Automated Risk Management & Decisioning
Digital transformation is coming to the financial services sector. Consumers are adopting digital technologies at a breathtaking pace, and Fintech startups are disrupting the industry by creating new lending models and similar solutions to meet consumer demands. Banks and credit unions, meanwhile, are left to contend with strict regulatory requirements that limit their flexibility and create risk management complexity.
Gradual, consistent technological innovation has helped firms contend with these changes, but the period of disruption isn’t over. McKinsey predicts that the financial services sector could face even more risk management change in the next 10 years than they did last decade. Increased automation, growing demand to collaborate across lines of business and a need to advocate for corporate values within risk management schemes are all emerging as key disruptors moving forward.
How automation is transforming risk management
Big data is central to the way automation is changing how organizations assess and manage risk. In essence, companies use analytics to compile more data, create more robust scorecards and put all of that information into decision engines to identify how much risk a loan presents. The lending choices can be made without human intervention, meaning the only need for a person is by choice. This isn’t always the case, as some complex lending processes or loan types will involve humans at key checkpoints, but the marketplace lending industry, for example, has gained an edge over traditional financial services firms by accelerating loan processing by minimizing the human factor.
“Effective automation that reduces manual processes can simplify lending.”
McKinsey pointed out that effective automation that reduces manual processes can simplify lending. It also makes it easier to comply with regulatory rules and eliminates human bias during decisions.
The problem is that machines can’t necessarily replace humans entirely. In fact, McKinsey pointed out that operational models in risk management will likely shift to have people focus on new and more nuanced responsibilities instead of being outright replaced by machines. This is essential as firms try to deal with increasingly complex environments while taking full advantage of what automation has to offer.
Considering cultural change made available by automation
A Harvard Business Review report explained that the complexity businesses are experiencing in terms of risk management – especially in light of regulatory scrutiny – is making values-based decision-making and clear ethics rules particularly important. Because risk decisions are so complex, it becomes incredibly difficult to identify exactly where processes break down or go wrong from an ethical or legal perspective. However, most failures end up happening when humans faced with a short-term corporate outlook or enterprise indifference end up making choices that create risk.
In practice, the speed and complexity of the modern economy pushes people to make choices that are less-than-ideal because the individuals are overwhelmed. In financial services, these problems can take many forms. Automating backend procedures in risk management enables firms to revisit values-based decision-making processes and embed them into operations. When analytics platforms provide all of the data-driven risk assessments businesses need, human workers can then focus on the more nuanced issues that normally aren’t considered, becoming more valuable to the organization. Check out our video on how analytics can drive efficiency gains to learn more.