Changes in customer behaviour and expectations were already creating pressure for change among risk managers. The increasingly real-time nature of financial services has forced banks and regulators to reassess how and when risk is calculated. Once-a-month assessments, based on historical aggregated data are out of date before they are produced. Instead, banks need to rely on current transaction data to give the most accurate picture of a customer’s current status, and thus underpin the best risk decisions.
New data, new opportunityTransaction data is just one of the ‘new types’ of data required by risk managers. The increasing diversity of risks calls for wider ranging data from multiple sources, many of which are outside of the bank. For example, in COVID times, regulators began asking banks for the number of rooms, car park spaces and occupancy levels of hotels they were lending too. This information simply did not exist in current risk analysis systems. Climate risk is another emerging case for integration of broad and granular data from multiple external sources to support effective risk calculations.
But the biggest challenge for risk managers is moving to adopt the ‘segment of one’ approach pioneered by marketing. Calculating risk in real time, to deliver a personalised rating based on what a specific customer is doing in the moment may seem beyond the capacity of the risk department. Using out-dated manual processes and silos of data it is. But with the access to integrated data that marketing teams are beginning to leverage, plus the latest automation, analytics and AI practices, risk teams can benefit from investments already made to create game-changing advantage through risk.
High stakes, high reward
Of course, the stakes are high. A mistake in targeting a marketing programme can have significant implications, but nothing compared to the legal, financial and compliance risk associated with bad or non-transparent risk decisions. For this reason, the use of analytics and AI has been approached cautiously in risk, and rightly so. However, in environments like Vantage, day to day skills and approaches of risk management can be automated as a first step to building more sophisticated analytics. Enterprise feature stores and AnalyticOps approaches can provide the auditability, governance and transparency needed to supply regulators and bank leadership with sufficient evidence of how, when and why decisions were made.
Suddenly, from being a back-office function, focused primarily on meeting the demands of the regulator, the risk team can add value across the whole bank. Risk management is the DNA of banks and could be the real competitive advantage they need to fend off encroaching fintech and big tech players. Embracing risk as a core element of sustainable and fair business models can impact every aspect of the bank. From keener pricing, delivered in real-time but based on accurate, auditable risk decisions can improve top line whilst reducing costs.
Creating a risk-literate culture that pervades the whole bank and leverages unique, trusted, real-time data, provides the foundation for improved customer service, lower costs, improved innovation and faster time to market.
It is time to stop thinking about risk as essentially something a specialist team does to report to the regulator. With a foundation of integrated data, available across the bank, as well as specialist analytics deployed at scale and capable of supporting real-time decisions for 50 million or more customers, risk decisions should be part of the day-to-day operations of all bank departments driving new value.