What crucial trends are driving the industry?
In my opinion, the major current trends are continuations of the issues that have driven the industry over the past few years.
The reasons behind regulatory reform following the financial crisis, namely higher transparency for end-investors and risk mitigation for both the buy- and sell side, are still being addressed. It can be argued that the regulations themselves were developed largely based on the need for reform with less thought on the methods for implementation and compliance.
However, the issues of investor confidence and systemic risk were highlighted. Whether or not these new regulations are repealed or tempered in the future – such as Dodd-Frank in the US – banks and asset servicers should continue to develop best practices around increasing transparency and decreasing credit and operational risk. By doing this, opportunities for new and improved value-added services may be established, as well as a reduction of operational costs as more automation is introduced into what were traditionally considered manually intensive operational procedures. The industry should proceed as if full compliance with the regulations is firmly in place.
Addressing big data in the financial industry is another continuing trend. As in psychoanalysis, identifying the problem is the first step, and when it comes to data, this has, at least, been accomplished. Not only have financial firms realized the vast amount of data that regularly comes into their organizations but they have also found that much of it is duplicated. In larger firms, there may be separate licenses for the same data across the enterprise. Many firms have gone through the exercise of reviewing how that data is being used by various departments and entities. Some have even made the effort to source its own data. Take, for example, the initiative formed by J.P. Morgan, Goldman Sachs, and Morgan Stanley to jointly create their own reference data company, SPReD. Using this consolidated data, the industry is developing new ways to use it. Much like the fields of science and marketing, the financial industry will continue to build applications for predictive analytics and data curation, creating opportunity and streamlining operations.
While outsourcing has been around for quite a while, the use of the cloud and SaaS models in the financial industry will expand the availability of these infrastructures. The security of the cloud no longer seems to be in question. Some hedge funds have opted to place their operations, including positions and trading information, to third-party SaaS providers. There was a time when this would be unheard of, as that information was considered vital (and highly secretive) to a hedge fund’s strategy.
Another major trend is the emergence of cryptocurrencies, now going into its second generation. The adoption of Bitcoin as a currency/commodity in various markets, in spite of its sometimes volatile track record, is an example of this growing trend. The database that tracks the Bitcoin trades, blockchain, is a disruptive technology in itself. Initially, the currency avoided the use of banks, thereby escaping the scrutiny of regulators. However, as more financial firms start to trade and hold positions in Bitcoin, regulators will be required to get involved. The security, stability, and speed of transaction of cryptocurrencies in general – and Bitcoin specifically – have yet to be fully addressed to the satisfaction of established markets.
What market segments will experience the most growth and why?
In addressing the trends, there is opportunity for all players, not only the buy- and sell-side firms, but for application and data solution providers. There are many start-up technology companies offering innovative solutions for risk analytics, integration, data mining, and support for alternative trading. This past year, the industry also witnessed consolidation as larger providers acquired niche development firms with innovative solutions, as well as established vendors, to bolster market share. Vendors of all sizes that offer advanced solutions in these areas should benefit from the growing demand.
The larger vendor firms are also offering managed services platforms with broader functionality, running on traditional as well as SaaS environments. The market for outsourcing and Business Processing Outsourcing (BPO) services should continue to expand. According to a study by Broadridge Financial Solutions, “Charting a Path to a Post-Trade Utility”, outsourcing core post-trade processing could reduce a financial firm’s operational cost by 20% to 40%, and overall, could save the industry up to $4B annually. As evidence of this growing market, it was announced this past August that FIS, one of the largest outsourcers of financial processing, acquired the financial solution provider, SunGard, bolstering not only the former’s market share but expanding its scope of product offerings that could eventually be ported to a hosted platform.
In the area of data, another large acquisition this past year is indicative of the market potential and increased activity in information delivery and processing. Intercontinental Exchange (ICE), a firm that operates a global network of exchanges and clearing houses, acquired financial data provider, Interactive Data Corporation, for a reported $5.2B. Given the exploration by financial firms in developing new methods for how data is utilized, acquisitions and consolidation within the data provider segment should continue into the near future.
What are the key challenges?
If certain financial regulations are not enforced or are retracted, financial firms should continue their efforts to reduce risk and increase investor transparency as if compliance was required. It has been shown that the amount of disclosure to the investor is in proportion to market efficiency, as well as the performance of individual stocks. Proceeding with compliance, whether mandated or not, will be a challenge in itself. Regarding internal and systemic risk, building necessary functionality within applications benefits the industry overall. On the technology side, this requires improved design for risk processing, including the introduction of new weighting factors, automated analysis of historical trends, and interrogation of data across disparate sources. To address transparency, a secure infrastructure would have to be established in order for investors to access additional information.
In dealing with disparate data sources, integration is key. There are many start-up technology firms who offer innovative integration utilities. Some of these employ an “anything in/anything out” approach that can assist organizations in mapping sources into a single, normalized layout. However, there is also something to be said for standards. ISO 20022, for example, uses an XML-based methodology to not only design a standard format but to also build a global set of business-based terms and logic. Take-up of the ISO 20022 approach can be seen in global and domestic payments, securities operations, and trade finance applications and will continue to expand into other financial processing areas.
When considering outsourcing its operations, a financial firm must obviously perform its due diligence. Typical exercises such as cost-benefit analysis, reporting procedures, regulatory compliance, end-user access, are standard. When selecting a vendor, a firm should not only ensure that the proper certifications are in place, but that all the required functionality is offered. Beyond functionality, integration across various operational processes should be reviewed. Some outsourcing vendors have the depth of functionality but not all have the proper level of integration across applications.
The introduction of new currencies, such as cryptocurrencies, requires flexible data models that can be expanded to create new elements such as positions, update client static details, and populate enterprise-wide reporting. Since the introduction of the Euro, many core applications have this flexibility. However, cryptocurrencies, with their current lack of regulation, non-traditional payment protocols, and extremely high levels of volatility, have unique requirements beyond those of globally-accepted currencies. Flexible data models are also useful when developing new risk models and normalizing data across disparate sources.
