If one looks up the general fintech statistics, they’ll be surprised by the figures. The financial services sector is predicted to grow by 25% annually, hitting $310 billion by 2022. Although the pandemic has been a heavy blow for hundreds of industries, financial institutions managed to ride this wave out by broad and lightspeed adoption of innovation, among which predictive analysis occupies a special place. But how exactly predictive analytics in financial services can help to improve the agility of the industry?
A Few Words About Predictive Analytics
In the century of big data, it’s humanly impossible to perform business analysis, calculate risks and create prediction models manually. Since the financial industry is considered the most data-intensive sector in the global economy, predictive analytics is one of the most vital technologies data science can offer to manage and thoughtfully make use of those terabytes of precious customer data. The predictive analysis itself is a highly complex technology based on specific machine learning models and algorithms that enable software to perform such crucial business analysis processes as risk management, customer data analytics, strategic planning, and many more.
Predictive Analytics for Financial Services
Finance is the field where accurate predictions save billions of dollars and where a single miscalculation can lead to a disaster. Since the industry is getting more and more versatile, the application of predictive analysis is not limited to strategic planning only.
Any sector that deals with providing customer service values personal client data most of all. Needless to say, the information that financial institutions get from their clients is the top priority, being in direct correlation with its image and reputation. Thus a single fraud will inevitably lead to the financial and public “death” of an organization. To avoid such consequences, predictive software can help detect fraudulent actions and suspicious customer behavior at early stages, not giving a chance for cybercrime to happen.
Risk Management On Point
More than three-quarters of risks in the financial sector are connected with compiling a wrong or inaccurate client picture. Hundreds of factors have to be taken into account to calculate whether a person is reliable and creditworthy. InData Labs provides predictive analytics software in financial services that is not susceptible to the “human factor” and has access to almost any kind of digital data picturing a client’s actions both regarding financial institutions and social media. That volume of data collected is thoroughly analyzed via prediction models and the final verdict comes out deprived of any faults, saving considerable sums on future risks.
Before launching a product, any industry conducts deep customer research, based on data they get on a daily basis. When it comes to introducing new financial products, the data sets appear to be much larger, and client value systems turn out to be more complex. And again there’s no better tool than predictive analysis to be sure every new campaign hits the target.
Enhanced Customer Understanding
Any financial service institution just like any modern business in general is directly dependent on its customers. So the idea of accumulating millions of data bytes to keep in step with people your venture relies on sounds reasonable. New trends are born every day, people get attracted and become worried about matters that didn’t exist earlier. That’s why predictive analytics in financial services is essential to be able to sense the change in customers’ behavior and their values to keep making products and services relevant for the audience.
The Final Thought
The recent shift in the global service sector has taught us a valuable lesson of always having the B plan to rely on. With the true blossom of artificial intelligence, it is now simply inexcusable to ignore the capabilities of innovation and its undeniable power of positive change. The financial sector has already got rid of its former sluggishness and conservatism, making the way for cutting-edge technology for the sake of leveraging customer experience. Predictive analytics in financial services is now the core of the industry, successfully proving that only those who know how to work with data truly run the money world.