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Risk management, technology and banks - perfect storm or catalyst for change?
Politics, pandemics, fintechs and regulations. Banks are relying on risk management functions to build resilience to the challenges they face and keep them safe.
The risk management role is changing to include new approaches to managing non-financial risk and the effect of market digitalisation.
Technology, such as AI and powerful data analytics, will provide capability, efficiency and security for banking and financial institutions.
Risk management is undergoing a period of dramatic transition in banking. With a pandemic, political instability, a shift in climate and societal values, regulations, low interest rates and digitalisation posing ongoing challenges, risk officers can no longer focus solely on financials and must form a critical pillar of institutional resilience and growth.
A new PwC study, Risk Management 2025 and beyond - priorities and transformation agenda for the banking industry, spoke to more than 80 risk professionals at global and regional banks to gain their perspectives on key priorities and transformation ambitions.
The findings show that banking risk functions are becoming and need to become more dynamic and flexible, increasingly helping their institutions through a complex and volatile landscape of opportunities and threats. With major advances in the use of technology on the horizon, capabilities will need to be strengthened and new areas brought into the risk management fold.
Risk and business transformation
Technology change, new competitors and pressure on shareholder returns are putting pressure on bank business models to evolve. As they do so, risk functions will need to pivot their skills, capabilities and infrastructure to keep in step.
Most banks see the need for risk functions to adjust as traditional value streams are disrupted, forcing businesses to reposition or find new sources of values. Key drivers for this change include the disintermediation of the market as technology and telecommunications companies, as well as fintechs, decouple payments and transactions from the banking sector.
Additionally, digital assets and cryptocurrencies continue to move towards the mainstream, and it is expected that more central banks will launch their own digital currencies. Blockchain technologies will likely be adopted across different industries, reshaping business models around payments and settlements, further disrupting incumbents but also providing great opportunity.
Of interest, threats and trends such as disinformation and the Internet of Things were expected to be highlighted as new gaps or considerations for risk identification, but did not come up as much as expected by those interviewed.
Technology to help with non-financial risk
Emerging non-financial risks are also increasing the need for new frameworks, assessment approaches and organisational structures. Cyber and climate change, each with diverse impact channels are two such areas. So far, significant differences exist in organisational maturity and ambition related to non-financial risks and present a complex area for risk in most banks.
Technology can help address such risks, such as in the use of data. Poor data quality and availability need to be addressed, however, as these often limit the ability to perform even simple analytics. Data is foundational to the predictive and targeted capabilities, so effort must be made to define the correct data points, and make them accessible in a high-quality format.
Governance, Risk and Control (GRC) systems and processes need to be redesigned as tools that work for a bank’s management layer, with simplified requirements and user interfaces. There is further work to be done with such systems so that they encompass data models that include enriched non-financial risk datasets.
Institutions have thus far opted for reconfigured vendor solutions or in-house platforms when it comes to GRC systems. The benefit of these includes a significant increase in risk maturity at a business management level, as well as greater proactivity in identifying risks and issues — and a substantial reduction in costs.
Smart technology can also help staff take automation to the next level. AI and machine learning are increasingly helping with bank risk, such as in anti-money laundering (AML) and fraud. FAQ-style self-service tools and digital assistants are allowing bank staff at many institutions to assess risk real-time.
Automation for competition
Indeed, new tools and models have gone into production across the risk management cycle. However, realising the potential of emerging technologies at scale still faces a number of challenges, in particular with regards to legacy infrastructure.
Many firms in the study see big data and AI/machine learning as a must-have to remain competitive, especially with limits as to how much the cost of risk and compliance can be reduced without using advanced analytics. Not every institution has made the same progress when it comes to analytics, automation and AI, but all are at least thinking about experimenting with applications.
A lot of this adoption is coming from within institutions organically, where large analytics and data science teams are emerging from within risk functions and driving the data and tooling agenda. But obstacles remain in terms of data quality, legacy systems, ROI, and accountabilities.
Compliance and financial crime are areas where most banks are using some form of AI/ML tools as they prove transformational, enhancing effectiveness and efficiency, while also being well received by regulators. Institutions highlighted that they were looking to expand these learnings to other areas of focus throughout the business, including to priority areas such as credit risk, operational risks and regulatory/internal reporting.
The banking-tech bottom line
Technology is itself changing the banking landscape, but while providing challenges in the market, it is also fundamental to helping institutions to compete, understand risk and create efficiencies.
Banks wishing to embrace automation and analytics should establish a technology vision and integrated roadmap aligned to other parts of the organisation, underpinned by strong governance and demand management.
Smart tools, such as interactive systems and chatbots should be prioritised for larger/international firms to augment staff with analytics capabilities and future-proofing. Finally, as increasing investment goes into addressing data quality and using that data for a competitive edge, ethics and privacy issues will need to be addressed in clear and actionable policies.
The move to predictive analytics around early warning systems has worked well, and different activities are being used well to measure and manage risk (for example, digital twins being used to identify areas of process risk led optimisation). All of these moves will help to drive productivity gains and allow banks to do more with less — all while enabling the risk function to become a strategic pillar of banking institutions.
For detailed information on the risk management function in banks, including areas such as preparing for climate change, generational workforce transitioning and the lessons from the COVID-19 crisis, download the Risk Management 2025 report.
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