Smarter 'Stock AI'... Koscom's 'Robo-Advisor Test Center' in the Spotlight

The stock robo-advisor market utilizing artificial intelligence (AI) is rapidly growing. Alongside this, the role of Koscom in verifying 'smarter' robo-advisors is also gaining attention.

According to Koscom Robo-Advisor Testbed Center on the 28th, as of January, the total assets under management by robo-advisors amounted to 1.825 trillion KRW. Compared to just 11.6 billion KRW in August 2017, this represents a growth of over 150 times in about five and a half years.

The expansion of the robo-advisor market was enabled by effective verification through Koscom's testbed. At the Koscom testbed, inspections are conducted on items such as ▲diversified investment ▲investor profile analysis ▲hacking prevention to ensure that robo-advisors properly perform investment advisory and discretionary management functions.

KOSCOM Headquarters, Yeouido, Seoul.

The robo-advisor testbed operated by Koscom was launched in 2016 and is now in its eighth year. At that time, a task force (TF) team was formed with financial authorities, academia, and industry, and it is currently operated mainly by private experts. Koscom, which has expertise in IT technology and capital market infrastructure, serves as the secretariat and supports related tasks.

So far, a total of 352 robo-advisor algorithms from 118 companies, including individual participants, have been reviewed. The 20th regular review is currently underway. Among the 310 algorithms that have completed the review, 217 passed. On average, 3 out of 10 robo-advisors either voluntarily withdrew or failed during the review process.

Koscom plans to continuously upgrade the testbed in response to the increasingly high demands of financial consumers. They will develop and disclose additional performance indicators for robo-advisors and strengthen the monitoring of algorithms currently disclosed.

Yang Hoon-seok, team leader of the Koscom Robo-Advisor Testbed Secretariat, said, "We will continue to support financial consumers in making the best choices by developing various performance indicators and enhancing algorithm monitoring."