Administración Estratégica de Empresas (Dr.)

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    Location-allocation problem for banking correspondent services : the colombian urban market case
    (Pontificia Universidad Católica del Perú, 2017-03-02) Cardona Prada, Juan Carlos; Vincent, Charles
    Banking correspondents are a channel through which third parties operate on behalf of a bank, under a contract authorising the provision of some banking services. This model has been implemented extensively in developing countries, as a channel to increase financial inclusion by bringing financial products and services closer to marginalised populations. However, there is a lack of studies on the criteria employed by banks when selecting retailers to turn into banking correspondents (BC), in turn preventing the channel from offering a service portfolio adequate to the capacities of the retailers providing this kind of services, affecting the profitability and sustainability of the channel. The current research parted from the agency theory, which allowed to understand the relationship between the parties involved in the delivery of BC services, seeking to boost financial inclusion in Colombia through the development of the BC channel by solving the problem of location and portfolio allocation for retailers acting as banking correspondents in Colombian urban zones. It parted from the case of Bogota, where improvements were achieved in the selection of retailers and portfolio allocation, thus enhancing the relationship between agents, allowing banks to select banking correspondents and allocating them a particular service portfolio, while transaction volumes and channel profits are maximised. This was done through the development of a methodology comprising five stages, namely: (a) the development of a taxonomy on network integration models and financial services; (b) the development of a taxonomy on the strategies of small and medium retailers that could be selected as banking correspondents; (c) the validation of both taxonomies through cluster analyses; (d) validation of the resulting classifications through an ANOVA and a Kruskal-Wallis H test; and (e) the elaboration of a chance-constrained programming model that uses the elements built and validated in the formers stages. A classification of retailers was obtained from factors related to their operational and business strategies, as well as a classification of banking correspondents based on their service portfolios. It was also noted there is a significant relationship between the groups from both classifications, which led to the chance-constrained programming model being run on a sample of retailers in Bogotá, located at the borough of Suba. The model enabled to select those retailers best suited to become banking correspondents, determining the number of transactions according to their constraints in terms of retailer capabilities, banks and the environment, while estimating the expected income from these banking correspondent operations
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    An internal fraud model for operational losses : an application to evaluate data integration techniques in operational risk management in financial institutions
    (Pontificia Universidad Católica del Perú, 2017-03-02) Paredes Leandro, Rocío Margaret; Vincent, Charles
    The handling of external operational loss data by individual banks is one of the longstanding problems in risk management theory and practice. The extant literature has not provided a method to identify the best way to combine internal and external operational loss data to calculate operational risk capital. Hence, to improve the knowledge and understanding of internal-external data combination in operational risk management, this study applied a simulation-based evaluation of well-known data combination techniques such as the scaling, the Bayesian, and the covariate-base techniques. This research considered operational losses arising from internal fraud in retail banking within a group of international banks that share data through an operational loss data exchange. One of the key elements of the simulation-based statistical evaluation was the development of a dynamic internal fraud model for operational losses in retail banking. The internal fraud model incorporated human factors such as the number of employees per branch and the ethical quality of workers. It also included the extent of risk controls set by bank managers. There were two sets of findings. First, according to the simulation-based evaluation, the scaling technique was by far the less useful for estimating the appropriate operational risk capital. The Bayesian and the covariate-based techniques performed best. The Bayesian technique was the best for higher percentiles while the covariate-based technique was the best at not so extreme quantiles. The choice of technique therefore depends on the risk appetite of the financial institution. The second set of findings relates to the model validation with hard data. Losses generated by the model in the banks across the world were associated with GDP growth and the corruption perception of the country where banks were located. In general, internal fraud losses are pro-cyclical and the corruption perception in a country positively affects the occurrence of internal fraud losses. When a country is perceived as more corrupt, retail banking in that country will feature more severe internal fraud losses. To the best of knowledge, it is the first time in the operational risk literature that this type of result is reported