How much has the pace of financial services industry innovation accelerated? The last 10 years have upped the stakes to improve client experiences like no other time in history—ushering in enormous omnichannel technology investment. During this time, we also saw robotic process automation emerge, with its power to improve efficiency by managing data entry between legacy systems.
Yet the pace of change and scale of innovation over the past decade will pale compared to what lies ahead. Jim Marous, owner of the Digital Banking Report, said on a recent BAI Banking Strategies podcast, “The pace of change will never be this slow again”—a statement you can time not with a calendar, but with a stopwatch.
And that will force the industry to adapt at an even more rapid pace in 2019: a critical year as financial services organizations lay the foundation for and embark upon truly transformational change.
Clean up your data
Data holds the key to success for financial services organizations in 2019. Data will form the framework that drives financial services, experiences, relationships, products and processes. Organizations must have ready access to clean, structured, usable data in real time. This enables systems, analysis, segmentation and processes—and without it, a bank’s odds of success going forward will be limited.
With respect to data readiness, financial services organizations face a formidable challenge. Given how most of them were built, the task will involve accessing data from numerous source systems, silos and processes. Then comes cleansing and structuring, all of which must be done in a manner that respects privacy and compliance regulations.
Make way for more AI
What was true this time last year, when BAI named artificial intelligence its Trend of the Year, has only picked up steam. As the industry grasps the Internet of Things (IoT) and open banking like never before, expect to see an upward trend in AI adoption in 2019. And that raises the most elementary of concerns. As we’ve spoken to leaders throughout the industry and shared our use cases of AI implementation, one of the questions we often hear is, “Where do I even begin?”
It’s best to select a decision- and data-driven starting point of medium value: an appropriate experience, product, service or process. Start small, learn, succeed and then grow the organization’s AI capabilities. Starting with critical challenges will increase the odds of failure. In general, you should adopt AI in a manner that’s appropriate for your organization’s strategy, clients, employees and culture.
Regardless of how large or small your institution, start now. It’s critical. AI’s growth has hit an exponential pace. Those who continue to delay will fall further behind. Playing catch up will prove both time consuming and expensive.
Prepare for data-centric regulation
Regulation will play a role in another critical role in 2019 as the industry moves towards becoming data and technology driven. Privacy, security, trust and transparency will increase in relevance. Regulators and financial services organizations alike will have their work cut out for them as the pace of change accelerates.
Regulators will need new skills and knowledge as they work to stay current with the rapid evolution of data use and technology. They must understand those forces at a granular level and know how to ask detailed questions about how banks (and the technology/algorithms they deploy) function. This will extend to the parties with which financial services organizations partner. Lineage and compliance across complete value chains will require justification.
Financial services organizations must accept a new regulatory environment that more than ever stresses data, transparency and trust. They will also need to explain how data is used by technology and justify regulatory compliance. Hewing to the General Data Protection Regulation (GDPR) as well as emerging country, province or state regulations will add layers of complexity.
Find and land the right tech talent
In a recent BAI Banking Strategies article, president and CEO Debbie Bianucci discussed the pressures financial services organizations face to find, attract and retain talent—especially for high-tech positions.
Specifically, financial services organizations will face an extra hurdle to find the data science and AI talent they need, paying attention to the level of training versus task. For example, some hires may need a PhD for higher-level data strategy, architecture and governance activities; less formally educated data science staff can play critical roles in data cleansing, structuring and implementation.
Meanwhile, matching staff and skills will only require more focus and effort as new disciplines, roles and careers emerge. Determining what’s actually needed in advance prevents the waste of overpaid and/or underutilized resources so much in demand.
Compensation-wise, financial services organizations should remain flexible to compete for and hire this talent. But even that won’t be enough. They will have to bridge the gap in culture and benefits between themselves and companies perceived to be trendy and innovative, especially startups in sought-after locations.
Putting it all together: New Year’s revolutions
And so 2019 marks a time for financial services organizations to build solid data and talent foundations—not just for now, but the rapid transformation in the years ahead. Playing AI catch-up, lagging in regulatory modernization or losing the talent race aren’t acceptable—but they’re also not inevitable. Even if it’s a few weeks past making those New Year’s resolutions, smart banks know that the quest for digital excellence is no longer temporary: It’s timeless.
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Based in Toronto, Kunal Chopra is head of financial services at Gradient Ascent.
For more 2019 predictions and insights, check out our recent podcast with BAI's Leadership Team.