Operations in Financial Services—An Overview (2 of 6)

1.2.6. Use of Intermediaries. This is an important aspect of the financial services industry. In some cases a direct-to-consumer approach is used (credit cards); in other cases most of the customer facing work is done by intermediaries (financial advisors, insurance agents, annuity sales through banks, etc.); and in still other cases the firm’s employees and its agents have to collaborate with one another (insurance). Working through an intermediary entails a set of issues not normally seen in other services that function without intermediaries. For example, financial product and service design and delivery get filtered through the prism of what the agent feels is in his or her own best interest. At times, the relationship between the firm and the intermediary is not exclusive, hereby adding a layer of complexity because the customer may choose between products from competing firms. Therefore, what gets planned in the corporate offices of the financial services firms and what is seen by the customer may be quite different. The operations management literature, to our knowledge, has not paid attention to product and service design in such situations, because the implications on customer lifetime interactions with the firm go much beyond initial pricing, product features, and the inventory of brochures left with the agents.

1.2.7. Convergence of Operations, Finance, and Marketing. There is probably no other industry where this convergence is more pronounced. These functions are supported and enabled by a healthy dose of statistics, technology, and optimization. By focusing only on back-office operations such as call centers, researchers in service operations are leaving a lot on the table. There is very little research in the service operations literature that leverages this convergence, which requires a choreography, as described by Voss et al. (2008), who put it in a more limited context of operations and marketing. For example, the client acquisition process in full-service retail brokerage and investment advisory firms begins at the corporate level, where it draws resources from marketing, strategy, information technology, and operations, and is ultimately implemented through the sales force of brokers/ financial advisors. Customer acquisition at a credit card company is a competitive differentiator and a complex process focused on direct mail campaigns. At many large firms, the budgets for direct mail run into several hundred million dollars annually. By focusing on the billing mailroom, collections, call centers, and billing call centers, researchers in service operations are working on a problem akin to quality inspectors at the end of the production line—by then it is too late, the volumes of mail and calls are baked in during the mailing campaign creation, while their skills could have made themailingsmoreeffective andtargeted(giventhe minuscule response rates), resulting in fewer delinquent accounts (requiring fewer outbound collection calls), and perhaps also fewer billing calls to inbound call centers.

At a more sophisticated level, very few credit card firms use contact history in mailing solicitations, which may result in repeated mailings to chronic non-responders. The managers developing campaign strategies may not have the analytical background that a researcher in service operations can bring to bear, and the cycle time for campaign creation is typically so long and complicated that much attention gets expended on scoring for credit and response, file transfers from credit bureaus and data vendors, scrubbing of data, etc. These complicated processes leave little time to incorporate experience from a previous mailing because a reading of the results of that mailing takes time (prospective customers may not respond immediately, even if they do respond), and file structures may not have been designed to carry information about previous contacts and the response to them.

Another indication of this convergence is that the majority of the undergraduate and MBA hiring at an investment bank in the greater New York City area from one of the region’s business schools is in the COO’s operation, whether the student concentrations are in finance, marketing, information systems, or operations.

The foregoing does not imply that no significant work has been done in the research on financial service operations, just that areas of work have had a narrow focus. The purpose of this article and this special issue is to begin to expand that focus and encourage research in neglected or emerging areas in financial service operations. We will survey existing research next, not only where the attention is only on financial service operations, but also where research in service industries in general has substantial application in financial service operations. In Appendix A, we provide an overview of the various operations processes in financial services and highlight the ones that have been addressed in operations management literature.

This survey paper is organized as follows. Sections 2 through 9 go over eight research directions that are of interest from an operations management point of view. The first couple of sections consider the more general research topics, whereas the later sections go into more specific topics and more narrowly oriented research areas. Section 2 focuses on process and system design in financial services, while section 3 considers performance measurements and analysis. Section 4 deals with forecasting, because forecasting plays a major role in virtually every segment of the financial services industry. The next section focuses on cash and liquidity management; this section relates cash management to classic inventory theory. Sections 6 and 7 deal with waiting line management and personnel scheduling in retail banking and in call centers. Even though these two topics are strongly dependent on one another, they are treated separately; the reason being that the techniques required for dealing with each one of these two topics happen to be quite different from one another. Section 8 focuses on operational risk in financial services. This area has become very important over the last decade and this section describes how this area relates to other research areas in operations management, such as total quality management (TQM). Section 9 considers product pricing and revenue management issues. The last section, section 10, presents our conclusions and discusses future research directions.


Service systems design has attracted quite a bit of attention in the academic literature. It is clear that service design has to be as rigorous an activity as product design, because the customer experiences the service first hand, much like a product, and comes away with impressions regarding the quality of service. Although the quality of service delivery depends on a number of factors, such as associate training, technology, traffic, neighborhood customer profile, access to the service (channel access), and quality of resource inputs, the service experience gets baked into the process at the time of the service design itself, and therefore a proper service design is fundamental to the success of the customer experience.

2.1. Aspects of Service Design

Service research has usually focused on capacity management (type of customer contact, scheduling, and deployment) and the impact of the response to variability on costs and quality. For long the nature of customer contact has influenced service design thinking by creating front-office/back-office functions (Sampson and Froehle 2006, Shostack 1984). Shostack also pioneered the use of service blueprinting for identifying fail points where the firm may face quality problems. She illustrated this methodology for a discount brokerage and correctly identified that many of the operational processes are not seen by the customer; she then focused on the telephone communication step, the only one with client contact. This focus on client contact tasks, whether in the front office or in the back office, is widespread in services research in general and in research on financial services operations in particular. One reason may be that service researchers have found it necessary to motivate their work by differentiating services from products (whether it is service marketing vs. product marketing, or service design vs. product design), and client contact is an obvious differentiator.

NYU Masters in Risk Management

From the outset, it has been clear that service processes are subject to a significant amount of randomness from various sources. Frei (2006) discusses the various sources of randomness in service processes and how firms react to them in the design of their services. She identifies five types of variability— customer arrival variability, request variability, customer capability variability, customer effort variability, and customer preference variability. She states that firms design services to factor in this variability by trying either to accommodate the variability at a higher cost (cross training of employees, increased automation, variable staffing) or to reduce the variability with a view to increasing efficiency rather than cost (off peak pricing, standard option packages, combo meals).

2.2. Focus on Single Encounters

Much of the services literature, however, focuses on single service encounters, which are common in services such as fast food. Even if a customer repeatedly visits the same restaurant, there is not the kind of stickiness to the relationship as can be found in financial services. Retail banking seems to have attracted the most attention among financial services with respect to service design, but here again the focus is on disparate single visits to the branch or Automated Teller Machine (ATM), rather than as part of a life cycle of firm–customer interactions. Other than meeting the branch manager when opening an account, there is usually no other recognition of the stage of the relationship in the delivery of service. Perhaps this will change with time as more firms start experimenting with their service delivery design as Bank of America has been doing (Thomke 2003).

2.3. Descriptive vs. Prescriptive Studies of Financial Services

Several descriptive studies have focused on retail banking (Menor and Roth 2008, Menor et al. 2001), substitution of labor with information technology (Fung and Fung 2008), the use of customer feedback to improve customer satisfaction (Krishnan et al. 1999), the use of distribution channels (Lee et al. 2004, Xue et al. 2007), self-service technologies (such as ATMs, pay at the pump, see Campbell and Frei 2010a, b, Meuter et al. 2000), online banking (Hitt and Frei 2002), and e-services in general (see Boyer et al. 2002, Ciciretti et al. 2009, Clemons et al. 2002, Furst et al. 2002, Menor et al. 2001). These studies talk about the types of customers who use the various different channels and how firms have diversified their delivery of services using these new channels as newer technologies have become available. However, they are usually descriptive, rather than prescriptive, in that they speak about how existing firms and customers have already adopted these technologies, rather than what they should be doing in the future. For example, there are few quantitative metrics to measure a product (e.g., its complexity vis-a-vis customer knowledge), a process (e.g., face to face vs. automated), and proximity (on-site or off-site) to help a manager navigate financial service operations strategies from a design standpoint based on where her firm is now. In that sense, financial service system design still has ways to go to catch up with product design (product attributes, customer utility, pricing, form and function, configuration, product development teams, etc.) and manufacturing process design (process selection, batch/line, capacity planning, rigid/flexible automation, scheduling, location analysis, etc.). Because batching and lot sizing issues have been of considerable interest in the history of the study of manufacturing processes, and because online technologies have made the concept of batching considerably less important, it would be interesting to see how research in service systems design unfolds in the future. One paper with prescriptive recommendations for service design in the property casualty insurance industry is due to Giloni et al. (2003).


3.1. Best Practices and Process Improvement

Many service firms are measuring success by factors other than profitability, using such factors as customer and employee loyalty, as measured by retention, depth of relationship, and lifetime value (Heskett et al. 1994). Chen and Hitt (2002), in an empirical study on retention in the online brokerage industry, found that ease of use, breadth of offerings, and quality reduce customer attrition. Balasubramanian et al. (2003) find that trust is important for online transactions, because physical appearance of branches, etc. no longer matter in such situations. Instead, perceived environmental security, operational competence, and quality of service help create trust.

In general, service quality is difficult to manage and measure because of the variability in customer expectations, their involvement in the delivery of the service, etc. In general, there may be two different measures of service quality that are commonly used: the first refers to and measures the actual service provided (e.g., customer satisfaction, resolution, etc.), the second may refer to the availability of service capacity/personnel (e.g., service level, availability, waiting time, etc.). The first type of quality measure is not as nebulous in financial services where the output is generally related to monetary outcomes. If there is an error in the posting of a transaction, or if quarterly returns from a mutual fund are below industry performance, there is an immediate customer reaction and the points in the service design that caused such failures to occur is apparent, whether it is in remittance processing or in the hiring of a fund manager. Quality in financial services is not influenced by such matters as the mood of the customer, as may be the case in other services. This makes ensuring quality in financial services more doable and one of the foci of the research in operational risk management which we will discuss later.

Roth and Jackson (1995) found that market intelligence and imitation of best practices can be an effective way of improving service quality, and that service quality is more influenced by service process choices and the cumulative impact of investments than by people’s capabilities. Productivity measurement in services is also a challenge (Sampson and Froehle 2006). Bank performance as a result of process variation has been studied by Frei et al. (1999).

This current special issue of Production and Operations Management provides some interesting new cases of process improvement in financial services. The paper by Apte et al. (2010), “Analysis and improvement of information-intensive services: Evidence from insurance claims handling operations,” presents a classification of information-intensive services based on their operational characteristics; this paper proposes an empirically grounded conceptual analysis and prescriptive frameworks that can be used to improve the performance of information-and customer contact-intensive services. The paper by De Almeida Filho et al. (2010) focuses on collection processes in consumer credit. They develop a dynamic programming model to optimize the collections process in consumer credit. Collection processes have been the Cinderella of consumer lending research, because psychologically lenders do not enjoy analyzing their mistakes, and also once an accounting loss is ascribed to a defaulted loan, there had been little incentive for senior managers to keep track of how much will be subsequently collected. The paper by Buell et al. (2010) investigates why self-service customers are more reluctant to change their service provider. This paper’s primary contribution is to investigate how satisfaction and switching costs contribute to retention among self-service customers. This is a particularly important issue in the financial services industry where considerable investments have been made in developing self-service distribution channels, and migrating customers to them.

3.2. An Example of Best Practices: Asset Management

Asset management provides an interesting example of an area within the financial services sector that has been receiving an increasing amount of research attention with regard to best practices from various operations management perspectives. The body of research on operations management in asset management is growing, however, not always produced by operations management researchers, but often by those in the finance world (Black 2007, Brown et al. 2009a, b, Kundro and Feffer 2003, 2004, Stulz 2007), who examine operational risk issues in hedge funds. A collection of operations management research papers in asset management can be found in a recent book by Pinedo (2010). Alptuna et al. (2010) present a best practices framework for the operational infrastructure and controls in asset management and argue that it is possible to effectively implement such a framework in organizations that enjoy a strong, principle-based governance. They examine conditions under which the cost-effective strategy of outsourcing asset management operations can be successful for asset managers and their clients. Figure 1, which has been adapted from Alptuna et al. (2010), shows the multiple constituent parts that must work together in order for a typical asset management organization to function effectively. Figure 2, also adapted from Alptuna et al. (2010), lists the functions in the investment management process according to their distance from the end client. Typically, the operations-intensive functions reside in the middle and back offices; accordingly, the untapped research potential of operations in asset management must be sought there. One can create a similar framework, as shown in Figures 1 and 2, for a typical retail bank, credit card issuer, mortgage lender, brokerage, trust bank, asset custodian, life or property/casualty insurer, among others, none of which is less complex than an asset manager. Outsourcing operations adds to the complexity by introducing elements of quality control for outsourced pieces and coordination between the main organization and the third-party provider (State Street 2009). To develop their framework, Alptuna et al. (2010) draw heavily on asset management industry resources on best practices, namely the Managed Funds Association’s Sound Practices for Hedge Fund Managers (2009), the Report of the Asset Managers’ Committee to the President’s Working Group on Financial Markets (2009), the Alternative Investment Management Association’s Guide to Sound Practices for European Hedge Fund Managers (2007), and the CFA Institute’s Asset Manager Code of Professional Conduct (2009).

Figure 1: Typical Structure of an Asset Management Organization


Figure 2: Investment Management Process Functions


Schneider (2010) provides a framework for asset management firms to analyze their costs. Arfelt (2010) proposes an adaptation of the Lean Six Sigma framework used in automobile manufacturing for asset management. Biggs (2010) advocates a decentralization of risk management, accountability as well as technology and expense control in asset management firms. Cruz (2010) argues that the focus of cost management programs at asset management firms should be strategic and tactical (see also Cruz and Pinedo 2009). Nordgard and Falkenberg (2010) give an IT perspective on costs in asset management. Campbell and Frei (2010a) examine cost structure patterns in the asset management industry. Amihud and Mendelson (2010) examine the effect of transaction costs on asset management, and study their implications for portfolio construction, fund design, trade implementation, cash and liquidity management, and customer acquisition and development strategies.

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Emmanuel D. (Manos) Hatzakis, Suresh K. Nair, and Michael Pinedo


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