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Technology 162 views Jun 22, 2018
Going hand-in –hand: Big Data and Banking

Banks are digitally transforming themselves at a fast pace with advanced branchless technology and contemporary services. The latest buzzword in the fintech industry are chatbots which have been adopted by almost all leading banks to make their customer service readily available to clients round the clock. So now, what is next? Big Data? But banks across the world are already using data analytics to upscale their business. Hover, tech experts believe that banks are still to realize the full potential of Big Data. While the BFSI sector creates enormous amount of data every second, is it able to mine this voluminous amount of information?

May be it is time, say some. Big Data that is defined by volume of data, variety of data and velocity of processing the data presents big opportunities for financial institutions. Many of these have even transformed themselves with the help of data mining that eventually helps in quick, easy and apt decision making. While, banks have been slow in the adoption of this technology due to the confidential nature of its data, the trend is seeing a positive change. Let’s take a look at some advantages of deploying Big Data techniques in banking:

  1. Risk Management

While all businesses need to engage in appropriate risk management, in banking industry this practice warrants extra attention. Big Data coupled with Business Intelligence can provide vital insights to banks on risks of approving loans to potential customers’ post evaluation of portfolios. Big Data can likewise help in early detection of fraud since it locates and presents data on a single scale making it simpler to mitigate the count of risks to a controllable number.

While improving the projecting power of risk models, big data also lowers system response times and increases effectiveness. Also, along with wide risk coverage, analytics also cause vital cost savings by generating more automated processes and precise predictive systems and less failure risk. It can positively impact fraud management, credit management, loans management, operational risks, and integrated risk management.

  1. Compliance

A heavy regulatory framework dictates the working of financial services so as to form a shield of protection against frauds and misuses. Big Data can play a crucial role in conforming adherence to regulations. It can identify and patch vulnerabilities, thereby strengthening and fortifying all materials of data governance and compliance. It can likewise help create baseline for ‘standard’ operations, which gives organizations a head begins in recognizing extortion and enables supervisors to spot consistence and administrative issues previously they turn into an issue.

  1. Customer Experienc

American worldwide management consulting firm McKinsey Company says that marketing productivity can be boosted by 15-20 per cent if companies use data and Big Data to make better marketing decisions. From ‘Product is King’, BFSI strategies now focus on ‘Customer is King’ and it has become important to focus on what they need and expect from a bank and financial institutions. To understand this, just a few customer snapshots won’t make the deal, a data hub needs to be created with ALL information about the customer and his interaction with the brand like personal data, transaction history, browsing history, service, and so on.

These customer insights generated by data-based analytics can empower the BFSI sector to segment customers and target them with appropriate material.

  1. Fraud Detection

Banks also, monetary administrations can and are already using Big Data analytics to distinguish between fraudulent activities and genuine business transactions. investigation and machine learning can both help determine standard movement in view of a client's history and differentiate it from unordinary conduct demonstrating extortion. The investigation can also suggest remedial activities, for example, blocking crooked transactions, deriving from actions taken in past. It will not only stop misrepresentation before it happens but will also improve profitability.

  1. Employee Engagement

What your employees feel about working in your company has a lot to do with what your end customers will experience. A higher level of satisfaction among employees will also extend to your customers and will push business growth. Big Data can help companies look at real-time data and not just annual reviews which are usually based on human memory. With the correct tools in place, companies can measure everything from individual performance, team work, inter-departmental interaction, and the overall company culture. When the data is related to customer metrics, it can also enable employees to spend less time on manual processes and more time on higher-level tasks.

Challenge

While there are many positives to making use of Big Data analytics in the BFSI sector, the huge amount of data that is being generated by a wide variety and number of sources poses a big challenge. A study says that, the digital universe is expected to reach 44 zettabytes (that's 44 trillion gigabytes) by 2020. Thus, imagine the amount of data that is going to be generated. Super software and computers will be needed to process such information that can halt legacy systems.

Conclusion

Once the sorting is done and useless data can be justifiable thrown out, the remaining crucial data can help banks grow from leaps to bounds. Besides, helping banks deliver better services to their customers, both internal and external, Big Data is also helping them improve on their active and passive security systems.

Big Data is already playing a role in the banking sector with many banks and financial institutions capturing customer related data for sentiment analysis, starting from social media websites to various market research channels.

Transactional analysis is being used to fathom spending patterns of customers, assess consumer behavior based on channel usage and consumption patterns and segment consumers depending upon the aforementioned attributes, and identify potential customers for selling financial products.

Most of these findings can be applied easily into fiscal systems of banks aiding them reinforce data security and avoid any type of attack. A combination of many such transactional and sentimental gauges can help banks arrive at a holistic decision making approach and thereby implement erudite machinery, a need of the hour for the banking sector.



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    348 Posted by manohar parakh
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    258 Posted by manohar parakh
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    232 Posted by manohar parakh
  • 26 Apr 2018
    Don't you feel almost all technological facilities are related to cloud these days? Guess what these services also include, the robotic technology. The day is not far when RaaS will turn out to be a multi-million-dollar industry. The global expenditure of robotics and robot related services will reach around $135.4 bn by 2019 which was $71 billion in 2015, according to an International Data Corporation report. John Santagate, research manager at International Data Corporation Manufacturing said, "With the rise in investment in AI development Robotic capabilities will keep on rising with the driving competition in order to bring cut the expenditure related to AI technology”.   According to a report titled 'Global Robotics Technology Market, 2013-2020 ‘, the universal robotics technology market is likely to reach up to $82.7bn by the 2020, recorded a CAGR of 10.11% during 2014-2020. The key factor that drives the robotic industry is the growing need for reduced labor costs of most established nations and the increasing instances of supported living style. More and more enterprises have started to enter the industry hoping to evolve and refine automation techniques and customer services.   Service robots provide a benefit by taking up industry-related tasks that are usually challenging and seem risky. Various everyday jobs are taken over by robots that are difficult and require much more human effort. Robots ensure and offer a higher level of accuracy and precision. The major sectors to use the Robotics and AI technology is Factories and manufacturing sectors, that develop merchandises on the methods of medications have been benefited from the accuracy that AI tech has offered.   Talking about the ever-increasing consumer world, a lot of cloud based enterprises like ESDS has / had started building chat bots that can be used in customer service processes in order to provide assistance to consumers in making correct use of products and helping them save a lot in the bargain. Industrial application of bots not only helps reduce cost, but it also initiates major transformations to take place for a better customer experience.   It has been proved that AI enabled RaaS is a boon to various verticals of manufacturing industry which includes manufacturing sector that requires hefty functional tasks in data storehouses. The RaaS model is now becoming a commonplace in the Agro sector. Agricultural robots and drones are used in a variety of tasks and they are expected to US $12 bn in next 5 years to come.   Talking about the healthcare industry, bots are able to perform tedious operations, they can interact with patients also check status of their health and suggest further appointments. Grouping of Artificial Intelligence and bot technology has surprised everyone already with the evolution of a bot called Sophia. All the data that is been taken by robots in different verticals and service sectors can be stored in cloud. Data analytics can be performed on the stored data and this enables businesses to increase productivity at a lower cost. It also helps build a smart enterprise link that let teams to focus only on their business related tasks.   A report by International Data Corporation stated that 30% of robotic applications which is based on commercial services will be in the form of a RaaS enterprise model, by 2019. This would definitely help reduce costs of robot deployment. The same report further predicts that more than 55% of robots will depend on cloud-based applications in order to define AI potentials and related applications, which will eventually lead to the formation of a AI based cloud market by around 2020.   The advent of the RaaS technology denotes a massive change in the service-based models in the technology sector. These models have a fast growth capability for adoption and offer an attractive value proposition to different industries and businesses. RaaS has the capability to develop new and improved enterprises prototypes.   A lot of RaaS providing industries like ESDS software solution Pvt. Ltd. can support and provide 24*7 support with incorporation of Artificial Intelligence technology and storage facilities used within industries. This helps cost cutting and also makes scaling of resources feasible with greater flexibility. With the rise in AI technology robots are more likely to get incorporated on cloud technology in a rapidly growing digital environment meant to craft an intelligent enterprise environment.
    169 Posted by manohar parakh
  • 18 Oct 2017
    Middle banking is the centralization of banking transactions done thru the individuals and banks as a whole. the whole financial institution and its skills are controlled under a unmarried surroundings.the india post has a larger center banking device than that of sbi, stated union it and communications minister ravi shankar prasad. the india publish modified into helped via way of tech big infosys to installation the middle banking answers connecting 1.5lakh post places of work with 20crore client payments in 2012. implementation of cbs is an vital part of authorities’s plan for it modernization.what's core banking?a patron can manipulate his/her financial institution account and carry out simple transactions like withdrawal, deposit, transfer from any department of the bank. in layman terms, it an everywhere,each time bank.the banking programs are deployed on the centralized server and are constantly up to date in actual time because the patron performs a transaction. with the advancement of generation and cutting-edge-day cloud computing, center banking website hosting has come to be less difficult and rate powerful.blessings of center bankingwithin the millennial generation, the decision for for core banking solution is immoderate. with the fast pace digital age, middle banking is a severe need of the monetary and credit score institutions. also, because of iot and cell banking cbs implementations is welcomed.the customers can display all their bank debts in one region and  can manage their cash as and at the same time as desired. a secure 24*7 banking facility is to be had. speedy payments via the usage of internet banking and cell banking is some other benefit of center banking.middle banking answers allow business business enterprise continuity for entities and clean analytics of records. a low rate going for walks shape assists in the investments to reach out to more customers and enlarge geographic reach. with transparency of transactions, file submissions to the government and distinctive regulatory our bodies like rbi becomes unchallenging.
    151 Posted by manohar parakh
  • 13 Nov 2017
    You may consider the Internet of Things as an environment where each and everything that surrounds you i.e.: objects like vehicles, flora, fauna, and people – are Things. The role that IoT plays here to the “things” is add digital interactivity amongst them. Sounds crazy, right?     This is exactly what could happen in the near future. IoT can take the Internet to another level, where web applications interact with each other and with people, also interaction between web applications and other countless objects in the physical world takes place. And physical world also means everything that you can imagine of like: instruments, electronic devices, smart devices, telecommunication enables devices, houses, transportation, medical devices and so on. And guess what all these are completely connected via internet!   Cloud computing and Internet of Things (IoT) are two different technologies that are already playing an important part of our lives. It is predicted that IoT might accelerate operation of the cloud computing technology, also will intensively advance predictions about consumer preferences, also modify the breadth of facilities that managed service providers can provide. The tons of GB’s of data generated by cities, needs to be stored, processed and accessed, which leads to rapid growth of IoT and this rapid data generation calls for association of technologies and also creates a connection between “things.” Here Cloud technology acts as a paradigm for data storage in large amounts and analytics on the data takes place. At the same time IoT is exciting in its own way, the innovation will derive by combining IoT with cloud computing.     Let’s talk about eNlight IoT, the eNlight enabled IoT has the potential to change the way we interact with our belongings. eNlight IoT is a managed cloud platform that lets connected devices easily and securely interact with cloud applications and other devices. eNlight IoT can support various devices, and can process and route sensor messages to other devices reliably and securely. With eNlight IoT, your applications can keep track of and communicate with all your devices, all the time, even when they aren’t connected. eNlight IoT makes it easy to use Node RED, to build IoT applications that collect, process, analyze, visualize and act on data generated by connected devices, without having to manage any infrastructure.   Feature of eNlight IoT:   Device Connection Management:   eNlight IoT allows you to easily connect devices to the cloud and to other devices. You can actually make your thing talk to you using eNlight IoT. Connecting your devices and interacting with them was never so easy.     Secure device Connection, data transfer & Access Control   eNlight IoT provides authentication, access control and end-to-end encryption throughout all points of connection, so that data is never exchanged between devices and eNlight IoT without proven identity.     Real-Time Data Management   With eNlight IoT, you can collect, filter, transform, and trigger upon device data on the fly, based on business rules you define. You can update your rules to implement new device and application features at any time. eNlight IoT makes it easy to use Node RED services for your device data. You can easily set real-time triggers and notifications on your device data on the fly.     Rich Analytics & Insights   With eNlight IoT, you can collect, analyze and visualize device data on our Dashboard. You can visualize data with various graphs and widgets. eNlight IoT makes it easy to use Node RED services for your device data to send data to various analytics tools and do real-time analysis of your device data.     The ideal eNlight IoT Use case:   Cloud computing and IoT combination will now enable monitoring utility and advance powerful processing of sensory data streams. For instance, data generated by smart devices can now be uploaded and stored on the eNlight enabled cloud, later on it can be used brilliantly for monitoring, analysis, generating insights and also for communication with other smart equipment. So the goal is to transform data to knowledgeable insights and be highly productive, and generate cost-effective action from those insights.   Ultimately eNlight IoT serves effectively as the most intelligent suite that improves decision-making and optimizes internet-based communication.  
    129 Posted by manohar parakh
  • 23 Apr 2018
    Big Data is basically sets of data which are large in volume and cannot be processed through some traditional application software. The term big data is not new as it has been around since a long time and there has been many concepts related to the term. Even if the concept is not new in the industry, there is a lot of confusion revolving the true meaning of what big data actually is. When you work on a particular principle and start collecting knowledge on the similar, you start generating data which will be useful for you in the future to analyze the data and get further insights. Before computers and the rise of internet, the transactions were recorded on paper and archive files which were fundamentally data. Today computers allow us to save whatever data we have on spreadsheets and organize them in the most efficient way. Since the emergence of cloud computing, it has offered the best technology with a wide range of applications for various purposes in the most cost effective way. It is almost like a match made in heaven for big data and cloud computing because there is a lot of data and only cloud computing can provide that kind of compute power to process the data. Whatever we do almost leaves a digital trail as we generate data whenever we are on the internet. As cloud computing is transforming IT, huge amount of compute power is needed with the help of internet to store and analyze this data. Cloud computing has brought such a change that it has reshaped the way computers are being used to process data. Cloud has made it very simple for data storage in comparison with traditional data storage. Cloud computing provides scalable resources on demand and it has changed the way data is stored and processed. This is a powerful approach to analyze data provided by cloud computing and has become vital in the growth of big data in multiple industries. The full potential of what cloud computing can offer is not yet been realized due to lack of expertise and thus many enterprises fail to realize what can be achieved through cloud computing. Due to not implementing ‘Big Data’ in businesses in the way it should be, organizations are not growing because of not analyzing the data available to them. Combination of big data and cloud computing will help organizations in business analytics and will also improve their decision making in important parts of the business. The world can benefit from this combo and can have huge analytics advantage to generate information which is ideal for business continuity. Let’s take a look at the opportunities organizations can achieve by combining big data and cloud computing: Agility The traditional systems have proved to be slower since storing data and managing it is time consuming and is a tedious process. Since the adoption of cloud by organizations, it has been providing all the resources to run multiple virtual servers in cloud database seamlessly within matter of minutes. Affordability Organizations have a budget when they wish to switch to a particular technology and in this case, cloud is a blessing which is a top technology under a budget. Companies can choose the services they want according to their business and budget requirements. Applications and resources which are needed to manage big data don’t cost much and can be implemented by enterprises. Only pay for the amount of storage space you use and no additional charges will be incurred. Data processing Apache Hadoop is a big data analytics platform which processes structured and unstructured data. Social media alone generates a lot of data from blogs, posts, videos and photos which is difficult to analyze under a single category. Cloud takes care of the rest by making the whole process easy and accessible to any enterprise. Feasibility Traditional solutions require extra physical servers in the cluster for maximum processing power and storage space but the virtual nature of the cloud allows to allocate resources on demand. Scaling is a great option to get the desired processing power and storage space whenever required. Big data requires high data processing platform for analytics and there can be variations in demand which would be satisfied by only the cloud environment. Challenges to Big Data in the Cloud environment Big Data generates huge amounts of data and it is complicated to manage this amount of data on a traditional system. It is also difficult to analyze this data on the cloud platform to extract only the important bits. While moving large sets of data, there is often sensitive information like credit and debit card details/ addresses which is a major security concern. Businesses face high security concerns when they have their data on cloud. Attackers seem to come up with new ways to breach into the system which dents a company’s reputation and leads to cloud abuse. Replication of data is vital in case of an event where there are chances of losing data. Analysis of data is not possible in such case. Conclusion Big Data and Cloud Computing is a fit combination which allows processing of huge amounts of data on a platform which is scalable and will meet the resources needed to analyze data. Obviously there are opportunities and challenges when it comes these 2 technologies but isn’t that a part of the IT field?
    124 Posted by manohar parakh