FINSERV
“ Good quality data alone can significantly transform a firm ’ s AML process effectiveness by reducing data silos and providing a far clearer picture of the risk a potential customer presents ”
STEVE ELLIOT LEXISNEXIS RISK SOLUTIONS
Personalised approach Cramp is right . Over the past 12 months , everything from financial data aggregators and AI money managers to bespoke financial and insurance products are growing in popularity . A more personalised marketing approach to BI and data analytics is considered paramount .
However , instead of focusing on lead generation and more effortless follow-ups , a greater understanding of how data analytics can help banks develop a more personalised marketing campaign for their services , is required . With the help of ML and AI , big data can be segmented and used for determining what individual customers are looking for . But it ' s a long-term process .
Cramp says , “ We will see more personalisation in this field as fintechs in this area expand their customer base , create more partnerships and have access to more data that will help them shape new products .”
However , enabling all of this to happen will likely require more specialist data analytics tools and services – we ’ re likely to see a subsector of data analytics developing that caters entirely in the B2B field of enabling Open Banking innovation .
" A wider point to remember is that innovation trends evolve rapidly based on often temporary media or consumer interest . Data analytics is no different . Companies can reduce the chances of backing the ' wrong ' innovation if they develop a wider data skills base that can look beyond the immediate shiny new technology to understand what will actually work for their business .”
She adds , “ Similarly , in fields such as AI , we know that ethical concerns cannot be ignored . Incorporating ethical principles into how you innovate and the technology you adopt makes it much more sustainable ."