Banks are picking up the pace to adopt technology that can provide holistic views of their risk after a spate of failures in the industry this spring raised questions around the state of institutions' operational resilience.
Rising interest rates, the recent banking turbulence and
"I think the activity of all the failures and the bank runs created an impetus to become more nimble in how we respond to new threats," Watson said. "So instead of focusing on reducing the amount of the risk and threats happening, banks are investing in technology in improving their responsiveness to a threat or risk once it occurs," such as automation and cloud platforms.
Companies that provide governance and compliance risk technology said they have experienced growth in demand from financial institutions in the last year, which has accelerated since March.
Gaurav Kapoor, CEO and co-founder of MetricStream, said he's seen an aggressive effort among banks to integrate teams, so that risk isn't siloed in any one part of an institution. MetricStream provides banks with a platform to monitor governance and compliance risks, such as third-party management and regulatory changes.
"Risk is not just about the top 200 people in a bank looking at it," Kapoor said. "Risk should be viewed [by all employees of a bank]. They all have a view on where risks might be sitting. So the ability to actually interact with the frontline and to be able to capture the risk is a big moment I'm seeing in banks."
One of the cloud's key powers is that it can be used to pool large amounts of data in useful ways. Watson said banks' appetite for cloud technology is on the rise as they look for better ways to manage data.
Mehna Raissi, managing director of banking solutions in the Americas at Moody's Analytics, said connecting different parts of the bank can also be an expense management play. She said
"Previously, there was more independence between the front office, middle office and back office," Raissi said. "We're seeing our customers thinking more about the integrated end-to-end. They want technology that really helps build a common language across the organization, and ensures that the lenders are also connected to those that are in the underwriting space, and also in the back office, where they're actually managing the portfolio."
Almost all financial institutions expected to
Regional banks will need to implement holistic, sophisticated data and risk analysis technology following last month's bank runs, experts say.
Tracy Moore, director of strategy in the Americas for Fenergo, also said she started seeing banks begin looking more closely at their compliance and risk technology about a year ago, but that the crisis in March increased the momentum. Fenergo provides cloud-native, automated compliance services to banks, and recently added continuous transaction monitoring of clients.
Jim Wetekamp, CEO of Riskonnect, said that he's seen banks seek increased breadth and depth in risk management technology, including increased agility to keep up with changes in a client segment or line of business, and third-party oversight systems
In March, Ronak Doshi, a partner focused on digital transformation and banking at the Everest Group, said in an interview that he
The buzziest topic in tech, artificial intelligence, is driving development in risk management. Building more cohesive views of data helps artificial intelligence systems function better, Watson said.
Only about 12% of regional and community banks and credit unions listed artificial intelligence as one of their top tech priorities for 2023, compared to about 36% of global and national banks, the Arizent research from last year showed.
Kapoor said MetricStream has increased AI investment by nearly three times. Moody's recently announced that it partnered with Microsoft to deliver generative AI solutions built on Azure OpenAI service. For example, a new tool called Moody's Research Assistant can compile and summarize information from multiple data sources for banking, capital markets and insurance clients.
Watson said there's been an ongoing shift from rules-based AI, in which humans design the rules, to machine learning AI, especially in cybersecurity and fraud. Last month, Google Cloud launched an anti-money laundering product powered by machine learning-based AI, which Watson called a first-of-a-kind. HSBC found in a study that the product identified two to four times more suspicious activity, while reducing alerts by more than 60%.
"I think the step to generative AI is real," Watson said. "It's not just hype. You are seeing Amazon, Google, Microsoft creating platforms that banks can use to get the benefits of large language models, but still keep their data separate."
