potential threats for devising any strategic business decision. This process is called risk analytics.
A company can also increase its security using risk analytics. Data remains in the centre of risk management and risk analysis because it examines the severity of damage and multiplies it with the frequency of loss. Data science professionals working in finance require to be proficient in mathematics, statistics and have problem-solving skills; because risk analysis and risk management are completely dependent upon these factors.
- Fraud Detection
Fraud detection is one of the chief concerns in the field of finance. With increased numbers of transactions, the chances of fraudulent activities have also grown significantly. But, owing to data science, it has now become easier for finance companies and organizations to keep track of scams and frauds in a more effective way by using proper analytical tools and big data analysis.
However, credit card fraud still remains one of the top scams in the finance sector. But, there has been a significant improvement in detecting credit card fraud because of the development of algorithms. Anomaly detection has also become way easier with higher and improved accuracy. Furthermore, the losses related to frauds and scams have also been reduced because of the real-time detection alert received by companies about the anomalies in financial transactions.
- Real-time Analytics
Long before, data used to be processed and analysed in big batches as there was no facility for real-time data analysis. It had a huge drawback because the data it worked with used to get much older by the time it got fully processed and analysed. For obvious reasons, the decisions devised on historical data was neither accurate nor helpful.
With time, different finance companies started to face problems as they were working without real-time data in order to gain valuable insights about present scenarios. But, now, it has become feasible to access data with a very less amount of delay owing to technological advancements and the development of dynamic data pipelines.
- Consumer Analytics
There are several financial organisations that place consumer personalisation at the forefront of their major operations. That’s why these companies seek the aid of data science because it helps them gain insight into real-time consumer behaviour with the help of real-time analytics in order to make improved business decisions. The finance sector uses data science extensively to reduce losses by eliminating below zero customers.
Get a Data Science Certification and Secure a Job in Finance
Data science is considered indispensable in the finance sector, and therefore there is a constant lookout for eligible data science candidates. So, if you are a person who is passionate about pursuing a successful career in data science, then you must look for institutions that offer data science certification, and the field of finance offers one of the best opportunities for capable data scientists.