Capital markets have been impacted by the post financial crisis transformation of financial institution business models – not just post crisis regulations, but the opportunities and challenges brought on by new financial technologies. While the use of fintech and regtech for big banks has been a hot topic for years, Bloomberg recently reported that the US’ federal stimulus program to combat the recent economic downturn is pushing more community banks to embrace financial technology partnerships.
A new report from the Securities Industry and Financial Markets Association (SIFMA) assesses how the narrative around analyzing and deploying fintech opportunities has evolved, including:
- The Client Experience – Technology has changed how people live their lives, and these modern personal experiences (Uber, Amazon) are flowing over into financial services.
- The journey begins a few years back where we first looked at how financial institutions made strategic decisions on IT expenditures. Then, in the beginning, we had what can now be viewed as an overly optimistic tone for how to spend the bucket dedicated to new technologies.
- Now, while many opportunities in the fintech universe hold possibilities, when assessing deployment, we first consider potential hurdles to deployment. We look at what is the objective of the technology – is it transforming processes or platforms?
- The goal remains transforming legacy systems to modern ones, while keeping the economics in place and not disrupting client services. With this, we can assess the capital markets fintech maturity ladder, where not all technologies are on the same rung (capital market case studies included).
- No report on the fintech story would be complete without looking at regtech, an area ripe for technology.
Cybersecurity for individual firms and the financial ecosystem as a whole is crucial and always on the top of management teams’ agendas, to ensure resources (money and talent) are dedicated to the fight. - While data, or the new oil, is key, firms must watch out for that old adage garbage in leads to garbage out, i.e. data often needs cleaned up to be useful.