Data analytics to revolutionise risk
Data is likely to play a crucial role in helping corporates identify, quantify, measure, and monitor risk, transforming the way it is presented to boardroom executives. But for many risk managers in the Asia-Pacific region, the data analytics revolution is yet to take off.
Big data, the gathering and analysis of huge volumes of information, is integral to modern business, with companies across the globe harnessing the power of statistics to make informed decisions. While some industries, such as banking, have always relied on data, companies in every sector are exploring ways to use information to their advantage. Number-crunching artificial intelligence programmes and teams of data scientists are key to nearly every major corporation in the 21st century.
Data analytics is set to be a vital weapon for risk managers to assess performance and operational risk, from internal fraud to climate change or supply chain management. Data is likely to play a crucial role in helping corporates identify, quantify, measure, and monitor risk, transforming the way it is presented to boardroom executives. But for many risk managers in the Asia-Pacific region, the data analytics revolution is yet to take off.
According to a recent survey conducted by StrategicRisk Asia-Pacific in Singapore, risk managers are yet to adopt data analytics on a wide scale. About 50% of attendants at the October event said they used data analytics on an “ad hoc” basis. While 20% said they were not using data analytics at all. A further 20% of our audience said they had no plans to use data analytics. A total of 30% of our attendants said they were not undertaking steps to improve their use of data analytics.
Take a chance
Despite the slow uptake, risk managers clearly see the value in data analytics. About 60% of respondents to our survey said data could be used to help with risk quantification, and more than 50% said it could support key risk indicator (KRI) tracking. About 40% said it could help with simulation and scenario analysis.
Gordon Song, a PARIMA board member and senior risk manager, believes some risk managers do not know where to start on data analytics, and dismiss it as a specialist discipline.
Song said: “I suspect many risk managers do not understand what data analytics is to start with and do not know where and how data analytics can be deployed in risk management. People tend to think of “data analytics” as a black box discipline only availed to geeky data scientists; in reality, data analytics can be as simple as doing a pivot table on an Excel spreadsheet.”
The benefits of new technology and data analytics are clear to see. So why have so many risk managers in the Asia-Pacific region held back from using data analytics? What are the potential benefits, and will it be an integral part of risk management roles in the future?
Patrick Abdullah, vice president, enterprise risk management for investment company Astro Overseas Limited, says some companies have been slow on to integrate data analytics, while some risk managers simply “lack the initiative” to tackle data. He said a lack of proper training could also be to blame: “There is also a lack of experience among many managers, about how to assess data trends to draw informed conclusions.”
Abdullah said data can be used to identify risk in any sector: “Say a company is losing talent in the organisation, and the normal rate is about 7%, and the rate is 6%, it would tell the person doing the analytics this is well within the norm. If it is about 8%, it is a call for action.”
Abdullah said risk managers should approach the topic with the support of executive management: “It is very important risk managers are able to access data trends, particularly related to the scenarios they are analysing. The buy-in must come from the leadership teams. Risk managers must have the right skillset and exposure to be able to use data analytics to their advantage.”
Mark Wilson, a director at Risk 20/20, said data analytics are not used “anyway near as much as they could be.” He added: “Commonly, risk teams are too stretched to resource these projects, despite wanting to find smarter ways of doing things.”
Wilson called on companies to make their case to boardrooms: “Strong business cases to invest in analytics can usually be made based on cost savings. It also helps to have some exposure to data analytics to appreciate the other potential benefits, such as the insights they can unlock, that traditional work methods simply cannot.”
Be part of the solution
Chris Corless, a risk consultant at KPMG, expressed surprise at the results of the Singapore survey. He said: “What many of us are doing in the name of risk management is no longer adequate”. He added: “Data analytics is a key part of the solution.”
Corless said current approaches to monitoring risk were flawed. He believes the industry suffers from a lack of skillset to manage the field. As part of the solution, he said companies could introduce analytics with the help of external advisers: “Perhaps with pilots bringing in skills sets from outside your organisation or perhaps running specific hackathons to bring in expertise from a completely different angle. Once you have a proof of concept and see how it can work, I think risk leaders will be better placed to understand how best to organise their teams and what skill sets they need to start migrating to.”
Corless said risk teams could learn from other business divisions already using big data: “Most organisations I have seen lately are utilising data analytics to help optimise business performance, they are developing the skills and tools to do this. I believe risk managers can utilise much of this newfound capability, especially when starting.”
Danger and delivery
While data analytics can help risk managers spot potential danger, it is also an effective way to deliver information, experts say.
Astro’s Abdullah said data analytics dashboards were an effective way of conveying information, bringing together different risks and providing a clear overview. He added: “A dashboard will tell you if you are going out of alignment. Movement on a dashboard will tell you if a performance risk or financial risk is doing well.”
Abdullah said risk dashboards enabled Astro to track its performance risk and financial risk, and was presented to the board each quarter: “You have a business plan, you have to track it. Financials is one part of it, and KPIs are another. Dashboards help us marry the two together.”
While risk managers are yet to adopt data analytics on any meaningful scale in the Asia-Pacific region, market observers predict it will become an integral part of risk roles in the year to come.
Song called on risk managers to use data to improve efficiency: “It is only in recent years that people and companies have built the capabilities to collect, manage and use such ‘big data’. Every risk manager needs to begin with a mindset shift to make data an integral part of their work, and move from a ‘reactive’ stance to a ‘proactive’ stance – this includes thinking upstream on what data to collect, how to collect and store it, and how to process such data intelligently to make sense of them.”
KPMG’s Corless believes the wealth of available information available to modern companies will help teams spot dangers earlier than ever. He expects artificial intelligence will become just as important as human teams in the years to come.
He added: “As we get better at utilising machine learning and AI, we will begin to consider a variety of analytics that can provide early insight on changes to the risk that we previously could not have dreamed of. But to get there, we have to start the old fashioned way by leveraging the skills and experience of our people who manage the risk on a daily basis.”
The future is now
While risk managers attempt to grasp the enormity of the big data revolution, the future is already here for some. The rapid development of data analytics is poised to transform the way risk managers operate, and for some, it has already.
Song added: “Every aspect of risk management, from identification to measurement to monitoring, and even risk transfer, hinges on reliable and comprehensive data models. Let me put it this way – risk management without data analytics is no different from “rolling the dice” to manage risks.”