A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
Study compares classification techniques to predict customer churn in banking.
GenAI offers financial benefits but requires risk management.
Recent developments in the literature on financial architecture suggest that banks and markets not only coexist, but also coevolve in ways that are non-neutral from the viewpoint of optimality. This article aims to analyse the concrete mechanisms of this coevolution by focusing on a very relevant case study: Belgium (t…
We analyze the influence and interactions of 60 largest world banks for 195 world countries using the reduced Google matrix algorithm for the English Wikipedia network with 5 416 537 articles. While the top asset rank positions are taken by the banks of China, with China Industrial and Commercial Bank of China at the f…
The study compares profitability of conventional and Islamic banks in Bangladesh.
The study improves CLV predictions in retail banking with machine learning.
Study on electronic banking satisfaction in Nigeria.
iConViz helps banks manage default contagion risk in networked loans.
A new risk measure framework captures multivariate risk in banking.
The study designs inherently interpretable machine learning models for high-risk sectors.
The banking industry is very important for an economic cycle of each country and provides some quality of services for us. With the advancement in technology and rapidly increasing of the complexity of the business environment, it has become more competitive than the past so that efficiency analysis in the banking indu…
AI enhances bank credit risk management through deep learning and data analysis.
New method estimates corporate default probabilities using indirect data.
Geospatial framework assesses climate risks for California's banking and exposed sectors.
This paper reviews bank performance determinants, highlighting future research areas.
The study examines collective behavior in banking sectors across mature and emerging markets.
This paper contains a feasibility study of deep neural networks for the classification of Euro banknotes with respect to requirements of central banks on the ATM and high speed sorting industry. Instead of concentrating on the accuracy for a large number of classes as in the famous ImageNet Challenge we focus thus on c…
The manipulation of LIBOR by a group of banks became one of the major blows to the remaining confidence in financial industry. Yet, despite an enormous amount of popular literature on the subject, rigorous time-series studies are few. In my paper, I discuss the following hypothesis. Namely, if we should assume for a st…
Develops a framework to assess systemic risk in the economy using bank-firm network data.
Company2Vec creates embeddings from company websites for fine-grained business analytics.
To meet the Basel II regulatory requirements for the Advanced Measurement Approaches in operational risk, the bank's internal model should make use of the internal data, relevant external data, scenario analysis and factors reflecting the business environment and internal control systems. One of the unresolved challeng…
Expert system predicts credit card charge-offs using macroeconomic indicators.
We describe the innovations in finances, introduced over the recent decades, and analyze most of the business and regulatory challenges, faced by the financial industry, because of the present disruptive changes in the global capital markets. We use the integrative thinking approach to formulate the new central bank st…
The management of operational risk in the banking industry has undergone significant changes over the last decade due to substantial changes in operational risk environment. Globalization, deregulation, the use of complex financial products and changes in information technology have resulted in exposure to new risks ve…
This paper explores IT governance for CBDC adoption in financial markets.
By mid 2004, the Basel Committee on Banking Supervision (BCBS) is epected to launch its final recommendations on minimum capital requirements in the banking industry. Although there is the intention to arrive at capital charges which concur with economic intuition, the risk weight formulas proposed by the committee wil…
FraudTransformer detects payment fraud by preserving event order and time gaps.
In this paper we formulate a corporate bond (CB) pricing model for deriving the term structure of default probabilities (TSDP) and the recovery rate (RR) for each pair of industry factor and credit rating grade, and these derived TSDP and RR are regarded as what investors imply in forming CB prices in the market at eac…
Deep learning improves credit risk assessment without new data.
This thesis tackles bias in AI decision-making in banking.
Myanmar is languishing at the bottom of key international indexes. United Nations considers the country as a structurally weak and vulnerable economy. Yet, from 2011 when Myanmar ended decades of military rule and isolationism and transited towards democracy, its breakneck development has led to many considering the co…
This paper improves operational risk modeling by selecting better loss severity distributions.
Risk management is an important practice in the banking industry. In this paper we develop a new methodology to estimate and predict the probability of default (PD) based on the rating transition matrices, which relates the rating transition matrices to the macroeconomic variables. Our method can overcome the shortcomi…
AI enhances ESG practices in finance, but requires careful consideration.
We educe a perspective on how best to regulate the bank of tomorrow in frames of debate launched by the International Centre for Financial Regulation and Financial Times. Our goal is to create a conceptual framework for policymakers and regulators to shape the international financial system in century of globalization …
Paper defines new risk measures for elliptical distributions.
Reinforcement learning has become one of the best approach to train a computer game emulator capable of human level performance. In a reinforcement learning approach, an optimal value function is learned across a set of actions, or decisions, that leads to a set of states giving different rewards, with the objective to…
The paper analyzes sterling bills of exchange during the first globalization, revealing their global financial role.
Unlike other industries in which intellectual property is patentable, the financial industry relies on trade secrecy to protect its business processes and methods, which can obscure critical financial risk exposures from regulators and the public. We develop methods for sharing and aggregating such risk exposures that …
We give a detailed account of correlations between credit sector/quality and treasury curve factors, using the robust framework of the Barclays POINT Global Risk Model. Consistent with earlier studies, we find a strong negative correlation between sector spreads and rate shifts. However, we also observe that the correl…
Study compares information flow between Chinese and US stock sectors.
One of the key elements in the banking industry rely on the appropriate selection of customers. In order to manage credit risk, banks dedicate special efforts in order to classify customers according to their risk. The usual decision making process consists in gathering personal and financial information about the borr…
An asset network systemic risk (ANWSER) model is presented to investigate the impact of how shadow banks are intermingled in a financial system on the severity of financial contagion. Particularly, the focus of this study is the impact of the following three representative topologies of an interbank loan network betwee…
Study analyzes profitability and efficiency of Chinese banks, finding state-owned banks superior.
The European sovereign debt crisis has impaired many European banks. The distress on the European banks may transmit worldwide, and result in a large-scale knock-on default of financial institutions. This study presents a computer simulation model to analyze the risk of insolvency of banks and defaults in a bank credit…
This paper examines SVB's failure and its impact on bank stocks.
We report a study of a stylized banking cascade model investigating systemic risk caused by counter party failure using liabilities and assets to define banks' balance sheet. In our stylized system, banks can be in two states: normally operating or distressed and the state of a bank changes from normally operating to d…
We consider the problem of governing systemic risk in an assets-liabilities dynamical model of banking system. In the model considered each bank is represented by its assets and its liabilities.The capital reserves of a bank are the difference between assets and liabilities of the bank. A bank is solvent when its capit…