UOB Asset Management Ltd (UOBAM) and Value3 Advisory Pte. Ltd. (Value3)1, a financial technology (FinTech) start-up, today announced their collaboration to launch an artificial intelligence (AI)-enabled credit rating, research and reporting service in ASEAN. Through their collaboration, both organisations aim to help bond investors obtain credit insights in real time so as to make more effective investment decisions. UOBAM will also harness AI to enhance the market research and insights capabilities of its fixed income team.
UOBAM will combine its regional investment expertise with Value3’s machine learning and natural language processing technologies for thorough predictive analytics of ASEAN corporate bond issuers’ financial and non-financial data collected from diverse sources. UOBAM will also provide regional market and industry insights to help Value3 roll out in ASEAN its proprietary AlgoCRED AI-platform2, an online portal offering automated credit ratings, research and insights, for the region’s corporate bonds, including unrated bonds3. Automated quantitative and qualitative assessments will then be conducted to derive credit ratings, to create credit risk indicators with real-time alerts and to generate detailed credit rating reports.
For the first time, asset managers, financial advisory firms and institutional investors will be able to access independent credit ratings4 for unrated bonds in ASEAN by subscribing to the AlgoCRED AI-platform. This will enable the bond investors to evaluate the issuers’ creditworthiness and the issuances’ investment merits more accurately.
Mr Chong Jiun Yeh, Chief Investment Officer (Equities and Fixed Income) of UOBAM, said, “Across ASEAN, many corporate bond issuers may shy away from seeking ratings for their bond issuances due to the high fees that may be incurred or the time needed to obtain and to maintain the rating. As a result, investors including asset managers such as UOBAM have to rely on internal resources to determine the issuances’ investment merits. Greater visibility of credit ratings of bond issuers will also help benefit the corporate debt markets in the region.”
Mr Abhinav Mishra, Co-Founder and CEO of Value3, said, “Different financial institutions will typically rely on their own methodology to assign credit ratings to unrated bonds, leading to inconsistent ratings in the market. Through our collaboration with UOBAM, we will bring our proprietary and award-winning AlgoCRED Al-platform to ASEAN to address the demand for standardised credit rating services for unrated bonds. This will help corporate issuers, especially small- and medium-sized enterprises, to be more transparent in their disclosure and to attract more investors for their bonds.”
UOBAM will also work with Value3 to embed environmental, social and governance considerations into an exclusive credit rating model on the AlgoCRED AI-platform to facilitate its own responsible investing efforts.
Mr Chong said, “UOBAM has a strong track record5 in fixed income investing and is committed to using technology to deepen our capabilities. Through our collaboration with Value3, we will tap AI to automate our credit research and assessment processes and be far more efficient in our fixed income evaluation and investment management.”
The credit rating, research and reporting service is expected to be launched first in Singapore in December 2019 and subsequently in the other ASEAN markets.
1 Value3 is a finalist of the 2019 FinTech Awards at the Singapore FinTech Festival
2 Value3’s AlgoCRED AI-platform is currently available in Switzerland, covering approximately 1,400 Swiss franc bonds.
3 Refer to bonds that have not received a credit rating from one or more of the three global rating agencies: Fitch, Moody’s and Standard & Poor’s.
4 Corporate bond issuers do not have to pay fees for their issuances to obtain credit ratings on the AlgoCRED AI-platform.
5 UOBAM was named best fixed income fund house at various industry awards. Please refer to https://www.uobam.com.sg/about-us/awards.page for the full list of awards.