AUTOMATED RETAIL DERIVATIVES PLATFORMS: challenges and opportunities
The retail derivatives industry faces the same challenges seen in many mature financial markets: slow growth, heightening competition, increasing regulatory requirements and demanding clients. In this article, Stefan Naumann, Patric Mayer and Roger Waldhausen discuss how the automation of product platforms can help banks proactively maintain and expand their market share and highlight the different options to get there.
During the last several years, the market for retail derivatives in central Europe has been in turmoil. In the early days, structured products, also known as certificates, were highly successful, sold well and provided high margins to the issuing banks. Because the products offered liquidity to the banks and were used for funding purposes, they attracted more financial institutions to the market, leading to a wider variety of products, increased competition and smaller margins. During the financial crisis, the situation worsened. Being bearer bonds, the redemption of retail derivatives not only depended on general product characteristics, but also on the solvency of the issuing bank. For a long time, this was a theoretical issue until the collapse of Lehman Brothers—an important issuer of certificates. Because of public guarantees, rescue packages for the too-big-to-fail banks and several transparency initiatives, the industry managed to gain back the trust lost by investors.
Today, with a combined market volume of roughly €230 billion in Germany, Switzerland and Austria and more than 1 million different products in Germany,1,2,3 certificates are still an important source of liquidity to issuing banks—and the competition remains stiff. In today’s post-crisis environment, banks must now adhere to a growing number of regulations. Faced with these regulatory issues, increased competition and specific client needs requiring a broad and up-to-date range of products, the leading issuing banks began to automate their certificate workflows. As shown in Figure 1, the typical life cycle of a structured product consists of five phases: idea generation, structuring/pricing, issuing, hedging and life cycle events.
The life cycle of a new product begins with idea generation. When the basic idea of the product, such as its payout structure, is known, the product characteristics are further narrowed down by replicating the planned payout structure with the appropriate option and/or bond components. And, pricing is based on these components. During pricing, there is still room for minor changes to the product parameters (for example, barrier or strike levels) in order to best meet client or market needs. After the structuring and pricing is completed, the parameters are forwarded and entered into the legal, position keeping and custodian systems in order to reflect the product from a legal and economic perspective. As soon as the product is sold, the respective positions are booked into the systems and traders hedge the risks of the product. During the lifetime of the product, these hedges might need to be adjusted due to changing open interest in the product, varying market conditions, etc. Additional life cycle events could include (depending on the product type) barrier events, corporate actions of the product’s underlying(s), early exercises/assignments and (regular) expiries, as well as clearing and settlement. Continued reconciliation of static data from issue date during life cycle events to product expiry helps to maintain global data consistency across all systems (legal, position, custodian, external, etc.).
THE NEED FOR AUTOMATION
In the past, banks used manual processes, which can be slow, redundant and inconsistent in terms of quality, to manage each phase of a structured product’s life cycle. This put the bank at risk and also limited its ability to offer a large variety of products. To improve their competitiveness, the early movers in the industry began to automate parts of the product life cycle where processes were recurring. Structured products often only differ in a few attributes (like the yield or underlying), making them well suited for automation. In a market with over 1 million products, speed is critical.4 An efficient process yielding significant economies of scale can only be realized by automation—particularly in a fast-changing market environment with savvy clients who demand a broad range of products with attractive prices. In addition to reducing risk and minimizing the chance for human errors, automation also helps firms improve service quality and better address regulatory requirements.
THE BUSINESS IMPACT
Not only does automation help firms establish a competitive advantage, it also gives a firm’s employees more time to engage in new tactical and strategic business initiatives—time otherwise lost to manual processes and monitoring. Today, there are several examples of how automation is applied to the product life cycle:
- Idea generation, structuring and pricing is automated via web platforms where investors can customize and price their own products
- Issuing is automated by uploading static data into all relevant legal, position keeping and custodian systems
- Hedging can be automated by automatically netting and closing occurring delta, gamma or vega positions; some banks also choose to automatically sell occurring greek/option risks via inter-bank platforms and only keep the bonds in their books
- Life cycle events are streamlined by automated barrier event bookings, corporate action adjustments and expiry bookings
Firms can maximize benefits by fully automating the entire life cycle process. While first movers have an advantage, the leading banks are already closing the gap by automating their product workflows.
The existing level of automation is reflected in the total number of products, which has grown to well above 1 million over the last couple of years. In contrast, market volume tends to stagnate at around €100 billion in Germany5 and €120 billion in Switzerland6, which are by far the biggest markets. In Germany, the largest four players account for roughly 60% of this open interest. This is bad news for firms who are slow to automate and smaller players in a stagnating market. A competitive advantage will be established by the banks with the best distribution networks coupled with automated workflows. Unfortunately, the relative value of automation, especially for the late movers, drops. When the competition is already automated, becoming so no longer gives a firm an advantage; it merely puts that firm on the same plane. Thus, for the slower and smaller players, the window of opportunity is closing fast.
Automation requires an initial investment as well as ongoing service investments to maintain the underlying IT infrastructure. If a bank automates, it should do so for all areas of the life cycle in order to avoid new bottlenecks and interruptions in process flow. For example, if the life cycle steps referenced in Figure 1 were automated from idea generation to hedging, a bank would be able to initially sell a large volume of products. However, during the products’ lifetime, capacity issues might occur if too many of these products were subject to simultaneous barrier hits due to larger price movements in the underlying instruments. Automation makes the most sense if the bank is willing to increase the product range and—most importantly—is able to sell this increased portfolio to the market. For players in the certificates business that are not at least partially automated right now, this might be the last chance for change.
IN-HOUSE DEVELOPMENT VS. STANDARD SOFTWARE
If a bank decides to automate its workflow, one of the most important questions it faces is: build or buy? The answer to this simple question has far-reaching consequences for the company in terms of costs, incremental revenue and more.
In-house development is tailored to the needs of the company—with functions developed and integrated specifically for the bank. In contrast, standard software is built to accommodate a broad spectrum of functionalities, e.g., reporting, documentation and settlement. In-house software is independent and allows the owner to decide where and when to enhance the software, whereas, a vendor could stop the development of its software at any time. The maintenance of new functions in off-the-shelf software requires time and is not as flexible as home-grown systems. With in-house software that is closely aligned to business operations, companies are able to differentiate themselves from other market participants and create a competitive advantage.
On the other hand, disadvantages of in-house software include development costs which vary depending upon system complexity. Unplanned issues and problems during the project are difficult to estimate and can greatly affect the timeline. Plus, with in-house development, banks become more reliant on their employees and their specialized knowledge of the software.
Standard packages can be lower in cost than software developed in house. In addition, standard software for structured products is very flexible, allowing banks to adapt the software and automate nearly every kind of product and workflow. Oftentimes, banks that purchase off-the-shelf packages incur lower costs and can go live sooner than with software developed in house. Standard industry solutions have a broad range of customers to help improve the quality of the software. Errors are often detected and remediated quickly, enabling the vendor to provide better software. And the cost for regular software improvements is spread across all clients.
In addition to these benefits, standard packages are fast to implement and flexible. This, combined with lower costs as compared to in-house development, is appealing to many banks. Even so, banks should still conduct a pilot study to ensure the packages meet their specific requirements and work with the firm’s infrastructure.
Increasing regulatory requirements, the clients’ demand for a broad and up-to-date range of products and heightened competitive pressures are the challenges that lie ahead for today’s banks. To address these challenges and enable business growth, automation is key. In order to automate, a make or buy decision must be made. Nowadays, standard software is able to automate most of the common product structures—and new structures are usually available through software updates. Also, data interfaces that can be used for regulatory reporting are often already included or can be added. Unless a bank is planning to do a high volume of very exotic product structures, standard software may be the best choice to not only overcome the challenges of the automated derivatives markets—but also to take the firm to the next level.
- Swiss Structured Products Association, “Market Report Structured Products Quarterly Report,” December 2013, p. 3
- Deutscher Derivate Verband, “The German Derivatives Market,” September 2013, p. 1
- Scoach by Six and Deutsche Börse, “Auf dem Prüfstand: Scoach-Zertifikate-Indizes und Scoach-Put/Call-Sentiment,” December 2012, p. 2
- Deutsche Derivate Verband, Market Volume, http://www.derivateverband.de/ENG/Statistics/MarketVolume
- Swiss Structured Products Association, “Market Report Structured Products,” Monthly Report, February 2014
is Director of Business Consulting based in Frankfurt and an investment banking professional with over 12 years of experience in the banking and stock exchange industry. Stefan is responsible for the structured product projects in GSA and has supplemented his expertise as a lecturer at Humboldt University Berlin, where he gives lectures in finance and capital markets.
is a Senior Associate of Business Consulting based in Frankfurt with more than seven years of automation experience in the derivatives sector. He has worked on numerous straight-through-processing (STP) projects for industry leaders in central Europe, covering futures, options, structured products and complex over-the-counter (OTC) deals.