It gives me great pleasure to introduce the second of the fintech special issues of Cutter Business Technology Journal (CBTJ). This special issue further showcases the R&D work undertaken in State Street Corporation’s Advanced Technology Centres in University College Cork (UCC) and Zhejiang University (ZJU) and expands upon several of the concepts raised in last month’s edition. Specifically, this issue focuses on key topics of interest for financial services organizations, namely equity crowdfunding, legacy systems migration, robo-advisors, test outsourcing, and refining the reconciliation process.
Financial services is a sector with significant information systems challenges. Even today, with the myriad of technology advancements that have taken place in the industry, legacy information systems remain very much in situ. Legacy systems are renowned for their inflexibility, which is hardly surprising considering most financial services organizations invested in information technology with a short-term view, not intending for it to last a significant period of time. Between poorly documented systems and the loss of original legacy information systems designers to retirement, organizations are finding both current maintenance and further development difficult. This has prompted many to look beyond their organizational boundaries for assistance with their information systems implementations.
Over the years, firms have pursued various strategies in designing, developing, testing, and implementing their information systems. Many have opted to outsource in various ways, from complete outsourcing of the IT function to engaging in strategic partnerships. Regardless of the model adopted, the upshot is that significant aspects of a financial services organization’s IT are undertaken by third parties. While it is a common and mature practice, such outsourcing has not been without issues. Much remains to be understood as to how financial services organizations can successfully outsource and partner with third parties.
A second aspect of the legacy systems problem that organizations must grapple with is systems migration. Indeed, systems migration issues pertain not only to legacy systems but also to the adoption of newer technologies such as blockchain. Regardless of the technology concerned, migration is a significant challenge for all financial services organizations, one that typically entails a time-consuming, costly, and difficult process. How can organizations handle systems migration effectively? Are there specific methodologies that can help? Can technology play a role?
Another important area financial services organizations are focusing on at present is robo-advisors, and there is much discussion around their design, business models, and user adoption. One key question that remains to be answered is what is their operational value and the associated investment returns for users? Frankly, do these algorithms succeed in creating successful ROI margins in their selected portfolios? How do they perform in dynamic, volatile markets? Do they outperform existing (human) processes and methods?
Crowdfunding, the practice of funding a venture by raising small amounts of money from a large number of individuals, is typically performed via Internet-based intermediaries. Crowdfunding has received much attention in recent times, thanks to projects such as Oculus Rift, which received close to US $2.5 million in initial funding from investors on Kickstarter in 2012. Two years later, Oculus’s owners sold the company to Facebook for approximately $2 billion. The Oculus Rift case became somewhat controversial because of its implications for investor protection. As Guardian technology reporter Alex Hern asks, “Were the backers, who paid almost $2.5m, engaging in a purchase (in which case the risk of failed projects seemed overly high), an act of philanthropy (which seems undercut by a billion-dollar sale), or an investment (but one in which they don’t receive a share of the profits)?” Such controversies have very much put regulation of crowdsourcing in the spotlight. Should crowdfunding intermediaries be regulated? What should be the nature of such regulation? This is a critical topic for discussion in today’s multifaceted investor environment.
In This Issue
Speaking of crowdfunding, our first article — by Jack Smith, Joseph Feller, Rob Gleasure, Philip O’Reilly, Jerry Cristoforo, and Shanping Li — focuses on equity-based crowdfunding, an alternative source of financing for organizations and a possible key to overcoming small and medium-sized enterprise liquidity issues. Alternatives to bank financing have drawn increased attention in recent years, as the financial crisis has restricted the amount of capital available through traditional means. One major advantage of crowdfunding is that it can be both a faster and cheaper source of financing. However, there are risks associated with the practice, including the potential for investors to be provided with inaccurate information. Educating and informing both investors and fund seekers is an important aspect of the crowdfunding process, and regulation will play an important part in this. Smith et al.’s research suggests that “equity crowdfunding regulations need to be specific and unique to this emerging investment mechanism; such platforms cannot be covered by existing investment regulations.” Indeed they note that managing equity crowdfunding risk requires a specific set of regulations, making the important point that markets should not be overregulated from the start. Any regulations should ensure that the diversity of the crowd is maintained, a critical success factor in the context of equity crowdfunding. The authors note that “regulators and government departments seek to achieve a delicate balance between regulation for the safe participation of all involved and preservation of the unique investment environment that equity crowdfunding creates. Regulators and government departments are aware of how novel equity crowdfunding is and are cautious not to overregulate the market, which could kill it off completely.”
As we observed last month, it seems that mainframe legacy systems will always be with us. This is a problem both in terms of increased operating expense and human capital — young people have little interest in learning procedural languages, and thus there are fewer and fewer people available to maintain these often mission-critical applications. While re-platforming COBOL in Linux or cloud containers might seem like the easiest fix, it doesn’t address the problem of the dwindling talent supply. The only real solution is migrating mainframe systems to a modern technology stack, typically an expensive and time-consuming proposition. In our second article, Albert Ma tells us about BlueMorpho, a joint research project of InSigma Hengtian Software and Zhejiang University that uses machine intelligence and a new ontology-based methodology to “make the migration effort much more efficient and effective.” While Ma acknowledges that BlueMorpho can’t “automate the entire process flawlessly ... [w]hat it can do is to optimize cost savings and improve agility in migrating systems to a modern platform.”
In last month’s CBTJ, Jie Yang, Hanxi Ye, Yadan Wei, and Linqian Bao discussed robo-advisors, online platforms that use sophisticated algorithms to provide automated management of investment portfolios. In this issue, Yang et al. introduce Alpha UMa, the robo-advisor they created to help retail investors in China make sound investment decisions. They detail how Alpha UMa goes about selecting asset classes and making automated, threshold-driven trades, balancing the pursuit of high returns with the need to keep transaction costs low. While Nobel Prize winners and Harvard economists alike warn that the typical retail investor is unlikely to beat average market returns for very long, “Alpha UMa uses quantitative methods to generate views” that repeatedly yield above-market returns. Indeed, the authors note, “Our simplified portfolio has an annualized return of more than 10%, which is a very good result in a turbulent market.”
With so much money riding on the accuracy of algorithms, you can bet that the financial services industry is concerned about the quality of its software. High-quality systems require rigorous testing, which is the subject of our fourth contribution. In the article, Xiaochun Zhu and Shanping Li cite research that claims “product reliability will be better if independent test organizations conduct testing,” which leads to their focus on test outsourcing. In looking at the subject, the authors found that “despite the growing interest in outsourcing in general and test outsourcing in particular, there has been no study that comprehensively investigates the types, processes, and challenges of test outsourcing.” Fortunately, they’ve rectified this omission with their empirical study of test outsourcing at Insigma Technology, China’s second-largest IT outsourcer. Through interviews and a quantitative survey, Zhu and Li identify the challenges and pinpoint the success factors in test outsourcing, making it easier for client companies to reap the benefits and avoid the pitfalls of this widespread practice.
In our final article, Zhou Li and Jianling Sun discuss the application of machine learning in the context of account reconciliation. The reconciliation process is critical to ensuring the completeness and accuracy of company accounts and likewise ensuring that organizations comply with various international accounting standards and principles (e.g., US GAAP). Li and Sun’s research illustrates the efficiencies that can be realized through utilizing machine learning to reconcile accounting rules, resulting in reduced costs and less time spent on the onerous reconciliation process.
To sum up, in this issue we learn that:
Regulation can contribute to equity crowdfunding success, but new regulations must be aligned with the principles of this novel form of financing.
A combination of machine intelligence and an ontology-based methodology can greatly facilitate efforts to migrate legacy systems to modern platforms.
Robo-advisors can play a vital role in asset selection and provide an above average ROI in a multi-asset portfolio invested in a rapidly evolving market.
Test outsourcing can help deliver the high-quality software financial services firms depend on, and there are key success factors organizations need to consider to achieve this outcome.
Machine learning can be applied to the accounting reconciliation process, thereby providing financial services companies with significant cost efficiencies and reducing the time they spend on this essential task.
The research articles in this special issue of CBTJ advance the state of the art of fintech knowledge and provide detailed insights for financial services organizations that wish to gain an understanding of the ways technology can create value for them. They also underscore the benefit of establishing partnerships between leading-edge financial services firms and universities to create new knowledge and lead the fintech revolution.