Banks guard against a number of high-profile and critical risks in their everyday management and business activities. Some of their largest concerns include:
Credit risk: The largest risk to banks, the threat that borrowers will be unable to repay their loans and leave them out of pocket as a result.
Market risk: The impact of fluctuations in the financial world, such as interest rate changes, or other external cultural, environmental and economic changes.
Operational risk: Errors and anomalies created by people and processes that the bank relies on, for example, an employee mistyping a customer’s date of birth or account data duplicating, all of which compromises data governance and reporting compliance.
Cyber risk: The potential exposure of information to unwanted third parties.
These issues are well-known and familiar to most organizations. Worryingly, they are increasing in both volume and frequency. Accenture reports that 77% of risk leaders across a variety of industries have raised concerns regarding the fact that operational and financial risks are emerging more rapidly than ever.
An effective risk management strategy is therefore essential to keep banks properly protected, both today and as things evolve. Although it’s impossible to completely avoid an incident, it pays to be prepared and work hard to minimize the chances, as well as the impact if the worst should happen.
Structured risk management planning should set out to ensure stable, safe operations and performance while enabling continued visibility so that any issues can quickly be identified, resolved and learned from. In turn, this helps improve the efficient use of resources, time and budget.
Cashflow is every bit as important for financial institutions as it is for any other business. If it’s not managed and anticipated accurately and effectively, a bank can face collapse.
This famously happened to the legendary Lehman Brothers back in 2008, as part of the incident that triggered a global financial crisis. At the time, it was the fourth largest investment bank in the United States, with some $639 billion of assets – but it accumulated $613 billion of liabilities and had to shut its doors permanently.
In more recent times, under pressure from rising interest rates, Silicon Valley Bank collapsed. At this point, the market disruption has resulted in the seizure of Silicon Valley Bank and Signature Bank, the bailout of First Republic Bank and the takeover of the troubled Swiss bank Credit Suisse by its rival, UBS.
Managing risk poorly can also threaten a bank’s brand reputation and general standing with customers and in the industry. US Bank experienced this last year, after it was exposed for having pressurized its employees to open fake accounts in their customers’ names for more than a decade, in order to meet ambitious sales targets3. It was fined $37.5 million as a result, and lost face with investors and real customers alike.
Failing to comply with evolving industry regulations and laws can also spell big trouble for banks, ultimately imposing sizeable fines which can compromise brand reputation and consumer trust.
Like many industries, banking processes include a substantial number of repetitive and sequential tasks, which take up a lot of time and effort. Automation technology can revolutionize these processes by making them more efficient, less costly, error-free and flexible to adopt frequent regulatory changes.
The result is a better experience for employees and customers across the board, while enabling the bank to maintain competitive advantage and devote resources to other crucial tasks – like winning new business.
By leveraging the possibilities of automation, banks can become more strategic in planning and process, with minimal human intervention. Examples include:
Workflow optimization and automation: Creating workflows of risk management activities helps to promote transparency, accountability, and auditability. Workflows can then be automated to ensure that tasks are completed as and when they are needed, and minimizes the risk of human error. Automated hand-offs also guarantee that tasks are routed to the appropriate department.
Data integration and aggregation: Automating data collection from multiple sources and storing it in a centralized automation platform provides a holistic view of information. This means data from internal systems in the bank, and third-party data are all united in a single place for thorough risk assessment and analysis.
Risk monitoring & scoring: Automated risk monitoring systems can detect anomalies in real-time, enabling quick responses to any threats. Intelligent automated technologies can also use data to detect emerging trends, help make informed decisions, set risk thresholds and ultimately minimize potential losses.
Compliance and regulatory reporting: Automated workflows will not only ensure that processes are compliant by following the set rules, but will also generate an audit trail. It’s easy to pull reports for regulatory authorities to prove compliance.
Fraud detection and prevention: Process automation can optimize tasks involved in AML and KYC processes by analyzing customer behavior and transaction data to reduce banks’ risk of falling foul to fraud. Machine learning can be applied to predict patterns and stay one step ahead of criminals.
Risk mitigation and control: You can set thresholds and triggers within processes that are automatically responded to when limits are breached. This reduces the need for manual intervention and means that some actions can be pre-empted and prevented.
Bizagi has already helped several financial institutions across the sector to put automated technology to work in operations and compliance. By connecting and integrating systems, we have enabled end-to-end visibility of processes and made it easier to identify and mitigate potential risks.
Insight Investment implemented workflows that standardized processes, reducing operational risk by guiding staff through complex processes and handing off work reliably.
VKB Bank, introduced procedures that verify data to limit errors, improving data quality through system tests and validation.
AgFirst built rigorous process compliance checks, using agile workflows to immediately reflect changes to policies.
Old Mutual defined business rules that identify threats so individuals can flag suspicious activity for fraud prevention.
And Bancolombia automated repetitive and manual tasks prone to error, reducing operational risk by 28%.
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