In the complex and competitive world of financial services having speed and visibility is key to staying ahead of the competition. That’s the key message Jung Seok Kang, CEO of South Korean-based fintech AIZEN hopes to get across when he meets with potential clients around Asia. Creating AIZEN back in 2016 after several years at Citi, Kang saw firsthand how banks struggled to manage and capitalize on their internal datasets and saw that there needed to be change.

 

Using a complex modelling process Kang eventually established AIZEN’s ABACUS, a machine learning automation platform specialized in helping those in banking, payments, insurance and asset management. According to Kang, his ABACUS platform can do a number of actions such as guidance on loan underwriting and retail payment fraud detection; essentially helping businesses make informed decisions.

 

“Artificial intelligence is one of the key technologies that can change the banking industry. This is a problem that many in the financial industry don’t realize. If you look internally within the big banks, the funding and lending processes are very complex,” shares Kang.

 

Though determined in his desire to help incumbent financial institutions, Kang admits that he had to overcome several challenges in getting his message across to the right organizations. “One of the hardest things before was that most banks were not able to provide adequate products in a timely manner especially where lending products are mostly required in the data-rich industry,” recalls Kang.

 

The turnaround for Kang and AIZEN came soon though with the global interest and drive to improve digital financial services. Specifically, for Kang it meant increased conversations and partnership potential with various firms from insurance companies to banks. South Korean Woori Bank, a key client for AIZEN, for instance uses the fintech to help monitor, predict and control the bank’s loan portfolio via a single platform.

 

“We are providing automated banking operating systems which means that we don’t only provide one score or predictive model but a holistic view for the bank. We are looking at what products they should be offering, and what sort of interest they need to charge for it,” Kang says. “We convert existing data into pre-payment risk models and are also incorporating the usability of funding, looking at who is most likely to buy certain products.”

 

Other solutions created by AIZEN for financial firms include a SME default risk prediction model for commercial loans and a credit card payment fraud detection system.

 

When looking at this year, Kang and his team are beaming with excitement as they look to craft solutions for a number of clients in South Korea and elsewhere. We feel that the market is changing very rapidly as digital banking is taking hold in places outside of South Korea such as in Singapore, Hong Kong, and all Southeast Asian countries,” highlights Kang.