The spread of energy deregulation across the Asia-Pacific region and the opening of China’s commodity markets have created a host of new trading opportunities in recent years, causing a surge of new players to enter the region. However, risk management challenges abound, particularly around credit.
For Asia-based credit risk officers, counterparty risk assessment is notoriously difficult due to the lack of publicly-available data on the creditworthiness of smaller players. Additionally, many smaller players are still using spreadsheets rather than an energy trading and risk management (ETRM) system, leaving them struggling to obtain a holistic view of their risk. This can also create operational challenges as spreadsheets do not have the inbuilt error-spotting and data-cleaning technology of ETRMs. Meanwhile, multinational firms with an office or subsidiary in Asia often also struggle to get an enterprise view of risk due to poor communication between their multiple ETRM systems.
Understanding this, CubeLogic, an enterprise risk management software firm, entered the Asia-Pacific region last year, opening a Singapore office in October 2017. The impetus was to better serve existing clients in the region, but it also saw a growing Asian appetite for its products. One of its biggest projects in Asia to date, signed earlier this year, is a deal with a multinational energy firm in which CubeLogic replaces two legacy ERM systems worldwide. It is also currently rolling out its products to the Asia-based teams of a big mining conglomerate.
Its ERM platform – which can be provided on-site or in the cloud – is designed to give a holistic view of risk across an organisation, allowing for accurate measurement and better management of market, liquidity, regulatory and credit risk. It does this by pulling data from numerous systems across and outside an organisation, standardising it and feeding it into the relevant risk modules where calculations and analyses are carried out.
The credit risk function benefits from this in particular due to the non-standard nature of much credit data and credit risk measures, says CubeLogic’s Singapore-based managing director Karl Sees. “If a chief risk officer wants to know the company’s aggregate exposure to a particular counterparty, it is very difficult to get that quickly when the data is scattered across numerous systems,” he says. “We bring together that data in near-real time and provide an instant enterprise view of the exposure, taking into account complexities such as future deliveries of product to the counterparty, whether deals are done on a fixed-price or floating basis, invoice terms, rules around collateral and so on.”
CubeLogic also brings in outside data from traditional sources such as rating agencies, bond prices, credit spreads, equity prices and the credit default swap market to help with internal counterparty credit scoring. However, in Asian commodity markets, many counterparties are privately-owned, unrated and unquoted companies, and very little data is available on them. “In Asia, it’s hard to get the financials needed to do fundamental credit work,” Sees says. “There’s no publicly available information on many Chinese firms, for example.”
To that end, CubeLogic has developed CubeWatch, a social media sentiment analysis tool that takes feeds from sites such as Twitter, LinkedIn and Glassdoor, and analyses them to identify positive and negative sentiment towards particular firms. It then produces a score that can be tracked over time.
If there is an event like a pipeline leak or a protest against palm oil production, social media may be a better early-warning indicator of potential reputational risk than equity markets would be
Karl Sees, CubeLogic
“This sits on a credit officer’s desktop and is particularly useful for early-warning information on companies that don’t have publicly traded securities,” says Sees. “For example, if there is an event like a pipeline leak or a protest against palm oil production, social media may be a better early-warning indicator of potential reputational risk than equity markets would be.”
This year CubeLogic also developed a component for physically tracking cargoes at sea and calculating the credit risk associated with them. “This is particularly relevant to the Asia-Pacific region where so much trade is shipped,” says Sees.
Additionally, to address some of the operational problems associated with spreadsheets, CubeLogic has developed a ‘rules engine’ that can examine all incoming files and spot errors such as empty fields or data that needs enriching or deleting. It then adjusts the data and flags the error, putting it into a workflow queue for operations teams to look at. “In theory operations teams can do this manually, but in practice it’s very hard to spot these errors,” says Sees.
He stresses that he doesn’t advocate firms using spreadsheets instead of ETRM systems as a long-term solution, but they can be a good interim tool while the market becomes more sophisticated.
CubeLogic’s move to Asia means it now has a global footprint with offices in Houston as well as London where it was launched in 2009.
- Quant Finance Master’s Guide 2019
- People moves: SocGen adds in prime services, Deutsche fills new rates hole, HSBC makes model move, and more
- Cross-currency swaps could hasten RFR shift in Australia
- Podcast: Kenyon and Berrahoui on the pitfalls of PFE
- EU parliament OKs no-action powers but leaked doc signals delay