I-OnAsia has specialized in due diligence and independent investigations into Environmental, Social, and Governance (“ESG”) issues for over nineteen years.
I-OnAsia’s team has completed over 15,000 cases in Asia since 2001, investigating hot topics such as Human rights, Climate change, Cyber security, Tax avoidance, Breaches of fiduciary duty, and False reporting.
I-OnAsia has investigated:
- Many dozens of suspected human trafficking and indentured servitude cases, on behalf of retailers and manufacturers sourcing in Asia.
- Forced labor at Asian factories that have wrongfully perverted national military and local police units to pressure workers against unionization.
- Timber and jewel smugglers harming the environment, and followed their money trails.
- Bribe taking and corruption on major natural resources extraction deals.
- Dumping and anti-competitive practices that have an ESG component.
- Unfair wealth concentration at the expense of minority shareholders and workers.
- Systemic failures to combat sexual harassment and sexual misconduct in the workplace.
- Failures by ESG monitors to do their jobs, and bribe-taking.
We are extremely proud of this aspect of our business.
I-OnAsia’s team has a demonstrated track record of integrity, fairness, investigative ingenuity and a bit of savvy.
Through our work, we also know who the “repeat offenders” are.
Here are trends we are seeing:
- Hedge Fund are increasingly being asked by institutional investors that are signatories to the United Nation’s Principals for Responsible Investment to mature their ESG diligence process.
- Key data that is used by many research houses to generate an ESG compliance or quality rating remains flawed, due to reliance on data sets that are compromised, either because the data has been supplied by the business itself or collected by third parties focused on a “lowest common denominator” standard of public records data collection. These are garbage-in / garbage-out problems.
For example, in performing volume ESG due diligence into third parties on behalf of one of the world’s largest garment brands, I-OnAsia has found that in over 60% of cases third parties have submitted false information relating to their ownership structure on due diligence questionnaires.
In another recent investigation for a large investor, I-OnAsia identified false statements made to other investors relating to the salaries and treatment of workers.
The underlying ESG problems were so severe that the company is likely to fail, but the public statements made by the company are painting a false picture.
In another example, published information was falsely flagged a “negative finding” by a “black box” AI model assessing a subject’s ESG risk.
Needs for ESG monitoring at scale (by investors and the corporates themselves) create systemic vulnerabilities, and a false sense of security.
Collective approaches by groups of investors and enterprises concerned by ESG has resulted in a concentration of resources in monitoring programs that reduce the individual investor’s level of involvement and oversight.
I-OnAsia is regularly called upon to perform independently minded due diligence on behalf of investors that are concerned about concentration risk in the due diligence process on “club deals”.
In one horrific case it was too late, our client declined to perform independent due diligence and accepted the due diligence of another loose club of investors.
The underlying work performed by that club had been faulty, and valuable water rights were not legitimately obtained from the local government.
The losses to our client were in the tens of millions, after the business failed and was sued by locals for having disturbed local drinking water without proper approvals.
One possible outcome from these trends is likely to be material financial losses and reputation damage by investors that overly rely on diligence that uses weak data and club approaches to ESG monitoring.
Another possible outcome from these trends is that smart investors can increase returns by finding deals the group-think is avoiding.
