For many years, technology aimed at financial institutions has evolved at a measured pace. These organizations simply moved their operations and transactional services progressively from the manual to the Internet. However, as a result of the great financial crisis that began in 2008 , a new wave of disruptive entities emerged that embraced the concept of ‘customer-facing’ and began to be known as Fintech.

The DNA of the financial industry changed forever. These startups, which based their modus operandi on the data, began to offer the customer new formulas for investing and making payments, blowing all the alarms within the traditional banking. However, these agile and attractive startups, now known to all as Fintech, do not have decades of valuable data stored, as is the case with traditional institutions.

Through analytics, these organizations will be able to face their next evolutionary leap. Their competitive advantage will take shape when they are able to draw conclusions from new sources made up of vast volumes of historical data. It is true that Fintech entities may have received all the media attention and a good part of the investment pie, but, thanks to analytics, especially to predictive analytics, banks will be able to better serve the financial health of their clients. customers, providing them with an exceptional service, which will allow them to win this match.

Financial institutions are starting to bet on predictive analytics

Predictive analytics, one more step

Financial institutions are starting to rely on predictive analytics, as it allows them to forecast future events and results more reliably, from the needs and behaviors of their customers and prospects, to any type of financial or fraudulent risk. These organizations capture and store huge amounts of data. Data relating to customer applications, transactions, bank accounts, demographic information, promotions and other business tools that contain a vital intelligence that, on many occasions, remains hidden. Predictive analytics combines automated visualization and data analysis technologies that help financial companies prepare for the future by learning from the past. Thanks to predictive analytics,

Increase customer acquisition and retention: Better customerprofiling and segmentation will enable these companies to obtain a wide range of customer information, such as loyalty level, cancellation rate, product utilization, or total value of their permanence. The appropriate effort can be employed to acquire and retain the most valuable customers in order to ensure continued growth.

Feed Marketing Success: With a better understanding of the market and customer needs, financial institutions can deploy better targeted promotions and more efficient cross-selling and up-selling campaigns, as well as more accurately predict their impact.

Combating fraud: The ability to detect or anticipate illegal or suspicious activities and transactions – such as identity theft or money laundering – will enable these organizations to significantly reduce fraud. Since scammers constantly review their techniques, banks have no choice but to employ automated methods of data discovery and predictive analytics.

Mitigate risk: These agencies can dramatically reduce risk if they figure out how to balance their investments and ensure price hedges more appropriately. In addition, they will be able to predict their profitability more accurately, prevent risk with regard to loans and credit applicants, and better understand debtors’ behavior to save and capitalize efforts.