Of course it is! Risk management analysis is one of the key areas where banking sector can save themselves from any kind of fraud and unrecoverable risk. From all customer, business and compliance point of view, such analysis is at most required. An MBA (Finance) and PGP Analytics by Education, Kamalika is passionate to write about Analytics driving technological change. Implementing a big data banking analytics strategy is in the best interest of any financial institution, but it isn’t without its challenges. Also, most of the generated data is unstructured, and so you need machine learning technologies like R and Python or even have to write UDFs to make it structured and process further using Hadoop ecosystems.eval(ez_write_tag([[250,250],'hdfstutorial_com-medrectangle-4','ezslot_10',135,'0','0']));eval(ez_write_tag([[250,250],'hdfstutorial_com-medrectangle-4','ezslot_11',135,'0','1'])); Every sector has loads of data and all companies need to do is analyze those data for some fruitful result. Today, Online retailers can tell you that today’s e-commerce sector simply. Big Data in Banking – Sales and Marketing Axtria Axtria offers a Cloud Information Management service, which it claims can help banking, financial services, and insurance companies explore new sources of data that banks could Over 1.7 billion people … This will help the BFSI industry to provide improved services in a timely manner with optimized operational costs. Additionally, improvements to risk management, customer understanding, risk and fraud enable banks to maintain and grow a more profitable customer base. Here is how these relate to the banks: •  Varietyis the different data types processed. © 2020 Stravium Intelligence LLP. You can also subscribe without commenting. Financial institutions are finding new ways to harness the power of big data analytics in banking every day — a journey of discovery that’s being driven by technological innovation. The promise of Big Data is even greater than this, however, potentially opening up whole new frontiers in financial services. Banks have several used cases to showcase the different ways where the data have been harnessed and used for intelligent analysis. And whenever they find any unusual behavior, they can immediately blacklist their card or account and inform the customer. Banking and the Financial Services Industry is a domain where the volume of data generated and handled is enormous. It is particularly essential in banking. Industries can take help of the data from e-commerce profiles like what they are buying, what they are browsing etc. Banks can also create targeted marketing campaigns based on these insights. Big data is especially promising and differentiating for financial services companies. The banking sector is still dealing with their cost-to-income ratios while global investment flows into the more agile fintech companies delivering a more seamless user experience. Big data service provider companies have a great chance to grab this market and take it to the next level. big data in financial services and banking oracle is available in our book collection an online access to it is set as public so you can download it instantly. In the banking and financial services industry today, the term “Big Data” is no longer a trendy buzzword. Each and every activity of this industry generates a digital footprint backed by data. With Big Data tools, companies are in a better position to improve banking processes and gain additional insights about their customer base. The below graphic by IBM shows how fraud can be detected with predictive analysis. conduct the 2012 Big Data @ Work Survey, the basis for our research study, surveying 1144 business and IT professionals in 95 countries, including 124 respondents from the banking and financial markets industries, or 11 percent of the global respondent pool. It aims to facilitate board-level discussion on AI. We are seeing some benefits being accrued by early adopters, while others […] As Big Data gets, well, bigger, it becomes even more important for executives and C-suites in financial services to stay ahead of the curve. Peter Pop, SVP Financial Services, HCL Technologies Big Data was the phrase on the lips of many business leaders last year, with the concept already moving past the Peak of Inflated Expectations in Gartner’s Hype Cycle. Digitization in the finance industry has enabled technology such as advanced analytics, machine learning, AI, big data, and the cloud to penetrate and transform how financial institutions are competing in the market. After all, a quicker trading platform, lower latency transactions or better financial analysis equals a more competitive edge. Big data analysis can again help in analyzing the data and finding the situation where financial crisis or security issue can occur. Big data is no The risks of algorithmic trading are managed through back testing strategies against historical data. According to TechNavio’s forecast (Technavio 2013), the global big data market in the financial services sector will grow at a This has prompted many BFSI organizations to disrupt their analytics landscapes and gather valuable insights from immense volumes of data assets stored in their legacy systems. Big Data and Hadoop is also assisting the financial services to have an idea of the type and time of their future attacks to happen. Here is a simple customer segmentation analysis-eval(ez_write_tag([[250,250],'hdfstutorial_com-banner-1','ezslot_9',138,'0','0'])); Personalized marketing is nothing but the next step of highly successful segment-based marketing where we divide the customers into a different segment based on some parameters and then follow with them accordingly to convert to sales. Financial institutions have to leverage big data properly as per their compliance requirements and high levels of security standards. The reason behind this is Big Data & Analytics which is changing the way businesses function. Here are some of the common problems banking sector is facing despite having huge data in hand. Employee Engagement For all the attention Big Data has received, many companies tend to forget about one potential application that can have a … Big Data has a lot of benefits that can help to change the banking and financial services industry. This article looks at the Financial Services industry to examine Big Data and the technologies employed. These business gains have been made possible with the existing data analytics practices that have simplified the monitoring and evaluation of the vast amounts of customer data which include personal and security information. amzn_assoc_linkid = "e25e83d3eb993b259e8dbb516e04cff4"; The financial and banking data will be one of the cornerstones of this Big Data flood, and being able to process this data goldmine means gaining a competitive edge over the rest of the financial institutions. The connectivity and data challenge in trading and financial services. •  Volumeis the space that the data will take to store. Though the implementation of Big Data on a large scale has just started to evolve in the BFSI industry, the sooner organizations adopt Big Data practices, the quicker they will be able to unlock the benefits this technology brings to their business. Our teams in asset and wealth management, banking and capital markets, and insurance are helping our clients tackle the biggest issues facing the financial services industry. In personalized marketing, we target individual customer based on their buying habits. In the Banking and Finance Industry, its applications go much further than customer data, and the potential for its uses are immense to the say the least. Replies to my comments With Big Data Analytics, companies in the BFSI sector can not only grow their business but […] With professionals across tax , assurance , and advisory practices , we can help you find ways to thrive even in a period of uncertainty. Today, most banking, financial services, and insurance (BFSI) organizations are working hard to adopt a fully data-driven approach to grow their businesses and enhance the services they provide to customers. Based on these data, banks can make a separate list for such customer and can target them based on their interest and behavior. With big data, these companies can learn how to improve their process and learn more about their consumer base. In fact, in every area of banking & financial sector, Big Data can be used but here are the top 5 areas where it can be used way well. 70 Percent of Organisations are Investing in Risk Modelling and Fraud Detection. Banking analytics, or applications of data mining in banking, can help improve how banks segment, target, acquire and retain customers. amzn_assoc_search_bar = "true"; •  Identifying the main channels where the customer transacts like credit/debit card payments and ATM withdrawals. Technology solutions have removed barriers to entry in the banking and financial services industry. Thanks to big data analytics, as the number of electronic records grows, financial services are actively using it to store data, derive business insights and improve scalability. Legacy systems lack the infrastructure to accommodate big data analytics. But, there are some data themes that are getting overlooked in the industry due to a number of challenges. Big data can be applied to bring immense value to the bank in the avenues of effective credit management, fraud management, operational risks assessment, and integrated risk management. The market for big data technology in the financial and insurance domains is one of the most promising. 8 Reasons Banking and Financial Services Industry Is Betting Big on Data Analytics. On the other hand, there are certain New models of proactive risk management, using big data analytics, are being increasingly adopted by major banks and financial institutions. However, some businesses are still in … Big data in the financial services sector Big data analysis is not something new for banks. amzn_assoc_ad_mode = "manual"; Big data analysis can also support real-time alerting if a risk threshold is surpassed. With professionals across tax , assurance , and advisory practices , we can help you find ways to thrive even in a period of uncertainty. With the volumes that the banks of today work on, handling 1000+tranactions is not a hypothetical figure. From transaction details to credit scores and risk assessment reports, the banks have troves of customer data. Top 20 B.Tech in Artificial Intelligence Institutes in India, Top 10 Data Science Books You Must Read to Boost Your Career, Understanding How AI and ML Improves Variability across B2C Enterprises. The Role of big data in banking is significant. Big data analysis is helping them to know about the details like demographic details, transaction details, personal behavior, etc. Fraudulent crimes impact financial services on a daily basis. In every industry and sector, you will find people talking about data and just data. This real-time evaluation boosts the overall performance and profitability of the banking industry thrusting it to further into a growth cycle. All Big Data. Banking and financial services firms are building a strong foundation in using data by integrating it to their operations for maximum output. How can Artificial Intelligence Drive Predictive Analytics to New Heights? On the other hand, there are certain roadblocks to big data implementation in banking. IoT and Big Data analytics in Banking & Finance: 9 Real-Life Business Examples 1. Along with this, we also offer online instructor-led training on all the major data technologies. Contact the IFM team to learn how your institution can begin to reap the benefits of utilizing big data in banking. Several users also found fraud activity from their account. amzn_assoc_placement = "adunit0"; •  Velocityis the speed of adding new data to the database. Big Data Analytics comes into the picture in cases like this when the sheer volume and size of the data is beyond the capability of traditional databases to collect. According to research done by SINTEF, 90% of data have been generated just in last two years.eval(ez_write_tag([[468,60],'hdfstutorial_com-medrectangle-3','ezslot_8',134,'0','0'])); As you can see from the above figure that how a sudden growth happened in the data generation. The strict compliance regulations and ethics laws of the banking and financial services industries make it necessary for companies to handle documents properly. AI Use in Finance. Banks have been This will help the banks and financial sector to save from any compliance and regulatory issues. Big data analytics in banking can be used to enhance your cybersecurity and reduce risks. Big data in the financial services sector Big data analysis is not something new for banks. Banks have already started using Big Data to analyze the market and customer behavior but still a lot of need to be done. Follow these Big Data use cases in banking and financial services and try to solve the problem or enhance the mechanism for these sectors. to get the data of individual customers. What is Predictive Analytics and how it helps business? 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When banks began to digitize their operational processes, they needed to ensure different means which were feasible to analyse technologies like Hadoop and RDBMS (relational database management systems) for their business gains. Artificial Intelligence and Machine learning solutions help B2C enterprises in. Most banking and financial services are exploring new ways to integrate big data analytics into their processes for maximum output. Our book servers hosts in multiple locations, allowing you to get the most less latency time to Further risk assessment can be done to decide whether to go ahead with the transaction or not.eval(ez_write_tag([[468,60],'hdfstutorial_com-large-leaderboard-2','ezslot_12',140,'0','0'])); While every business involves risks but a risk assessment can be done to know the customer in a better way. 5 Top Big Data Use Cases in Banking and Financial Services. Big data and Internet of Things: governing financial services. Banks have to deal with huge numbers of various types of data day in and day out. Here is the current risk assessment graph of various major banks-. Financial institutions are making use of Big Data in big ways, from boosting cybersecurity to reducing customer churn, cultivating customer loyalty, and more through innovative and personalized offerings that make modern banking a highly individualized experience. Giant financial institutions like the JPMorgan Chase., China Construction Bank Corporation, and BNP Paribas, etc. Studies have shown that 71% of banking and financial market firms use information and big data analytics. Agile, customer-centric, and digitally mature financial services providers are on the cusp of taking over the market. This does raise many questions about data privacy and data sharing. TrafficJunky Ad Network- Should You Use It Or Not? Our teams in asset and wealth management, banking and capital markets, and insurance are helping our clients tackle the biggest issues facing the financial services industry. There’s no denying that data’s an incredibly valuable resource. Do add if you find any other segment where big data can be used in broad scale. Big data maturity levels, Microsoft and Celent, How Big is Big Data: Big Data Usage and Attitudes among North American Financial Services Firm, March 2013. Analysis of the customer behaviour on social media through sentiment analysis helps banks create credit risk assessment and offer customised products to the customer. In this special guest feature, David Friend, co-founder & CEO of Wasabi Technologies, takes a look at the big data and cloud storage technology stack as it relates to the finance industry. Read through its benefits to plunge into right away. For this, the best thing is to take help of Big Data technologies like Hadoop. It is not an unknown fact that the BFSI sector has long … 5 Big Data Use Cases in Banking and Financial Services February 05, 2017 According to Forbes, 87% of companies think big data will make big changes to … The impact of big data on the financial service domain is promising. Big data has made a significant impact in many sectors of the U.S. and world economies like healthcare, manufacturing and retail. Big Data benefits banking and financial services companies in the following ways: Customized Solutions – Through valuable customer data, banks and financial service companies can use this support for customized solution offerings to customers. Notify me of followup comments via e-mail. Gather the previous record of the customer like loan data, credit card history or their background data and analyze whether they can pay the kind of service they are looking for. BIG DATA IN FINANCIAL SERVICES: HOW THE BANKING SECTOR IS LEVERAGING ADVANCED ANALYTICS TO GAIN INSIGHT INTO CUSTOMERS AND THE BUSINESS Synopsis: An exploration into the proliferation of Big Data in the financial services sector, looking at how global financial services providers are using data visualisation software to drive analysis of their customer data … These Big Data use cases in banking and financial services will give you an insight into how big data can make an impact in banking and financial sector. CyberSecurity. 1. Insight Financial Marketing has over seventeen years of experience in helping banks identify opportunities to improve customer loyalty, grow revenue, and reduce potential risk through big data processing and analytics. amzn_assoc_marketplace = "amazon"; One of the biggest ones in financial markets today is data … The current Big Data landscape is one of increasing maturity. The Big Data Analytics in Banking market is expected to register a CAGR of 22.97%, during the period of 2020 to 2025. The major drivers for the adoption of Big Data analytics in the banking sector are the significant growth in the amount of data generated and governmental regulations. amzn_assoc_asins = "0544227751,0062390856,1449373321,1617290343,1449361323,1250094259,1119231388"; Hdfs Tutorial is a leading data website providing the online training and Free courses on Big Data, Hadoop, Spark, Data Visualization, Data Science, Data Engineering, and Machine Learning. Customer experience, in this case, becomes a deciding factor. IBM Global Banker Services, Business analytics and optimization—execution report 2013. If you are looking to advertise here, please check our advertisement page for the details. We have served some of the leading firms worldwide. Banking and the Financial Services Industry is a domain where the volume of data generated and handled is enormous. These data will unstructured and so use Big Data technologies; it can be converted into structured and can be analyzed further. 4 mins read For financial institutions mining of big data provides a … By nature, the banking, financial services, and insurance (BFSI) sector have always been data-driven. Kamalika Some is an NCFM level 1 certified professional with previous professional stints at Axis Bank and ICICI Bank. We here at Hdfs Tutorial, offer wide ranges of services starting from development to the data consulting. One of the ways to determine a technology’s influence on an industry is to look at how an … amzn_assoc_tracking_id = "datadais-20"; The site has been started by a group of analytics professionals and so far we have a strong community of 10000+ professionals who are either working in the data field or looking to it. And data creation isn't slowing down anytime soon. Big Data benefits banking and financial services companies in the following ways: Customized Solutions – Through valuable customer data, banks and financial service companies can use this support for customized solution offerings to customers. Banking and financial services need to do regular compliance and audit for their data, finance, and other stuff. Technology is transforming the banking and finance industry. Big Data offers the ability to provide a global vision of different factors and areas related to financial risk. The Role of Big Data & Data Science in the Banking and Financial Services. This is accomplished through advanced analytics, as well as AI and ML algorithms that drive automation and innovation. After all, a quicker trading platform, lower latency transactions or better financial analysis equals a more competitive edge. Understand customers better Today banks are using big data to create a 360-degree view of each customer based on how everyone individually uses mobile or online banking, branch banking or other channels. A lot of improvements can be needed in Merchant Account Solutions, credit card segment such as wireless credit card reader, best credit card swiper, etc.to make it secure and handy for the users. Big data Use cases in Financial Services Here are five of the most common use cases where banks and financial services firms are finding value in big data analytics. There are a few things banks and credit unions should be aware of before they proceed. Data drives the modern financial industry in many ways. Is Big Data used in CyberSecurity? Like most other industries, analytics will be a critical game changer for those in the financial … Thanks to the Internet of Things, business managers will get real-time financial data that facilitates and improves the quality of the decision-making process. This could have been reduced with the help of big data and machine learning. Copyright © 2016-2020. More than 40 percent of financial companies are experimenting with Big Data and IoT, according to a recent report. This helps in targeting the customer in a better way. Data is the most critical asset of financial organisations and they have found ways to leverage this data. Follow these Big Data use cases in banking and financial services and try to solve the problem or enhance the mechanism for these sectors. Financial services firms are leveraging big data to transform their processes, their organizations and soon, the entire industry. Two such innovations, machine learning and This event will help business leaders make better sense of the real data they have , get to it quickly and make the right, cost-effective decisions . By using intelligent algorithms, you can detect fraud and prevent potentially malicious actions. Working with Big Data, banks can now use a customer’s transactional information to continually track his/her behaviour in real-time, providing the exact type of resources needed at any given moment. In some cases, you likewise pull off not discover the statement If these sectors can use Big Data and related technologies in these niches, then they may expect some good result and better customer valuation. Big Data serves many advantages to banks and other companies that deal with financial services. To optimize the high-volume information pulling of a big data model while ensuring compliance, firms utilize Optical Character Recognition (OCR). Following the Great Recession of 2008 which drastically affected global banks, big data analytics has otherwise enjoyed decade old popularity in the financial sector. This data opens up new and exciting opportunities for customer service by improving TAT, and customised service offerings. The financial services industry is highly competitive, with products fighting for the smallest differentiation to make an impact in the market. What’s more, it’s projected that retail banking organisations will lead the adoption of Big Data by 2020, by a staggering 80 percent [Source]. The use of big data in banking is growing astronomically. The innovative use of technology in the design and delivery of financial services and products has led to Fintech (financial technology) altogether. As the number of electronic records grows, financial services are actively using big data analytics to derive business insights, store data, and improve scalability. amzn_assoc_region = "US"; The innovative use of technology in the design and delivery of financial services and products has led to Fintech (financial technology) altogether. All Rights Reserved. The amount of data generated by the financial industry—credit card transactions, ATM withdrawals, credit scores—is mind-boggling. Predictive analytics in banking and financial services paired with artificial intelligence (AI) is on the verge of going mainstream. Created by HdfsTutorial. Don't subscribe Big data analytics in banking can be used to enhance your cybersecurity and reduce risks. Big Data is used for personalized marketing, targeting customers on the basis of their individual spends. Banks are making the best use of the data they possess with a view to improve on their services to However, today, institutions in the BFSI sector are increasingly striving to adopt a full-fledged data-driven approach that can only be possible with Big Data technologies. applications in three areas of financial services: asset management, banking, and insurance. The banking industry is among many industries which have massive and useful data about their customers but very few banks are utilizing this set of information to enhance the customer experience and using the data information to prevent fraud. Download Ebook Big Data In Financial Services And Banking Oraclenot require more grow old to spend to go to the books establishment as capably as search for them. IoT is how the data lake acquires all the usable data. By using intelligent algorithms, you can detect fraud and prevent potentially malicious actions. Industry experts believe that AI will transform nearly every aspect of the financial … Data warehouses are getting migrated to big Data Hadoop system using Sqoop and then getting analyzed. If you are looking for any such services, feel free to check our service offerings or you can email us at hdfstutorial@gmail.com with more details. With great trust on technology to handle the growing customer volumes and more transactions, the overall service level offered by the organizations has also enhanced. In this blog post, I am going to share some Big Data use cases in banking and financial services. Machine learning (ML) is becoming a commodity technology. Banks are making the best use of the data they possess with a view to improve on their services to customers. Big Data in Financial Services The banking sector is currently one of the top investors by industry in big data and business analytics solutions according to the IDC Semiannual Big Data and Analytics Spending Guide. According to TopPOSsystem, over 90% companies believe that Big Data will make an impact to revolutionize their business before the end of this decade. Predictive analytics in banking and financial services paired with artificial intelligence (AI) is on the verge of going mainstream. Value for the banks corresponds to applying the results of big data analysis real time and to make business decisions. Financial institutions have to leverage big data properly as per their compliance requirements and high levels of security standards. They come under regulatory body which requires data privacy, security, etc. The banks can make strategies based on these pointers: •  Customer segmentation based on their profiles, •  Cross-selling and Up-selling based on the customers’ segmentation, •  Improvement of customer service delivery on based on their feedbacks, •  Discovering the spending patterns and making customised offerings, •  Risk assessment, compliance & reporting that aid to fraud management & prevention. Systems that enable with Big Data can detect fraud signals further analyse them real-time using machine learning, to accurately predict illegitimate users and/or transactions, thus raising a caution flag. The use of big data in banking is growing astronomically. Based on the machine learning analysis, banks can come to know about the normal activities and transactions a customer does. Big data analysis presents with the customised analysis for each customer, thus improving their services and offerings. Especially when we talk about Banking and Financial sector, there is a lot of scope for big data, and they have started taking benefits of it. The big data flows can be described with 3 V’s. These 3 V’s are useless if a business does not have the 4’Th one which corresponds to Value. Financial institutions are making use of Big Data in big ways, from boosting cybersecurity to reducing customer churn, cultivating customer loyalty, and more through innovative and personalized offerings that make modern banking a highly individualized experience. Banking and Finance Services Industry is thriving to increase organizational success, gain profitable growth, and improve performance with the help of Big Data Analytics and Data Management. Technology has made the Banks to work in tandem to harness the data for intelligent decisions. Big data gives a comprehensive analysis of the entire business, which includes customer behavior and internal process. It is one of the greatest technological innovations that made banking easy and simplified banking services. Today, data analytics practices have made the monitoring and evaluation of vast amounts of client data including personal and security informant data-driven and other financial organizations much simpler. It further covers ROI, Big Data analytics, regulation, governance, security, and storage as well as obstacles and challenges that have made the industry what it is today. Image Source: SG Analytics. Retail banking estimated to lead Big Data adoption by 81 percent. Learn about the many benefits of big data analytics in the banking and financial services industry. Banking is an industry which generates data on each step, and industry experts believe that the amount of data generated each second will grow 700% by 2020. Oracle Enterprise Architecture, Improving banking and financial services performance with big data, White Paper (Feb 2016) Google Scholar 2. This gives an alarming ring tone to the banking firm to have layered security and services. That includes variety, volume and velocity. Improved fraud detection and prevention. With so many financial institutions in the market, it gets tough for the customer to decide which bank to transact with. In this I hope you liked these Big Data use cases for banking and financial services. You can check more about us here. Big Data Analytics can become the main driver of innovation in the banking industry — and it is actually becoming one. Compliance and Regulatory Requirements Financial services Segmentation is categorizing the customers based on their behavior. generate terabytes of data daily. 1. As the number of electronic records grows, financial services are actively using big data analytics to derive business insights, store data, and improve scalability. After an extremely successful launch, SMI are proud to present the 2nd Annual Big Data in Retail Financial Services Conference, 27th November, 2014, London. amzn_assoc_ad_type = "smart"; Hadoop, Spark, Casandra are just a … amzn_assoc_title = "My Amazon Picks"; Thanks to big data analytics, as the number of electronic records grows, financial services are actively using it to store data, derive business insights and improve scalability. Banks are moving now from the label of product centric to customer centric and so targeting individual customer is at most necessary. Big Data Analytics enabled Smart F inancial Services: Opportunities and Challenges Vadlamani Ravi 1,* [0000 -0003-0082-6227] and Sk Kamarudd in 1, 2 [0000 -0002-1887-7391] We list several areas where Big Data can help the banks perform better… Lloyds banking group will introduce the software across the Lloyds Bank, Halifax and Bank of Scotland brands early next year. Companies can also take data from customers’ social media profile and can do sentiment data analysis to know the habit and interest. News Summary: Guavus-IQ analytics on AWS are designed to allow, Baylor University is inviting application for the position of McCollum, AI can boost the customer experience, but there is opportunity. CloudMoyo helps companies in the banking and financial services industry to leverage the power of data analytics to make better-informed, data-driven business decisions. The Internet of Things in financial services will only increase the accuracy and speed of information gathering, as well as broaden the range of available insights. 3 Best Apache Yarn Books to Master Apache Yarn, Big Data Use Cases in Banking and Financial Services, 7 Business Benefits of Using Streaming Analytics, A Basic Guide To Artificial Neural Networks, 5 Top Hadoop Alternatives to Consider in 2020, Top Machine Learning Applications in Healthcare, Binomo Review – Reliable Trading Platform, 5 Epic Ways to Light Up this Lockdown Period with Phone-Internet-TV Combos, 5 Best Online Grammar Checker Tools [Compiled List]. to penetrate and transform how financial institutions are … But it can be difficult to find in-depth information on what financial services firms are really doing. Banks have been leveraging technological developments to decrease the time it takes to make a trade by introducing high frequency Most organizations that collect data from users want to know their customers and clients better. Thanks to the Internet and the proliferation of mobile devices and apps, today’s financial institutions face mounting competition, changing client demands, and the need for strict control and risk management in a … In fact, in every area of banking & financial sector, Big Data can be used but here are the top 5 areas where it can be used way well. Distribution of fraud schemes in banking/financial Services… Recently millions of customers’ credit/debit card fraud had in the news. The BFSI industry will obtain a better grasp of its needs, by aligning with the latest technologies like Big Data and the other global trends both internally into their operations and with customers.
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