Popular approaches to building data from unstructured text come with limitations, such as scalability, interpretability, replicability, and real-world applicability. These can be overcome with Context Rule Assisted Machine Learning (CRAML), a method and no-code suite of software tools that...

There is increasing deployment of machine learning algorithms by financial institutions during and after the coronavirus pandemic. However, majority of these models are being implemented for credit risk management, anti-fraud and anti-money laundering use cases. Moreover, previous research and...

Due to the global financial crisis, credit on international markets became more restricted for banks, turning attention to internal clients and their deposits to gather funds. This driver led to a demand for knowledge about client’s behavior towards deposits and especially their response to...

The increased globalization makes every country more and more responsible for its actions that are meant to support the price stability and the fiscal position sustainability in an unpredictable world. Decisions makers can provide the right solutions to overcome the latest global economic crisis...

The research paper, focused on a rather technical approach, has the goal to design a system that brings together diverse audit stakeholders and investigates how an audit database available online can be implemented in SharePoint, as part of an on-line audit system which is collaborative and...

Using Gretl, I apply ARMA, Vector ARMA, VAR, state-space model with a Kalman filter, transfer-function and intervention models, unit root tests, cointegration test, volatility models (ARCH, GARCH, ARCH-M, GARCH-M, Taylor-Schwert GARCH, GJR, TARCH, NARCH, APARCH, EGARCH) to analyze quarterly time...

In this paper we illustrate the development of a modeling framework aimed at producing detailed quantitative estimates for economic variables, consistent with Shared Socio-economic Pathways, and their assumptions about national income and population. Our model not only provides information on...

Volumes of available digital data have been significantly expanding over the past decade. Alongside the volume, diversity and complexity of digital data have also been growing. Contemporary devices and systems are capable of generating data vastly exceeding capabilities of organizations and...

In this paper we present a computable general equilibrium model (G-RDEM), specifically designed for the generation of long run scenarios of economic development, featuring a non-homothetic demand system, endogenous saving rates, differentiated industrial productivity growth, interest payments on...

We motivate and detail the newly developed G-RDEM recursive-dynamic Computable General Equilibrium model as a tool for long-term counterfactual analysis and baseline generation from given GDP and population projections. It encompasses an AIDADS demand system with non-linear Engel curves, debt...