Future of Operations: Finding a Home for Fintech
Could new technologies free your workforce from ‘soulless business processes’ and allow them to focus on value-added client engagement? In this white paper, Broadridge and SIFMA’s Asset Management Group (SIFMA AMG) have partnered to explore this question and more.
The overall business case for new technology is clear – but the ability of financial services to harness the power of fintech in their operations to exploit the current boom and any future potential upside is not. When it comes to new technology, it appears that the operations functions of asset management firms are often dipping their toes in the water, rather than taking the plunge. Advances such as Artificial Intelligence (AI), Cloud Computing, Distributed Ledger Technology (DLT) and Robotic Process Automation (RPA) have the potential to further transform operations, reducing the human workload, squeezing new efficiencies out of processes, and lowering costs.
With findings from surveys of SIFMA and SIFMA AMG members, we ask: how can operations find a home for fintech?
Excerpt
To an outsider, it might look like the financial industry is flourishing: asset managers continue to generate healthy returns, win and retain clients and innovate along the way. We are also safer and sounder after the implementation of new regulation over the last decade. But insiders will know that not everything is rosy. Asset managers continue to grapple with lower fees. New regulation may have shored up the ship, but it continues to make demands on our time, energy and resources. Despite the various challenges, there is cause for cautious optimism. One bright spot is the increasing sophistication and agility of the operations function—the middle and back offices that manage risk and keep the information, cash and products flowing. Today, information technology advances such as Artificial Intelligence (AI), Cloud Computing, Distributed Ledger Technology (DLT) and Robotic Process Automation (RPA) have the potential to further transform operations, reducing the human workload, squeezing new efficiencies out of processes, and lowering costs. Fintech, if correctly deployed, is a proven alpha-generator in everything from debt and equity issuance to trade finance and commercial insurance.
Small, nimble technology players and Big Data companies alike are enjoying what Oliver Wyman has termed “flywheel momentum”. This flywheel momentum has a virtuous cycle. Technology companies continually gather and analyze data in ways that enable them to better understand their customers. This allows them to offer their customers more value-added services, which in turn brings in even more data. The biggest players have only scratched the surface in terms of what they might go on to do in financial services.
The overall business case for new technology is clear—but the ability of financial services to harness the power of fintech in their operations to exploit the current boom and any future potential upside—is not. Fortunately, the will is there. The 2019 SIFMA Operations Conference and Exhibition demonstrated that financial services firms already understand the link between technology and productivity gains. There is a strong and clear consensus within operations functions around the need to automate and take processes to the next level in an industry where humans still work in Excel sheets to gather information from one system and transfer it to another.
Despite the consensus, it appears that the operations functions of asset management firms are dipping their toes in the water, rather than taking the plunge, when it comes to new technology. Can the industry find a home for fintech?
Fintech Opportunities
- Some common fintech opportunities that financial institutions are analyzing, preparing to deploy or currently utilizing include:
Artificial Intelligence (AI): AI simulates human intelligence and can be used to increase efficiencies and lower costs in what would normally be manual tasks such as market surveillance, anti-money laundering (AML) and know your customer (KYC). - Cloud Computing: Cloud involves moving from on-site IT systems to software residing in a separate data center.
- Distributed Ledger Technology (DLT): DLT, of which blockchain is one type, is a consensus of replicated, shared, and synchronized digital data that can be geographically spread across multiple sites.
- Machine Learning (ML): ML is a subset of AI where computer algorithms can learn from data without specifically being programmed, and autonomously learn over time at identifying issues or options.
- Regulatory Technology (Regtech): Regtech is the utilization of technology, such as advanced analytics or ML, to aid in compliance, reporting and other regulatory requirements.
- Robotic Process Automation (RPA): RPA is a type of process automation technology based on the notion of software robots mimicking the actions of humans in carrying out a specific task. It is meant to take the repetition out of routine tasks, freeing up employees to focus on higher value assignments, such as those involving client interactions.