# A Systematic Review of Intelligent Systems and Analytic Applications in Credit Card Fraud Detection
## 4 Emerging Fraud Detection Techniques
### Agent-Based Modelling in CCFD
\begin{table}
\begin{tabular}{c c c c} \hline
**Reference** & **Title** & **Topic** & **Comment** \\ \hline \multirow{8}{*}{([PERSON] et al., 2018) [62]} & Early Warning Indicators and Macro Prudential Policies—a Credit Network Agent-Based Model & Finance–Banking–Credit Network System & In the study, an agent model was developed that renews an artificial credit network according to the leverage options of firms and banks. The study aimed to identify and analyze both early warning indicators and policy precautionary measures in the credit network. \\ \hline \multirow{8}{*}{([PERSON] et al., 2014) [64]} & Housing Market Bubbles and Business Cycles in an Agent Credit Economy & Finance–Banking–Credit Network System & In the study, housing and mortgage markets were examined with an agent-based macroeconomic model. A series of computational experiments were conducted to investigate the effects of different households’ credibility conditions on the credit network system. In the study, it is seen that easy access to credit increases housing prices and uncertainty in the economy. \\ \hline \multirow{8}{*}{([PERSON] et al., 2013) [65]} & In the study, the relationships between income distribution and monetary and fiscal policies were examined using a different version of the agent-based & In the study, the relationships between income distribution and monetary and fiscal policies were examined using a different version of the agent-based & In the study examined the interaction between increasing inequality and consumer credit in a multiplex macroeconomic system of households, banks and firms. The simulation results show that there are positive and negative effects to implementing consumer credit. A fiscal policy might be needed as the increase in financial profits triggers the decline in the real wealth of the household. \\ \hline \multirow{8}{*}{([PERSON] et al., 2016) [66]} & Increasing Inequality, Consumer Credit, and Financial Fragility in an Agent Macroeconomic Model & Economics–Financial Impact–Macroeconomic Model & In the study, an agent-based model was presented that reproduces a credit network formed by firms, banks, and individual customers. Simulation trials show that a combination of micro and macro prudential strategies decreases systemic risk but also increases banks’ capital volatility. The results support the argument that meso prudential policy can reduce systemic risk without affecting the stability of banks’ capital structure. \\ \hline \multirow{8}{*}{([PERSON] et al., 2021) [63]} & \multirow{8}{*}{\
\begin{tabular}{c} Incentive Distribution, Credit and Fiscal Policies in an Agent Keynesian Model \\ Model \\ \end{tabular} } &
\begin{tabular}{c} The study examined the interaction between increasing inequality and consumer credit in a multiplex macroeconomic system of households, banks and firms. The simulation results show that there are positive and negative effects to implementing consumer credit. A fiscal policy might be needed as the increase in financial profits triggers the decline in the real wealth of the household. \\ \end{tabular}
\end{table} 
Table 4: _Cont._In agent-based card fraud modelling studies, while some of the samples are used for training, testing, and validation, some of them can be used for scoring, monitoring, and reporting. In the first stage of the card fraud model development, the model pattern is determined by taking the training data set as a reference. The performance of the agent-based fraud training model can be examined on different data sets such as testing. The agent-based model should also be tested on out-of-time data sets, such as validation and scoring data sets. In credit card fraud studies, the performances of agent-based models and benchmarking models should be evaluated with the help of key performance indicators (KPIs). Training models are recorded in the process known as machine learning operations (MLOps), which is a continuation of the model development process.