Each year, the Deltec group of companies, of which is Deltec Bank & Trust, hosts in early March in Nassau (The Bahamas) a thought-provoking conference focusing on innovations and regrouping many ‘out-of-the-box’ thinkers. Amongst the subjects brought up this year was the future of banking in regard to AI and machine learning as growing constituents of our landscape.

Ever since the financial crisis of 2008, the relationship between public and banks deteriorated. With technology opening up new ways for financial management, more and more people are changing the way they manage their finance, more independently. However, though the banks are no longer the sole option, they are still here, and we have probably to count with the banking system as we know it for a while more. Now the question is how the banking industry is going to capitalize on disruption.

The Digital Revolution Is A Key To The Renewal Of The Banking Industry

With new communications, new technologies and new thought-process come new approaches to business. While it remains very small in regard to the global financial circulating mass, the spreading of digital currencies and peer-to-peer lending provides consumers with new ways to handle their finances. These also bring forth new funding avenues for SMEs and startups. For this reason, the banking institutions have to react to stay relevant, and harness as much as possible the advantage of the digital revolution.

Through digital services, advanced technologies, and big data, the banking industry can be made to re-imagine its role. It also enabled banks to enhance customer experience through the data shared by consumers, which provide them with profound insight. Traditional banks have a significant advantage over newcomers as they have a massive amount of financial data on millions of their customers.

Moreover, banks have the structure and the funds to exploit such data to improve their landscape. Big data is most often a massive but dormant asset that rests at the core of the company, waiting to be utilized. Additionally, more and more customers are adopting digital channels that allow banks to collect even more data about the financial behavior of customers as well as how they interact with banks.

Data Analytics’ Potential is Being Realized within the Banking Industry

Banking is reportedly leading the charge on the global revenues for big data and business analytics. It is not surprising as the applications of big data and analytics are seemingly endless in the banking and financial sector. One example of the application of big data in banking is in personalizing products and services in real time.

Mr. Jean Chalopin, Chairman of Deltec Bank www.DeltecBank.com said “Algorithms can use costumer’s data to personalize services and products based on their financial behavior. Besides personalization, data can help banks to gauge risk more accurately.” For instance, when offering a loan to customers, a lending company can utilize the customers’ financial data combined with the customers’ behavior regarding their respect of previous commitments, to determine if they should be entitled to a loan, calculate if and how they can pay the loan, making this lending safer both for the borrower and for the bank.

In that regards many predictive financial analytics technologies are been implemented by banks to analyze consumer’s credit history, credit or loan applications, and other relevant data. Additionally, the data can be used to improve customers’ satisfaction and help understand their needs.

From that point on, the most critical usage of data in banking is coming with the usage of machine learning and algorithms. Big data fed to machine learning algorithms can change the way we have been dealing with banks on a global scale, in an irreversible way.

Disclaimer: The author of this text, Robin Trehan, is Senior VP at Deltec International www.deltecbank.com.  The views, thoughts, and opinions expressed in this text are solely the views of the author, and not necessarily reflecting the views of Deltec International Group, its subsidiaries and/or employees.

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