Consumer finance: challenges for operational research

Consumer finance has become one of the most important areas of banking, both because of the amount of money being lent and the impact of such credit on global economy and the realisation that the credit crunch of 2008 was partly due to incorrect modelling of the risks in such lending. This paper reviews the development of credit scoring—the way of assessing risk in consumer finance—and what is meant by a credit score. It then outlines 10 challenges for Operational Research to support modelling in consumer finance. Some of these involve developing more robust risk assessment systems, whereas others are to expand the use of such modelling to deal with the current objectives of lenders and the new decisions they have to make in consumer finance. <br/

Operations research in consumer finance: challenges for operational research

Consumer finance has become one of the most important areas of banking both because of the amount of money being lent and the impact of such credit on the global economy and the realisation that the credit crunch of 2008 was partly due to incorrect modelling of the risks in such lending. This paper reviews the development of credit scoring,-the way of assessing risk in consumer finance- and what is meant by a credit score. It then outlines ten challenges for Operational Research to support modelling in consumer finance. Some of these are to developing more robust risk assessment systems while others are to expand the use of such modelling to deal with the current objectives of lenders and the new decisions they have to make in consumer financ

Multi-Objective Approaches to Markov Decision Processes with Uncertain Transition Parameters

Markov decision processes (MDPs) are a popular model for performance analysis and optimization of stochastic systems. The parameters of stochastic behavior of MDPs are estimates from empirical observations of a system; their values are not known precisely. Different types of MDPs with uncertain, imprecise or bounded transition rates or probabilities and rewards exist in the literature. Commonly, analysis of models with uncertainties amounts to searching for the most robust policy which means that the goal is to generate a policy with the greatest lower bound on performance (or, symmetrically, the lowest upper bound on costs). However, hedging against an unlikely worst case may lead to losses in other situations. In general, one is interested in policies that behave well in all situations which results in a multi-objective view on decision making. In this paper, we consider policies for the expected discounted reward measure of MDPs with uncertain parameters. In particular, the approach is defined for bounded-parameter MDPs (BMDPs) [8]. In this setting the worst, best and average case performances of a policy are analyzed simultaneously, which yields a multi-scenario multi-objective optimization problem. The paper presents and evaluates approaches to compute the pure Pareto optimal policies in the value vector space.Comment: 9 pages, 5 figures, preprint for VALUETOOLS 201

The Potential of Learned Index Structures for Index Compression

Inverted indexes are vital in providing fast key-word-based search. For every term in the document collection, a list of identifiers of documents in which the term appears is stored, along with auxiliary information such as term frequency, and position offsets. While very effective, inverted indexes have large memory requirements for web-sized collections. Recently, the concept of learned index structures was introduced, where machine learned models replace common index structures such as B-tree-indexes, hash-indexes, and bloom-filters. These learned index structures require less memory, and can be computationally much faster than their traditional counterparts. In this paper, we consider whether such models may be applied to conjunctive Boolean querying. First, we investigate how a learned model can replace document postings of an inverted index, and then evaluate the compromises such an approach might have. Second, we evaluate the potential gains that can be achieved in terms of memory requirements. Our work shows that learned models have great potential in inverted indexing, and this direction seems to be a promising area for future research.Comment: Will appear in the proceedings of ADCS'1

Managing Process Variants in the Process Life Cycle

When designing process-aware information systems, often variants of the same process have to be specified. Each variant then constitutes an adjustment of a particular process to specific requirements building the process context. Current Business Process Management (BPM) tools do not adequately support the management of process variants. Usually, the variants have to be kept in separate process models. This leads to huge modeling and maintenance efforts. In particular, more fundamental process changes (e.g., changes of legal regulations) often require the adjustment of all process variants derived from the same process; i.e., the variants have to be adapted separately to meet the new requirements. This redundancy in modeling and adapting process variants is both time consuming and error-prone. This paper presents the Provop approach, which provides a more flexible solution for managing process variants in the process life cycle. In particular, process variants can be configured out of a basic process following an operational approach; i.e., a specific variant is derived from the basic process by applying a set of well-defined change operations to it. Provop provides full process life cycle support and allows for flexible process configuration resulting in a maintainable collection of process variants

Automating joiners

Pictures taken from different view points cannot be stitched into a geometrically consistent mosaic, unless the structure of the scene is very special. However, geometrical consistency is not the only criterion for success: incorporating multiple view points into the same picture may produce compelling and informative representations. A multi viewpoint form of visual expression that has recently become highly popular is that of joiners (a term coined by artist David Hockney). Joiners are compositions where photographs are layered on a 2D canvas, with some photographs occluding others and boundaries fully visible. Composing joiners is currently a tedious manual process, especially when a great number of photographs is involved. We are thus interested in automating their construction. Our approach is based on optimizing a cost function encouraging image-to-image consistency which is measured on point-features and along picture boundaries. The optimization looks for consistency in the 2D composition rather than 3D geometrical scene consistency and explicitly considers occlusion between pictures. We illustrate our ideas with a number of experiments on collections of images of objects, people, and outdoor scenes

Emerging Perspectives on Self Service Technologies in Retail Banking

This paper attempts to critically examine the available literature on the subject, discuss a model that provides a managerial framework for analyzing the variables associated with customer value, and to identify potential research areas. The discussion draws conceptual impetus from new technologies in banking services through self service technologies in banking as a tool for optimizing profit. The discussion in the paper also analyzes the main criteria for successful internet-banking strategy and brings out benefits of e-banking from the point of view of banks, their technology and customer values and tentatively concludes that there is increasing returns to scale in the bank services in relation to the banking products, new technology and customer value.Self service technology, retail banking, customer value, profit optimization