AIZEN Global: Artificial Intelligence for better Banking Practices – AIZEN


AIZEN Global: Artificial Intelligence for better Banking Practices

“The firm’s ABACUS AI platform specializes in retail banking and insurance, helping them automate key business value chains”

The banking industry has always been seeking new technology. Banks now start to realize the importance of Artificial Intelligence (AI) to incorporate into their business processes. Especially in Retail Banking sector, there are huge opportunities to improve the efficiency of the process, by combining banks’ data, business-customized algorithms, and by improving processing power.

Due to the benefits from AI technology, strong demands are expected across the industry, at the same time, shortage of supply is also expected for the foreseeable future. Banks are trying either to hire AI expertise or to train Bankers to learn AI. However, finding an expert in both areas takes substantial resources. AIZEN Global based in Korea uses AI and expert financial knowledge to create predictive models in key functionalities in real-time, applied for U$400B size of financial institutions with its ABACUS platform.

“In the retail banking sector, huge opportunities can be created if data scattered around the organization is gathered in one platform.”says Jung Seok Kang, CEO of AIZEN Global. “Like key autonomous vehicle technology is changing the automobile industry, our vision is to provide key autonomous technology in Finance by applying AI to core business decision-making process.” continues Mr.Kang. Currently AIZEN’s AI business service is offered as an on-premises basis, and is actively working to transform it into a Cloud platform.

The firm’s ABACUS AI platform specializes in retail banking and insurance, helping them automate and improve efficiency in key business value chains. Today, most banks continue to use legacy systems that are often off-limits to providers. ABACUS, however, allows for smooth implementation into the bank’s legacy systems. The platform uses an API structure that helps the banks to interact with its database, which is kept on-premises so that the legacy systems can just hook into it to upload the data. ABACUS then extracts the variables from the data to create derivative parameters that are based on the existing parameters set by the bank.

On top of private sector, AIZEN provides combined predictive models for the Korean government’s guaranteed loan program. The government spends around $400 million per annum to support the low-income profile through traditional banking system. From the bank’s perspective, even if the loan defaults, the government will provide funds to them, which can prove to be costly for the latter. AIZEN creates sophisticated predictive models for the program which helps the government in either reducing its expenditure or utilizing the same amount of money for expanding a beneficial loan program which can help the people. AIZEN sees that almost all countries face the same issue.

AIZEN is ahead of the competition in terms of technology, experience and its talent eco-system. It has implemented its AI system into one of Korea’s largest banks, with $400 billion in assets. By applying AI predictive models in their core value chain using AIZEN ABACUS, to the value chain, partner bank cut its data analysis time, improved acceptance rate and created new business process using AI predictive models.

AIZEN has a lot of potential to diversify its business applications, functions, and portfolios. The firm is currently focusing on the personal lending space which has been valued at $5 billion, and as it is working on standardizing its products, it will increase the ease of expansion into other products like mortgages, small and medium-sized enterprise loans and car loans.

The firm is moving to Asset Management and Digitized Bank using same AI technology. AIZEN is either creating or merging small-sized banks and converting them into digitized banks. The organization is also improving its algorithm to have it standardized to scale up, which will also allow for functionally expanding its service models.

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