Automated Teller Machine Cash Demand Prediction

2021 ◽  
Author(s):  
Vismit Vishram Chavan ◽  
Jasvin James Manjaly ◽  
Mohammed Abbas Ali
Keyword(s):  
Demand Prediction ◽  
Automated Teller Machine ◽  
Cash Demand

Potential Indicators Based Neural Networks for Cash Forecasting of an ATM

2016 ◽  
pp. 1545-1563
Author(s):  
Partha Sarathi Mishra ◽  
Satchidananda Dehuri
Keyword(s):  
Neural Networks ◽  
Time Series ◽  
Computational Finance ◽  
Optimal Solutions ◽  
Series Method ◽  
Automated Teller Machine ◽  
Time Series Method ◽  
Past Data ◽  
High Degree ◽  
Cash Demand

Cash forecasting is one of the important tasks in the domain of computational finance. A number of tools have been developed by various groups of researchers and are being used by banks or corporate to identify future cash needs. However, due to the high degree of non-linearity of the problem and surrounded by many local optimal solutions, this paper propose a multi-layer locally tuned perceptron (MLTP) to forecast the future needs and at the same time reduce the users frustration. It uses a fine tuned MLTP to forecast a daily cash demand of an automated teller machine (ATM). Further, potential indicators are used to making the model robust in terms of its efficiency and accuracy. The accuracy is compared against a traditional time series method. Furthermore, it is validated using the past data collected from the SBI ATM of Bhadrak district of Odisha, India. The performance of the method is encouraging. This system can be scaled for all branches of a bank in an area by incorporating historical data from these branches.

Potential Indicators Based Neural Networks for Cash Forecasting of an ATM

2014 ◽  
Vol 5 (4) ◽  
pp. 41-57 ◽  
Author(s):  
Partha Sarathi Mishra ◽  
Satchidananda Dehuri
Keyword(s):  
Historical Data ◽  
Computational Finance ◽  
Optimal Solutions ◽  
Series Method ◽  
The Past ◽  
Automated Teller Machine ◽  
Time Series Method ◽  
Past Data ◽  
High Degree ◽  
Cash Demand

Cash forecasting is one of the important tasks in the domain of computational finance. A number of tools have been developed by various groups of researchers and are being used by banks or corporate to identify future cash needs. However, due to the high degree of non-linearity of the problem and surrounded by many local optimal solutions, this paper propose a multi-layer locally tuned perceptron (MLTP) to forecast the future needs and at the same time reduce the users frustration. It uses a fine tuned MLTP to forecast a daily cash demand of an automated teller machine (ATM). Further, potential indicators are used to making the model robust in terms of its efficiency and accuracy. The accuracy is compared against a traditional time series method. Furthermore, it is validated using the past data collected from the SBI ATM of Bhadrak district of Odisha, India. The performance of the method is encouraging. This system can be scaled for all branches of a bank in an area by incorporating historical data from these branches.

Customers’ Satisfaction Towards Automated Teller Machine

2011 ◽  
Vol 4 (5) ◽  
pp. 333-336
Author(s):  
Dr. R. Renuka Dr. R. Renuka ◽  
◽  
A. Paulraj A. Paulraj
Keyword(s):  
Automated Teller Machine

PEMBUATAN PENDETEKSI OBYEK DENGAN METODE YOU ONLY LOOK ONCE (YOLO) UNTUK AUTOMATED TELLER MACHINE (ATM)

2019 ◽  
Vol 17 (1) ◽  
pp. 69-76
Author(s):  
Mohammad Shiddiq Ghozali
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Object Detection ◽  
Open Source ◽  
Automated Teller Machine

Perkembangan Teknologi Informasi dan Komunikasi begitu pesat di zaman sekarang ini. Diikuti pula dengan perkembangan di bidang Artificial Intelligence (AI) atau Kecerdasan Buatan. Di Indonesia sendiri masih belum begitu populer dikalangan masyarakat akan tetapi perusahaan-perusahaan IT berlomba-lomba menciptakan inovasi dibidang Kecerdasan Buatan dan penerapan Kecerdasan Buatan disegala aspek kehidupan. Contoh kasus di Automated Teller Machine (ATM), seringkali terjadi kejahatan di ATM seperti pengintaian nomor pin, skimming, lebanese loop dan kejahatan lainnya. Walaupun di ATM sudah terdapat CCTV akan tetapi penjahat menggunakan alat bantu untuk menutupi wajahnya seperti helm, topi, masker dan kacamata hitam. Biasanya didepan pintu masuk ATM terpampang larangan untuk tidak menggunakan helm, topi, masker dan kacamata hitam serta tidak membawa rokok. Akan tetapi larangan itu masih tetap ada yang melanggar, dikarenakan tidak ada tindak lanjut ketika seseorang menggunakan benda-benda yang dilarang dibawa kedalam ATM. Oleh karena itu penulis membuat sistem pendeteksi obyek di bidang Kecerdasan Buatan untuk mendeteksi benda-benda yang dilarang digunakan ketika berada di ATM. Salah satu metode yang digunakan untuk menciptakan Object Detection yaitu You Only Look Once (YOLO). Implementasi ide ini tersedia pada DARKNET (open source neural network). Cara kerja YOLO yaitu dengan melihat seluruh gambar sekali, kemudian melewati jaringan saraf sekali langsung mendeteksi object yang ada. Oleh karena itu disebut You Only Look Once (YOLO). Pada penelitian ini, penulis membuat sistem yang masih dalam bentuk pengembangan, sehingga menjalankannya masih menggunakan command prompt. Keywords : Automated Teller Machine (ATM), Kecerdasan Buatan, Pendeteksi Obyek, You Only Look Once (YOLO)  

Financial Innovations and Performance of Commercial Banks in Kenya

2020 ◽  
Vol 2 (2) ◽  
pp. 21-33
Author(s):  
Naomi Wanja Ireri ◽  
Gladys Kimutai
Keyword(s):  
Rural Areas ◽  
Commercial Banks ◽  
Internet Banking ◽  
Ease Of Use ◽  
Primary Data ◽  
The Internet ◽  
Mobile Banking ◽  
Good Opportunity ◽  
Financial Innovations ◽  
Automated Teller Machine

Commercial banks in Kenya have embraced alternative banking channels which represent a shift in delivery of banking and financial services since the alternative banking have become synonymous with commercial banks in Kenya. While banks have succeeded in leveraging available technology and provide alternative avenues to customers for banking services, the challenge it faces today is optimizing the usage of these channels so as to improve on their performance. The general objective of this study was to investigate the effects of financial innovations on the performance of commercial banks in Kenya. The specific objectives of the study were to examine the influence of internet banking, mobile banking, agency banking and ATM banking on the performance of commercial banks in Kenya. The study was guided by agency theory, balanced score card and diffusion of innovation theory. This study employed a descriptive research design. The study targeted44 commercial banks in Kenya as at 2017. The 16 banks which embrace all the four financial innovations from 2013 to 2017were selected using purposive sampling method. The sample size was 80 respondents who comprised of 5 senior management employees in each of the selected banks.This study used questionnaire to collect primary data from the respondents. Content analysis technique was used to analyze qualitative data collected from open ended questions in and reported in narrative form. Descriptive statistics such as mean and standard deviation were used to analyse the quantitative data. Multiple regression analysis was used to show the relationship between independent variables against dependent variable. The study revealed that internet banking, mobile banking, agency banking and ATM banking had a positive and significant effect on the performance of commercial banks. Thisstudy concludes that the banking industry has benefited tremendously from the development of the Internet. The Internet fundamentally changed the way in which banking networks are designed to meet the client demands and expectations. Mobile banking provides a good opportunity to commercial banks in Kenya to reach many mobile phone subscribers in Kenya who had remained unbanked and unreached due to limited access to bank branch networks in the country. The access to the large masses through mobile banking of the population gives banks the opportunity to grow by reaching the unbanked population. Agency banking has led to accessibility of financial service to many customer in remote areas and hence an increase in effectiveness and efficiency in service delivery. Customers are satisfied with the automated teller machine services because of ease of use, transaction cost and service security but not satisfy with automated teller machine dispense of cash. The study recommends that the public and businesses must be encouraged to use Internet banking in their daily activities, including deposits, payments and money transfers. Commercial banks in Kenya should ensure convenience and security of mobile banking through written guidelines on convenience and security of mobile banking. Commercial banks in Kenya should increase the number of agents in estates and in the rural areas. This can be done by reducing the requirements of becoming a bank agent. The banks should employ customized software that records relevant information on automated teller machine cards so that banks can establish whether unauthorized transaction has taken place or not.

scholarly journals Microfluidic Network Simulations Enable On-Demand Prediction of Control Parameters for Operating Lab-On-A-Chip-Devices

Processes ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 1320
Author(s):  
Julia Sophie Böke ◽  
Daniel Kraus ◽  
Thomas Henkel
Keyword(s):  
Fluid Management ◽  
Lab On A Chip ◽  
Microfluidic System ◽  
Flow Rates ◽  
Demand Prediction ◽  
Fast Running ◽  
Microfluidic Network ◽  
Fluid Properties ◽  
Network Simulations ◽  
User Friendly

Reliable operation of lab-on-a-chip systems depends on user-friendly, precise, and predictable fluid management tailored to particular sub-tasks of the microfluidic process protocol and their required sample fluids. Pressure-driven flow control, where the sample fluids are delivered to the chip from pressurized feed vessels, simplifies the fluid management even for multiple fluids. The achieved flow rates depend on the pressure settings, fluid properties, and pressure-throughput characteristics of the complete microfluidic system composed of the chip and the interconnecting tubing. The prediction of the required pressure settings for achieving given flow rates simplifies the control tasks and enables opportunities for automation. In our work, we utilize a fast-running, Kirchhoff-based microfluidic network simulation that solves the complete microfluidic system for in-line prediction of the required pressure settings within less than 200 ms. The appropriateness of and benefits from this approach are demonstrated as exemplary for creating multi-component laminar co-flow and the creation of droplets with variable composition. Image-based methods were combined with chemometric approaches for the readout and correlation of the created multi-component flow patterns with the predictions obtained from the solver.

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