Collaborative-demographic hybrid for financial: product recommendation

Internship Report presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced AnalyticsDue to the increased availability of mature data mining and analysis technologies supporting CRM processes, several financial institutions are striving to leverage customer data and integrate insights regarding customer behaviour, needs, and preferences into their marketing approach. As decision support systems assisting marketing and commercial efforts, Recommender Systems applied to the financial domain have been gaining increased attention. This thesis studies a Collaborative- Demographic Hybrid Recommendation System, applied to the financial services sector, based on real data provided by a Portuguese private commercial bank. This work establishes a framework to support account managers’ advice on which financial product is most suitable for each of the bank’s corporate clients. The recommendation problem is further developed by conducting a performance comparison for both multi-output regression and multiclass classification prediction approaches. Experimental results indicate that multiclass architectures are better suited for the prediction task, outperforming alternative multi-output regression models on the evaluation metrics considered. Withal, multiclass Feed-Forward Neural Networks, combined with Recursive Feature Elimination, is identified as the topperforming algorithm, yielding a 10-fold cross-validated F1 Measure of 83.16%, and achieving corresponding values of Precision and Recall of 84.34%, and 85.29%, respectively. Overall, this study provides important contributions for positioning the bank’s commercial efforts around customers’ future requirements. By allowing for a better understanding of customers’ needs and preferences, the proposed Recommender allows for more personalized and targeted marketing contacts, leading to higher conversion rates, corporate profitability, and customer satisfaction and loyalty

The Concept of the Cryptocurrency and the Downfall of the Banking Sector in Reflecting on the Financial Market

This paper aims to explain the concept of Cryptocurrencies such as Bitcoin, Litecoin and others, discuss their advantages and their disadvantages, and how is reflecting on the financial market and on the other currencies that are adopted in each country, like us dollar and the euro and the pound and so on (fiat currencies). This paper will discuss the major change that would occur if or when cryptocurrencies get adopted worldwide when the cryptocurrency becomes the who will benefit from this change and who will cease to exist, and what would this change mean to the banking sector, and where is it going to leave this sector. Could it destroy it or be a partner with it? It all depends on how this sector will handle this change when it happens because it will happen sooner or later

Competition in financial services

In the financial services sector, the failure of a single institution can have a compounding effect on the sector, and on national and global economies. In particular, there is systemic risk from inter-institution lending, and this effect is more complex in Australia due to the small number of major players. In retail banking in Australia, following a similar practice in most developed countries, if an unsecured creditor is a retail depositor, their deposit is insured by the government. That is, if a retail bank fails, the Federal Government will make the depositors whole. The regulatory system, particularly the prudential regulatory system, is designed to protect depositors’ and borrowers’ interests, and this protects the interest of the government. The effect is that regulatory policy on banking has prioritised stability in consideration of the sovereign risk associated with the risk of retail bank failure. However, this approach also creates a policy dilemma. The dilemma concerns the extent to which the retail banking sector can attain the benefits of the vigorous rivalry from effective and efficient competition, without unduly risking stability and the potential of a devastating call on the public purse. Specifically, in the context of effective and efficient competition, there is limited competitiveness in retail banking in Australia. This is reflected in the static state of market share between the four major banks, and very slow and marginal improvements gains even by strong second tier competitors. Furthermore, the retail banking sector’s capacity for product and service innovation is limited. Although the absence of vigorous rivalry is conducive to stability within the retail banking sector, it is likely to detract from the welfare of retail banking consumers. Furthermore, the level of innovation may not be as high as is feasible and barriers, including prudential regulatory barriers to entry or expansion, mean that the extent of rivalry is unlikely to change without some form of promotion of competition. The paper consequently makes a four-point recommendation for the removal of the ‘four pillars’ policy:  The four major banks are protected by an implicit government guarantee that impacts market operation with little observable benefit to consumers, and may be a source of consumer disutility.  The four pillars policy has prompted increased vertical integration within the sector, particularly in the area of mortgage products.  There are sufficient merger protections provided by Part IV of the Competition and Consumer Act 2010 (Cth).  Competition and contestability arise when there are reasonably low barriers to entry and exit from the sector. It is not clear that low barriers to entry exist in Australia, and evidence to support this view comes from the failure of international banks to gain a significant toehold in the retail banking sector in Australia. One deterrent to entry is the regulatory focus on the four pillars. The authors recognise that this position is at odds with the view of the Financial System Inquiry. However, the rationale in the report of the Inquiry was to prevent mergers, and the current competition law achieves this objective. The paper recommends two specific policies to promote competition in retail banking without the structural intervention that would otherwise be required to improve the intensity of competition in the retail banking sector:  Introduce bank account number portability. This would use ‘know your customer’ and central database systems in a similar form to those that have been used for mobile number portability in Australia for the last decade and a half.  Introduce customer access to data held by banks to allow third parties to compare bank offerings across all banks.  Significantly, these two recommendations are consistent with the productivity proposals issued by the UK Government in July 2015. The research paper also examines crowd equity funding as a disruptive force in the banking sector, and recommends that crowd equity funding be permitted with the following safeguards:  ASIC should take an active role in monitoring crowd equity funding and be willing to sue in case of fraudulent action.  Any intermediary online platform should have a financial services licence with limited duty of care.  There should be a cap for business raisings through crowd equity funding of $2 million in a 12-month period.  Crowd equity funding is a social phenomenon. Through its use of social media, it has attracted people who have previously never been interested in investing in companies. Instead of being feared, this interest should be nurtured through the promotion of investors’ financial education

Credit Scoring Using Machine Learning

For financial institutions and the economy at large, the role of credit scoring in lending decisions cannot be overemphasised. An accurate and well-performing credit scorecard allows lenders to control their risk exposure through the selective allocation of credit based on the statistical analysis of historical customer data. This thesis identifies and investigates a number of specific challenges that occur during the development of credit scorecards. Four main contributions are made in this thesis. First, we examine the performance of a number supervised classification techniques on a collection of imbalanced credit scoring datasets. Class imbalance occurs when there are significantly fewer examples in one or more classes in a dataset compared to the remaining classes. We demonstrate that oversampling the minority class leads to no overall improvement to the best performing classifiers. We find that, in contrast, adjusting the threshold on classifier output yields, in many cases, an improvement in classification performance. Our second contribution investigates a particularly severe form of class imbalance, which, in credit scoring, is referred to as the low-default portfolio problem. To address this issue, we compare the performance of a number of semi-supervised classification algorithms with that of logistic regression. Based on the detailed comparison of classifier performance, we conclude that both approaches merit consideration when dealing with low-default portfolios. Third, we quantify the differences in classifier performance arising from various implementations of a real-world behavioural scoring dataset. Due to commercial sensitivities surrounding the use of behavioural scoring data, very few empirical studies which directly address this topic are published. This thesis describes the quantitative comparison of a range of dataset parameters impacting classification performance, including: (i) varying durations of historical customer behaviour for model training; (ii) different lengths of time from which a borrower’s class label is defined; and (iii) using alternative approaches to define a customer’s default status in behavioural scoring. Finally, this thesis demonstrates how artificial data may be used to overcome the difficulties associated with obtaining and using real-world data. The limitations of artificial data, in terms of its usefulness in evaluating classification performance, are also highlighted. In this work, we are interested in generating artificial data, for credit scoring, in the absence of any available real-world data

Financial market regulation in the wake of financial crises: the historical experience

The focus of the present volume - which originates from a workshop held at the Bank of Italy on 16 and 17 April 2009 - is the regulatory response given to financial crises in the past, across countries. Alongside the scholarly interest of such a review its aim is also to offer some insights that may be useful in re-designing regulation in the present time of distress. Financial crises have been examined under many perspectives, including that of regulatory failures. The studies assembled in this volume, which touch on a significant array of countries, can be viewed as part of a historical survey on this issue. The basic question is whether regulatory responses form a pattern, and more specifically, whether they tend to be biased with respect to an optimum, however defined. In the end, rather than finding one pattern of response, we were able to identify the "disturbances" which most often enter the post-crisis decisional process. The awareness of such factors, and some knowledge of their functioning, are instrumental in understanding (for academics) and in governing (for policy makers) the response to major financial crises.Financial crises, financial regulation, economic history

Crummer SunTrust Portfolio Recommendations: Crummer Investment Management [2015]

We approach the market this year with muffled optimism. The market’s growth rate will be softer than the last two years, based on our GDP forecast of 2.8% accompanied by steady unemployment and low interest rates. In this environment, stock selection is paramount and we have modified the portfolio to favor pro-cyclical sectors like Consume Discretionary and Industrials

FINANCIAL CRISIS IN THE DEVELOPING WORLD - POST THE US "ASSET PRICE BUBBLE DEBACLE" - A NEW WAY FORWARD

This paper analyze how we should respond to possible asset price bubbles, especially in view of the various conceptual frameworks proposed based on a core set of scientific principles for monetary policy. Further, efforts have also been made at my end to establish as to how Monetary policy should not react to asset price bubbles per se, but rather to changes in the outlook for inflation and aggregate demand resulting from asset price movements. However, regulatory policies and supervisory practices should respond to possible asset price bubbles and help prevent feedback loops between asset price bubbles and credit provision, thereby minimizing the damaging effects of bubbles on the economy.The general massage of this paper is that credit conditions influence economies enormously and emergency steps to restructure balance sheets through policy revamping are crucial for fixing problems of excessive leverage. This stands in sharp contrast to the view from conventional models - that 'the effects of a worsening of financial intermediation are likely to be limited' and can be handled by interest rate cuts alone.In the alternative regulatory policy approach, we have strived to examine three possible regulatory responses to managing bubbles: portfolio restrictions; adjustments in capital requirements; and adjustments in provisioning requirements.JEL Classification: E58, E63, G15Keywords:financial crisis, asset price bubble