- Mature applications of AI are becoming more common in banking.
- Outlined below are three best practices for how banks can get the most out of investments in AI innovations.
- Insider Intelligence publishes hundreds of research reports, charts, and forecasts on the Banking industry with the Banking Briefing. You can learn more about subscribing here.
AI in banking is entering the mainstream as financial institutions start incorporating AI solutions into their businesses: A majority of financial services companies have implemented the technology for purposes like risk management (56%) and revenue generation through new products and processes (52%), per the Cambridge Centre for Alternative Finance and the World Economic Forum.
In Insider Intelligence's recent AI in Banking report, we discuss some of the most important tenets for banks looking to drive positive ROI from investments in AI innovations. Below are three best practices for banks looking to get the most out of their AI deployments, based on the strategies currently in use by banks that are finding success with AI applications.
- Find the right balance between developing proprietary solutions and collaborating with third-party providers. Banks must determine which developments and technology enablers need to be created in-house, and which elements can be entrusted to third-party solutions without losing competitive advantages, Álvaro Martín, global head of data strategy at BBVA, told Insider Intelligence. Bigger banks could create several new tech solutions in-house to exercise greater control over the final product, while only using third-party partnerships to roll out simpler features in a shorter time frame. Smaller FIs that want to leverage AI, on the other hand, may need to rely more heavily on turnkey solutions offered by third parties due to a relative shortage of AI talent, the expense of hiring the talent that exists, and a lack of resources to dedicate to development.
- Centralize data for easier utilization. The success of AI algorithms depends on the data used to train them, so FIs should realign their data-handling processes and technology infrastructure to centralize data storage and make it easily accessible to any business unit across the organization that needs it for their AI innovation efforts. At Bank of America (BofA), centralizing all of its data into a place where it can act on and leverage the data effectively was one of the most important challenges the bank overcame in its AI efforts, Christian Kitchell, AI solutions executive and head of Erica at BofA, told Insider Intelligence.
- Take the long view on judging AI solutions' success, while still bearing in mind the ROI of solutions they deploy. Kitchell said that an essential part of a successful AI strategy is getting the support of leadership that understands AI is a long-term effort to evolve the client experience for the better, and that it's important to stay the course and make the investment year-over-year. However, banks should still keep a close eye on the ROI and business impacts of solutions they implement from the start to see how they track as they mature, and consider ending investment in innovations that aren't consistently benefiting their bottom lines.
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