Global IT firm Aspire Systems has launched a customer intelligence framework for banks and financial institutions. The platform, called imagyn.ai, utilises artificial intelligence and machine learning to move account-centric legacy systems towards client-centric systems, a company statement said.
Low-quality data and poor segmentation of customers are some of the crucial problems faced by banks today. To help with customer interactions and framework channels, all important information such as transactions, account history and customer profiles will be integrated into one version for each banking client, said the statement.
“The greatest challenge banks face today is the lack of clean, consistent and precise data. The amount of data banks derive from their customers is erroneous but deriving the right insights from them has always been a trial,” said Anand Subramaniam, head of the artificial intelligence practice at Aspire Systems.
The statement said that imagyn.ai helps banks consolidate all data into a singular silo, which can help the bank provide customised products based on client preferences. Adding to this, Srini Peyyalamitta, head of banking and financial services, Aspire Systems, said that the high rates of customer attrition were pushing banks towards a customer-centric approach for better trust and loyalty.
“This is definitely a milestone for Aspire Systems in the AI/ML space,” said Peyyalamitta.
Tech companies are increasingly deploying ML and AI in the BFSI domain, with mid-sized companies and enterprises alike jumping on the bandwagon.
TechCircle had earlier showcased that AI chatbots can help banks save billions of dollars in the coming decade. Juniper Research said that chatbots can result in annual cost savings worth $8 billion by 2022 while tech research firm Gartner predicted that bots will handle close to 85% of all customer service interactions as early as 2020.
In an interview with TechCircle this January, Yes Bank’s chief information officer, Anup Purohit, spoke about how AI will continue to shake up banking in 2019 and beyond. “Machine learning, more precisely deep learning, has already transformed areas such as credit risk assessment, money laundering and fraud detection and will become more comprehensive and wide-ranging in the years to follow,” he had said.