Using Data Analytics in Risk Management
By Gary Pearce
Sep 24, 2021
Most risk managers rose to their role through a technical emphasis rather than a technology emphasis. Differently put, their passion is in addressing business issues such as claims, insurance coverages and risk financing, not in writing code or learning obscure programming languages. They are interested in technology and see its value, but they are very busy and regard technology as a means to accomplish non-technology objectives.
While this business emphasis was the driver of their success, it can leave them under-prepared to deal with the emerging world of big data analytics. Indeed, the subject can seem so big and complex that there is a strong urge to put off any exploration whatsoever. If only there were a practical way to traverse the enormous learning curve!
The good news is that technology has advanced to the point where its adoption has become more practical, not less. Here are some pointers for the risk manager regarding how to begin what can be a very worthwhile journey into the world of risk management data analytics.
- Work backwards. Start with your business needs, not the path to addressing them. Be exquisitely aware of the risk of allowing preconceived notions of what is and is not possible to limit your vision and reach.
- Consider possibilities, not just needs. Once you’ve identified your key needs you should move on to what’s possible. Breakthrough results often come from new innovative ways of thinking, not fine-tuning what’s already known. Again, beware of self-limiting your analysis at the early stages.
- Forget about being the tech expert. It’s just not your role. Yes, a good awareness of the landscape is beneficial but the lack thereof is no obstacle. Between those within your organization who are charged with technology, and the resources available through the providers of any relevant technology platform, you probably have more than sufficient coverage.
- Don’t boil the ocean. Stick to a handful of carefully considered business needs. You didn’t put all your current processes in place overnight, nor must all your technology initiatives be addressed in one fell swoop. Stay focused on executing a short list of priorities, and move on only when they’re in place. Start small if needed.
- Keep an eye on what’s actionable and compatible with the business. Clever analytics aren’t of much value unless they point to practical action.
- Take an inventory. Do you know of the key data pools within your organization? Might there be rich sources of information already in place that offer enticing opportunities for further exploitation? Reaching out to key stakeholders may yield pleasant results.
- Lean on related parties. Your needs might not be unique, or your ideas may be more powerful when you join forces with other stakeholders. Colleagues in functions such as security, legal, HR, and internal audit, among others, are probably good allies and potential partners in developing solutions for the larger good.
- Consider new realms. What about counterparty risk? Supply chain exposure? Cyber risk? Compliance? Ethics and corruption? Somebody is dealing with these and other issues, so they should be potentially in scope.
- Seek scale. When setting scope and priorities, have a preference for the repeatable, the lasting, and solutions with multiple applications or higher volume.
- Be proactive. Reacting to known situations is fine, but there is greater opportunity to add value if you don’t stop there. This matches up with the earlier statement about considering possibilities, not just needs. Just being reactive usually isn’t sufficient anymore.
- Anticipate obstacles and objections. No process is perfect; the typical journey tends to involve a few unexpected challenges. By thinking ahead you can minimize their impact if not totally remove them.
- Consider the expectations of your management, your auditors and your board of directors. Risk is top of mind in the c-suite these days. How would your vision address their interest?
- Envision yourself delivering results. Imagine delivering new ideas to your leadership team, or demonstrating true insight to your insurance underwriters, or prompting changes that allow more people to go home safe to their families every night. The attraction of the end-state can be part of the motivation to lead you through the process.
When seen in this light, it becomes clear that risk management data analytics isn’t some exotic boutique undertaking reserved only for the mad computer scientists; rather, it’s just another way of putting practical knowledge to better use. In fact, those IT savants are pretty helpless without the risk manager leading the effort and setting clear direction.