The digital twin, a digital replica of the real thing, is a versatile tool for financial decision-makers on the never-ending hunt for new technologies that will improve the customer experience. From reducing costs and designing bank branches to tightening cybersecurity, the dynamic digital twin is a win for bank strategists and planners.

As every tech firm knows, data is its most valuable asset – but worthless unless used efficiently and continually learned from. Fintechs must grapple with so many disparate seams of data in order to function smoothly and it’s not easy. Raw data is ugly, it’s complicated and it’s scattered across many file sources, languages and formats. What’s more, big data is getting bigger and more complicated every day.

Data is the new oil, and there’s no shortage of it. Rendering it useful while respecting privacy rights is the main challenge. That’s where synthetic data, created via artificial intelligence and machine learning to simulate real-world data, comes in. It is proving invaluable to financial firms seeking to optimize the vast power of data.

Deciphering coding is a stumbling block for businesses striving to stay relevant and maximize technologies. Fortunately, low-code and no-code solutions make the process of creating websites or applications easier and cheaper. How can banks cut through tedious coding and achieve optimal results with help from low-code/no-code platforms?