There is an interesting trend developing in financial and investment markets, where big data is being used to enhance and improve the customer experience and the bottom line. It’s disrupting the traditional operations of the financial industry and providing opportunities for new entrants into the market sector. It is also creating new job opportunities for data scientists and analysts to add real value to organisations.
Most financial institutions have vast amounts of data on their customers as well as market history and future trends. Yet while this data has been collected and stored for some time, it was seldom mined or analysed for ways to make it more useful. This is all changing.
Predictive analytics is just one area in which technology is adding value to customers where existing customer data is used to understand trends and predict future customer behavior. This can provide insights on what customers are most likely to purchase based on historical data. This information is enabling companies to tailor their products and services more precisely to suit customer’s specific needs. Given how customers are increasingly looking for personalisation, for those businesses getting this right its proving to be quite the competitive edge.
For jobseekers this presents a great opportunity, for while AI is expert in running analyses, data scientists are needed to formulate the analytics criteria and interpret the data in a way that is meaningful to customers. According to Deloitte, the structure of analytics is changing. Whereas before it was primarily reporting with just minor emphasis on algorithmic, descriptive and predictive analytics, there is now a far greater interest in these three types of analytics, primarily because of the change to a more customer centric approach to business. Jobseekers with either the skills or interest in any of these fields can make a valuable contribution to any organisation they choose to work for.
Wealth analytics in action
Despite having different approaches to building wealth, investors typically have one need in common – ensuring they get the best possible returns on their profile. Some investors are typically cautious while others are less risk adverse. With detailed analytics, financial institutions can track customer’s individual investment behaviour based on their buying habits and financial decisions. They can then create algorithms that identify future investment opportunities that may be of interest to the customer thereby enhancing the customer experience and providing them with a tailored investment portfolio.
A similar approach can be used for customer retention, using analytics to provide customers with feedback on the performance of their investments and presenting new opportunities to fine tune and improve returns. A long term approach may include helping customers set up retirement plans or savings funds. In terms of attracting new clients analytics can be used to identify customer needs in different life stages, ie: college funding, home loans or savings.
More importantly though, data can play a crucial role in fraud prevention through predictive analytics. By identifying characteristics of fraudulent transactions, actions can be flagged and put on hold rather than processed. Data scientists and analysts can be at the forefront of helping prevent and reduce fraud as well as enhancing the customer experience. No matter what your particular interest, one thing’s for sure – it’s an exciting time to be working in the FinTech industry.
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