BANKING
BI and security
Adam Lieberman , Head of Artificial Intelligence and Machine Learning , Finastra , says , “ When we look at leveraging BI tools , or building our own , we like to observe three security principles : process level security , data level security , and system level security . Process level security is an overall set of procedures to ensure our data is safe ; data level security determines what data in each data source a user can see ; and system level security concerns access , permissions , and management of users for the application . “ Data security is a top priority , especially within financial services . We often have sensitive information and attributes that we need to keep safe , and the top BI tools and best principles allow us to ensure this data is safeguarded .”
Lieberman adds , “ I also see it incorporating more tools to analyze unstructured data such as service inquiries , comments , reviews , and alternate text data , especially as we are collecting massive amounts of this data in financial services .”
Such developments all have one goal in mind - that is , to learn the habits of customers in the most up-to-date and accurate way possible . Gaurav Chawla , sales engineer at InterSystems says trends in BI , such as AI , machine learning and analytics , all have immense potential . But , they cannot thrive without data that is of high quality and which is fully integrated across all the available sources . “ Reliable , timely , properly integrated data is a prerequisite for meaningful BI . If banks or fintechs are to optimise ‘ Know Your Customer ’ rules , for example , they need all the data to be integrated ,” he points out .
Security and BI Chawla also says that BI also encompasses cyber security and network fortification . Incidences of major data breaches such as the SolarWinds hack at Microsoft have shocked the IT industry and revealed security as a critical consideration .
“ Network challenges are common to many industries , and banking is no exception . The notable security issue for banks is problems with data . If the data is untrustworthy or incomplete , the outcomes are not secure . Banks need , for example , to counter fraudulent applications for CBILS and BBLS loans , where in some instances , credit histories are hacked and other details were falsified or missing , such as financials or County Court Judgments .”
Chawla continues , “ If back-end systems are integrated they flag up that a company has only existed for a week or that the data is incomplete , then such fraudulent applications could have been spotted easily . Lack of integration of back end systems left banks exposed as and a portion of the loans went out to the wrong people . The resultant PR damage then impacted all future recovery policies .”
“ As an avid developer , I believe the best solution is the one that your team custom builds ”