Traditional retail banking providers, weighed down by monolithic legacy systems and ponderous regulations, are in uncomfortable territory. Advancements in fintech have upended the industry, enticing both large financial firms and smaller tech startups to apply disruptive technologies in ways that threaten the status quo.
To become more agile and remain relevant, traditional retail banking providers find themselves exploring their technological options with focused intensity. In particular, they’re looking for insights into customer behaviors.
The answer? Advanced data analytics.
New innovations in data analytics empower financial institutions with systems that are so smart, they learn on the go, automatically refining their algorithms and improving their results over time. This isn’t your grandpa’s approach to data analysis — spreadsheets, data tables and crunching numbers on a calculator. This is true artificial intelligence (AI).
Today, banks and credit unions can increase customer stickiness by having digital assistants effectively manage routine inquiries and provide personalized advice. All this can be achieved with minimal day-to-day oversight; it runs in the background, adheres to compliance protocols, and can dynamically adapt to new regulations.
Advances in automation and data-led intelligence put sophisticated AI technologies within reach of traditional institutions — those without the R&D skills and resources to pursue such initiatives internally. This is because the modern AI platform can essentially stand on the shoulders of the data- and process automation technology trends that preceded it. The data sets that capture the boundaries and basic interaction rules already exist and are within the regulatory purview.
According to the “Innovation in Retail Banking” report from Efma and Infosys Finacle, financial institutions understand the potential impact and benefits of AI, but that they are still hesitant to act. They are approaching it piecemeal, slowly building towards AI competency by stacking on more and more of the innovative technologies they know they will need — creating the foundation they need one building block at a time.
But there are other significant impediments to progress. In particular, the Efma/Finacle study found that half of banks listed their legacy systems as the biggest hurdle they face, followed by a lack of unified vision (44%) and a shortage of skills and experience (38%).
The Efma report found 58% of banking providers believe AI — along with several other technologies such as advanced analytics, big data and open APIs — will (eventually) have a significant impact on the industry. Noticeable progress is already evident in arease like automation, machine learning and data-led intelligence, which are already yielding new efficiencies. Still, AI will take several more years to reach its full potential.
While financial institutions estimate AI’s impact to be low in the immediate future — only 37% of respondents in another study by Infosys said they believe its impact will be significant in the next two years — the financial services industry is investing much more in AI technologies than other industries, and these investments will continue to grow steadily as banking providers get closer to achieving their fully-functioning AI-driven systems.
