Financial Analytics: How Data is Delivering Value

A growing number of businesses are implementing financial analytics into their businesses with a long term objective in mind such as predictive sales analytics, risk management analysis, cash flow analytics; but, like any developing technology, analytics comes with a fair share of challenges.

With the advent of globalization, companies worldwide have begun their tenuous journey towards expansion by exploiting opportunities for growth in terms of trade, obtaining new consumers, and increasing revenue. But, amongst the midst of all this activity, finance is at the heart, determining and dictating the scope and stability of their reach. Finance in today’s world is much more complex, data-driven, and widely observed due to its importance. Financial Analytics is enabling companies to employ technological tools to process this data by understanding the past and present performance to forecast investments and make informed decisions for risk management analysis, predictive sales analytics, cash flow analytics, and others.

A growing number of businesses are implementing financial analytics into their businesses with a long term objective in mind such as predictive sales analytics, risk management analysis, cash flow analytics; but, like any developing technology, analytics comes with a fair share of challenges. Companies who were among the first to implement analytics have found difficulties such as lack of proper management and communication between divisions; deploying tools in an ill-fitting organization structure; and finding the right specialists for the job. Finance companies tend to be secretive when it comes to sharing information, often storing data in silos and avoiding platforms sensitive to hackers. But, financial analytics requires all the data to be stored on a single platform, such as cloud, to convert the raw information into structured data for assisting and analyzing the insights for informed decision making based on risk management analysis, predictive sales analytics, cash flow analytics and others.

The world’s top financial cities are closely monitoring and encouraging companies to implement AI and data analytics in financial institutions to perform predictive sales analytics, risk management analysis, cash flow analytics and others. In 2015, Singapore launched a five-year Financial Sector Technology & Innovation (FSTI) scheme, a S$225m project, to promote an eco-system for FinTech innovation. The government is partially funding the program, which will further enable the companies to leverage data analytics and artificial intelligence to gain insights for predictive sales analytics, risk management analysis, cash flow analytics and others. Also, as a part of the scheme, the financial institutions need to educate their employees and provide necessary training modules for data analytics roles.

The financial sector is due for a technological overhaul. The catch up process is resulting in a compounding effect on financial institutions in the form of increasing online thefts and frauds, difficulties in complying with tighter regulations and meeting demands for greater transparency. However, the advancements in AI and machine learning are enabling financial analytics to address some of these key issues. Financial analytics is helping CFOs and industry executives to view and analyze the hidden data with more ease and shape up business goals and strategies. Not only these, financial analytics is also improving their decision making.

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