44,319 Hits in 4.3 sec

Data Analytics in Banking and Financial Services

S. Palaniammal, V. S. Thangamani
2019 Asian Journal of Computer Science and Technology  
In Journal of Banking and Finance [1] we are living in the era of the big data.  ...  For example, we can see rapid changes to organisation structures, approach to competition and customer as well as the recognition of the importance of data analytics in strategic and tactical decision  ...  CONCLUSION Banking analytics, or applications of data mining in banking, can help improve how banks segment, target, acquire and retain customers.  ... 
doi:10.51983/ajcst-2019.8.s1.1955 fatcat:7qm3bmp4c5cj3djksydamcbnp4

Real-Time Inbound Marketing: A Use Case for Digital Banking [chapter]

Alan Megargel, Venky Shankararaman, Srinivas K. Reddy
2018 Handbook of Blockchain, Digital Finance, and Inclusion, Volume 1  
Real-time inbound marketing: A use case for digital banking. (2018). Handbook of blockchain, digital finance, and inclusion: Cryptocurrency, FinTech, InsurTech, and regulation. 311-328.  ...  Research Collection School Of Information Systems.  ...  interpreting large amounts of data from various sources (Kona and Surti, 2010) .  ... 
doi:10.1016/b978-0-12-810441-5.00013-0 fatcat:wzhugicupnezbglyq4exg3pe6u

Big Data In Banking: A Bird's Eye View

2020 GIS Business  
Banks have voluminous data about their customers, which most of the banks failed to utilize in a well-timed manner.  ...  Big data analytics can be actuated in key areas like customer segmentation, offering customer lifetime value, fraud detection, risk modeling, etc.  ...  Big Data locates and presents big data on a single large scale that makes it easier to reduce the number of risks to a manageable number.  ... 
doi:10.26643/gis.v14i6.16861 fatcat:3qw2xiphvvax7b6e4pqittu3a4

Effect of Distribution Channel Strategies on the Performance of Banks

Dickson Ben Uche, Jane Nwakaego Anene, Emezue Leonard Nnabugwu
2022 Daengku Journal of Humanities and Social Sciences Innovation  
The population of the study was 43 management staff of five commercial banks operating in Nigeria. Questionnaire was used as the tool for data collection.  ...  on the performance of the bank.  ...  Thus, it gives access to a large segment and a large geographical coverage without large-scale investments. It also relies on thoroughly tested and secure technology.  ... 
doi:10.35877/454ri.daengku732 fatcat:bwiw7xlklng2fezz4uefmnmyfa

Towards Intelligent Risk-based Customer Segmentation in Banking [article]

Shahabodin Khadivi Zand
2020 arXiv   pre-print
For example, customer segmentation, i.e., the process of grouping related customers based on common activities and behaviors, could be a data-driven and knowledge-intensive process.  ...  In this paper, we present an intelligent data-driven pipeline composed of a set of processing elements to move customers' data from one system to another, transforming the data into the contextualized  ...  Figure 3 . 3 The proposed intelligent data-driven pipeline to automate risk-based customer segmentation process in banking. Figure 4 . 4 Risk Taxonomy 56 .  ... 
arXiv:2009.13929v1 fatcat:v52ryj3xzrhrfdktn3tti7mwd4

iC3i-A Environment for Analyzing Customer Behaviour in Banking Sector

Archana. S, Dhivyasri. Y, Nivetha. R, Srividya. R, Mr. P. Anandajayam
2017 International Journal of Engineering Research and  
However handling large volume of data efficiently and developing insight with real business value which makes data scientists to face large challenges.  ...  The volume of data gathered by bank is increasing speedily and provides moment for banks to conduct predictive analytics and boost its business.  ...  This further enables a bank to conduct large-scale customer experience analytics and gain deeper insights for customers, channels, and the entire market.  ... 
doi:10.17577/ijertv6is030198 fatcat:sbpbplxl35cyvlalnrrgwcgvwa

Using Unsupervised Machine Learning Techniques for Behavioral-based Credit Card Users Segmentation in Africa

Eric Umuhoza, Dominique Ntirushwamaboko, Jane Awuah, Beatrice Birir
2020 SAIEE Africa Research Journal  
Andrew Raafat of the analytics and big data lab for their tremendous assistance during the project.  ...  ACKNOWLEDGMENT This research came out of the practicum project submitted by the CIB to CMU Africa in fall 2019. We acknowledge the big role played by the CIB and its staff, especially Ms.  ...  CIB pioneered to build an advanced analytics and big data lab in 2015 with a vision to evolve from a successful yet local traditional bank into a leading data driven, customer-centric organization that  ... 
doi:10.23919/saiee.2020.9142602 fatcat:42ynwtzg4rfdxoewawtjnlgbly

Technological branch investments in physical branching strategies of small and medium scale banks

Selman Ortakoy
2017 Pressacademia  
In this regard, XTM Branches of a medium scale Bank has been taken as a technological branch example.  ...  In that sense, investments in technological branches could be an alternative for banks.  ...  Score Retail Score Houselhold Income 0% 15% Potencial Customer Number 0% 35% The Number of C+ Segment Customer 0% 8% Number of Large-Scale Company (250+ staff) 45% 0% Number of Micro-Scale  ... 
doi:10.17261/pressacademia.2017.535 fatcat:ev4r22vryzgxxbrjej5iaq5x2u

What does financial intermediation theory tell us about fintechs?

Júlia Molnár
2018 Vezetéstudomány / Budapest Management Review  
It focuses on two particular segments of the Fintech sector: online marketplace lenders and neo-banks.  ...  Technology and the widespread usage of internet have gradually changed the design and delivery of several banking services.  ...  Online marketplace lending Marketplace lending is a newly emerging segment of the financial services industry that leverages investment capital and operates data-and technology-driven online platforms  ... 
doi:10.14267/veztud.2018.05.04 fatcat:q34ah76ajvguflhsk4lyr7knry

Enterprise-wide analytical solutions for distribution planning

Keith Peterson
2003 Journal of Database Marketing & Customer Strategy Management  
Market entry is driven by untapped demand potential in the area. It is driven primarily by household mass and presence of target market segments for product.  ...  sources, making it difficult to resolve discrepancies by data source. Large-scale distribution planning systems cannot succeed without support from technology experts.  ... 
doi:10.1057/palgrave.dbm.3240202 fatcat:3rusys7ocndk5obfgatt2rdkn4


Pallavi Pandey, Bilal Mustafa Khan, Harish Singla
These features of digital platform are necessary for banks to provide uninterrupted services,safely to customers and allow business as usual.Artificial Intelligence and Machine Learning are enthusiastically  ...  Customer experience is the primary focus for the banks that are looking for ways to improve it either with their applications or simplifying customer journeys and introducing omnichannel experience.COVID  ...  The primary target segment for a large section of digital lenders is to provide small ticket, contextual unsecured credit, as they lend to customers having no credit or limited credit record.  ... 
doi:10.36106/paripex/6406903 fatcat:e6bdpndnofaczjyyz3qb26ap7u

Benefits of Using Data Mining Techniques for Business Intelligence

2022 Journal of Research in Science and Engineering  
The outcome of research shows that data mining tools are capable of discovering patterns in data in few hours those expert human quantitative analysts might not find in years of work to help make decision  ...  An important component of many of these applications is customer profiling, which aims to extract patterns of behavior from a collection of transaction records, and the comparison of such patterns.  ...  The need to scale up human analysis capabilities to handling the large number of bytes that we can collect is both economic and scientific.  ... 
doi:10.53469/jrse.2022.04(07).09 fatcat:jprcfyjtnbeppmtlw53bonz3je

Digitalisation and Big Data Mining in Banking

Hossein Hassani, Xu Huang, Emmanuel Silva
2018 Big Data and Cognitive Computing  
Banking as a data intensive subject has been progressing continuously under the promoting influences of the era of big data.  ...  Exploring the advanced big data analytic tools like Data Mining (DM) techniques is key for the banking sector, which aims to reveal valuable information from the overwhelming volume of data and achieve  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/bdcc2030018 fatcat:xlz5erzbrbd2ppfuzqdxnqrjxu

Interactive Psychographics: Cross-Selling in the Banking Industry

James W. Peltier, John A. Schibrowsky, Don E. Schultz, John Davis
2002 Journal of Advertising Research  
Pevrier following data differences often exist between customers and prospects aq | ia e Customers: The bank has behavioral data specific to banking on each individus This is the best data possible for  ...  In the next section we describe a study designed to test these relationships DATA ANALYSIS* Method To test the proposed model, data were col lected in conjunction with a large regional bank that was interested  ... 
doi:10.2501/jar-42-2-7-22 fatcat:hjhhi7uk4jaqbdus4w5pmgikhe

Financial Intermediation and Technology

Arnoud Boot, Peter Hoffmann, Luc Laeven, Lev Ratnovski
2020 IMF Working Papers  
Specialized providers of financial services can chip away activities that do not rely on access to balance sheets, while platforms can interject themselves between banks and customers.  ...  We point to more recent innovations, such as the combination of data abundance and artificial intelligence, and the rise of digital platforms.  ...  Data ownership rules are often undefined; the use of data is non-rivalrous, but exhibits large economies of scale and scope especially under AI and big data; data collection can entail externalities (  ... 
doi:10.5089/9781513552491.001 fatcat:qxtlfoi5r5avpezytswnmwsxay
« Previous Showing results 1 — 15 out of 44,319 results