How Singapore BANKS are Using Big Data
5 Ways Banks in Singapore are Using Big Data
With the help of machine learning, big data can help automate manual processes that are currently used for corporate and institutional client onboarding, such as client due diligence. It can also help speed up SME lending processes.
Data analytics aren’t only useful to analyse customer data, but also to streamline internal operations. For example in recruitment, significantly cutting the number of hours recruitment officers spend on the initial screening of applicants.
Responding to cyber incidents
With so much information being exchanged across the banking network, it is important for banks to secure not only the network but also its data centres. Big data can analyse threat patterns and identify any suspicious activities that could compromise a bank’s internal system.
Auditing bank branches and ATM network
Identifying the risks of a bank branch is tedious if not near impossible if done manually. Big data is used to identify any potential problems in any particular branch, which might require an audit. It can also help identify customer needs more accurately, using data such as customer flows.
Anti money laundering
Traditionally, bank processes for anti money laundering is reliant on a rule based approach. In other words, the system flags any transaction that violates a set of rules. A human will have to then manually sift through and review the transaction to identify any suspicious activity.
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