In today's blog post, we're inspired by our interview with David Rogers, the Global Product Marketing Manager for Risk at SAS. During Q1 of 2021 SAS has partnered with Longitude, a Financial Times company, and undertook a global research program that explores how banks are transforming their approach to risk management. Accordingly, a survey involving more than 300 senior executives, was held around a number of pressing questions around the topics of decision making, risk culture, risk modelling. The results were recently published in a report and interactive story. Findings in this report give key insights into how investing in risk management can help executives unlock benefits for their organisations. Innovative analytical approaches to unlock these potentials are already available, such as the technology and solutions SAS provides, however part of unlocking the benefits come from having a right approach to risk decision making, in order to make the organisation truly resilient to the changes they face today and into the future. Can adapting a modern risk management approach really have an impact on an organisation's success and growth? Let’s check out some findings and possibilities.
Value of Being A Risk Management Leader
In recent years, automation and digital transformation of the business processes has been one of the biggest priorities of companies across many industries, and certainly the financial sector is one of them. A key part of meeting the demands of digital transformation is wrapped up in the introduction of automation. Nevertheless, when it comes to risk management, banks are seemingly struggling to make the necessary changes. The survey reveals that an advanced group of banking executives are leading the way in adopting automating risk modelling and digitizing risk management and accordingly calls them the Risk Management Leaders. While many Banks have been slow to improve their approach to Risk Management, those identified as Leaders are investing more with increasing benefits. Risk Management Leaders report higher levels of integration and accuracy across the risk management process.
Becoming a Risk Management Leader mainly comes from implementing risk modelling that goes beyond transparency and reporting and boosts companies' capability to adapt to rapidly changing market conditions. This creates an evolving environment in banking and ultimately enormous opportunities for having a better decision-making process in risk management to support regulatory and business needs. It allows the leaders to act accordingly to the early indications of changes by having a strategic view of their model life cycle. By standardizing their model life cycle the Risk Management Leaders can reuse and repeat many of the key processes model deployment, integrate the model life cycle with their decision engines.
We can predict the future of risk management will involve a more extensive approach on meeting regulatory requirements plus onboarding process, credit scoring and account management, collections management to meet digital market demands. With such a broad range of risk models, we haven't even started talking about the AI and open source types of models that can be applied for anything from computer vision to natural language processing and so on what we can say is "Yes, you have a lot of models. These models are likely to increase over time. Beta is growing, your segmentation schemas are becoming more granular. You want to offer more personalized services to your obligor."
This gives more reason for banks to become "leaders" and adopt a standardized model life cycle so they can reuse and repeat many of the key processes and gain the agility and efficiency they need to be competitive.
Data Comparison Between Risk Management Leaders and Overall
The approach and the understanding Risk Management Leaders have towards automating risk modelling creates a significat differenece on being able to utilize these tools effectively to unlock further benefits. As you can see from the data below, leaders are able to see the benefits of automated risk modelling more significantly:
The survey provides additional data to back up this claim:
- More accurate business forecasting: more than a third (37%) of Risk Management Leaders rate the accuracy of projected balance sheets as “very high” compared with 14% overall
- The ability to project balance sheets further into the future: almost half (44%) of Risk Management Leaders can project balance sheets three or more years ahead, compared with 19% overall
- Greater integration between risk management and business planning: fully 78% of Risk Management Leaders report that the bank has already integrated regulatory stress-testing exercises with business-planning exercises, compared with 45% of the overall sample with a shorter time to complete regulatory activities such as stress testing
- Competitive Advantage: 73% of RM Leader respondents believe that their risk modeling processes are a competitive advantage versus their peers, compared with 47% overall.
Based on these findings, we can see that Risk Management Leaders are more likely to have integrated stress testing with business planning and perform scenario analysis more frequently and are able to forecast further ahead than the rest.
How Other Banks Can Catch Up to the Leaders?
One thing we found really valuable in our interview with David and the survey is that the interactive report also suggests five crucial steps to take and quotes from experienced CRO's (Chief Risk Officer) on what they think about the challenges and opportunities when it comes to risk modelling in the banking sector.
Accordingly, the first step would be to standardize and modernize risk modelling. Especially considering the regulatory differences and limitations, standardizing risk modelling could certainly be a challenge - but a rewarding one. To build, deploy, and monitor models at speed and scale, you need to modernize your risk-modeling lifecycle. In many instances,having a standard framework across the institution will guarantee easy application of both common and advanced analytics while aligning with regulatory and internal governance.
Second step is to invest in cloud infrastructure and automation. Banks should ensure that they move away from legacy infrastructures to newer ones -especially cloud infrastructure- consolidate and analyze increasingly large sets of data faster and create better responsiveness.
Third step is to Focus on quick wins – not large-scale transformation. Digitalization and automatization is not done overnight - and bears the challenge of being too disruptive if done on a bigger scale too quickly. Banks should start by identifying areas where modernization can deliver the greatest value, and piloting lower-risk projects such as early warning systems, model monitoring, credit collection and fraud risk detection. Based on the results, they can move onto bigger systems.
Fourth step is to integrate risk management with business-planning activities. This can bring immense value especially for processes such as forecasting. If the risk management is automated, this also gives the ability to be more effective from a business perspective.
Lastly, the fifth step is to invest in talent. Automation is done right if the human touch is still there in a meaningful way. Risk managers should be focusing on things that really matter in an effective way. Investing in hiring candidates with the right skills and capabilities will be vital for stronger risk management and having opportunities to provide training for them is equally important.
Having recent and extensive data is critical to bring a good understanding in the complex world of risk.
As the Global Risk Community team, we once again thank David Rogers for his insight on using automated risk models to enhance benefits. More information about this topic is available in SAS's interactive survey story - From Crisis to Opportunity: Redefining Risk Management as well as their downloadable full report- From Crisis to Opportunity: Redefining Risk Management. The report also includes infographics on 4 different regions, namely Asia Pacific, Europe-Middle East-Africa ,North America, and Latin America. It's possible to see regional differences that are driving Risk accordingly with quite surprising results.