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Article
Publication date: 28 July 2021

Abhishek Gupta, Dwijendra Nath Dwivedi, Jigar Shah and Ashish Jain

Good quality input data is critical to developing a robust machine learning model for identifying possible money laundering transactions. McKinsey, during one of the conferences…

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Abstract

Purpose

Good quality input data is critical to developing a robust machine learning model for identifying possible money laundering transactions. McKinsey, during one of the conferences of ACAMS, attributed data quality as one of the reasons for struggling artificial intelligence use cases in compliance to data. There were often use concerns raised on data quality of predictors such as wrong transaction codes, industry classification, etc. However, there has not been much discussion on the most critical variable of machine learning, the definition of an event, i.e. the date on which the suspicious activity reports (SAR) is filed.

Design/methodology/approach

The team analyzed the transaction behavior of four major banks spread across Asia and Europe. Based on the findings, the team created a synthetic database comprising 2,000 SAR customers mimicking the time of investigation and case closure. In this paper, the authors focused on one very specific area of data quality, the definition of an event, i.e. the SAR/suspicious transaction report.

Findings

The analysis of few of the banks in Asia and Europe suggests that this itself can improve the effectiveness of model and reduce the prediction span, i.e. the time lag between money laundering transaction done and prediction of money laundering as an alert for investigation

Research limitations/implications

The analysis was done with existing experience of all situations where the time duration between alert and case closure is high (anywhere between 15 days till 10 months). Team could not quantify the impact of this finding due to lack of such actual case observed so far.

Originality/value

The key finding from paper suggests that the money launderers typically either increase their level of activity or reduce their activity in the recent quarter. This is not true in terms of real behavior. They typically show a spike in activity through various means during money laundering. This in turn impacts the quality of insights that the model should be trained on. The authors believe that once the financial institutions start speeding up investigations on high risk cases, the scatter plot of SAR behavior will change significantly and will lead to better capture of money laundering behavior and a faster and more precise “catch” rate.

Details

Journal of Money Laundering Control, vol. 25 no. 3
Type: Research Article
ISSN: 1368-5201

Keywords

Available. Open Access. Open Access
Article
Publication date: 30 June 2023

Abhishek Nanjundaswamy, Abhinandan Kulal, Sahana Dinesh and M.S. Divyashree

The study aimed at analyzing operations managers’ perception of the use of electric vehicles (EVs) in business processes and its impact on…

3361

Abstract

Purpose

The study aimed at analyzing operations managers’ perception of the use of electric vehicles (EVs) in business processes and its impact on overall business process cost (BPC) and sustainable development (SD).

Design/methodology/approach

The present study adopts the triangulation approach which is a combination of quantitative and qualitative methods. The data was collected using structured and scientifically tested questionnaires from the industrial managers working in the industries in the Mysore region of Karnataka. Descriptive statistics, factor analysis and structural equation models were employed to analyze and interpret the data.

Findings

The findings revealed that the usage of EVs in Business Processes significantly impacts the BPC (b = 0.851, t = 8.037, p < 0.01) and it is also the usage of EVs in business processes can significantly impact SD (b = 0.889, t = 7.923, p < 0.01). Thus, the adoption of EVs in the business process offers many benefits to business organizations such as minimized operational costs, an eco-friendly business model, more tax incentives, less BPCs, a low-emission footprint and a contribution towards SD at large.

Practical implications

Many business organizations operating in the present time show interest in employing EVs in their business processes. Hence, before introducing EVs in industries on a large scale, it becomes imperative to obtain the perception of industrial managers who have already experienced its impact. This study may help industrial organizations to understand the impact of EV on various aspects of the business and to design a business model which would help in achieving SD goals.

Originality/value

The use of EVs in the daily life of human beings and business activities is gaining importance because of the various positive impacts. Therefore, it is necessary to understand industrial managers’ opinions regarding the use of EV in business activities.

Available. Open Access. Open Access
Article
Publication date: 28 October 2021

Kavya Satish, Abhishek Venkatesh and Anand Shankar Raja Manivannan

This research aims to study the recent changes in consumer behaviour and purchase pattern during the Covid-19 pandemic. Covid-19 pandemic has forced consumers to stockpile, which…

9494

Abstract

Purpose

This research aims to study the recent changes in consumer behaviour and purchase pattern during the Covid-19 pandemic. Covid-19 pandemic has forced consumers to stockpile, which has its own consequences. The article proposes the importance of “minimalism in consumption” to avoid greed in consumer behaviour.

Design/methodology/approach

The data are collected from consumers across India using an online survey during the first lockdown from March 2020 to May 2020. A simple random sampling technique is used for data collection, and the collected data are analysed using SPSS version 26.

Findings

The study states that there will be a shift in the purchase pattern of the consumers if lockdowns are imposed in the future or during any other crisis. However, at present, consumers have developed a stockpiling mentality fearing the unavailability of essentials.

Research limitations/implications

Pandemic has stimulated a drastic change in consumer behaviour, which is a situational effect. Each crisis affects consumer behaviour in a different way. In this research, we have considered only fear, greed and anxiety in the light of Covid-19. On the other hand, the research intends to draw realistic conclusions based on consumers' experiences during the lockdown.

Practical implications

The study proposes solutions that will help marketers frame exclusive strategies for a future crisis. Analysing the change in consumer behaviour and the shift in purchase patterns will emphasize the importance of market research to know consumer expectations during a crisis situation in order to cater to their new demands.

Social implications

Consumers who stockpile should realize the unavailability of goods to other consumers who are in need. They also have to understand the importance of “minimalism in consumption” during a crisis.

Originality/value

The data are collected during the most taxing crisis, the Covid-19 pandemic. Data are collected at the peak time of the first wave of Covid-19 in India, during a major shift in consumers' behaviour and purchase pattern. The article brings to the larger consciousness and also preaches a life lesson to all consumers to execute their responsibilities in consumption without over-demands and expectations.

Details

South Asian Journal of Marketing, vol. 2 no. 2
Type: Research Article
ISSN: 2719-2377

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