Haskell Indian Nations University Admissions Data

Effects of Air Pollution in Delhi - 1950 Words

Introduction Air is the ocean we breathe. Air supplies us with oxygen which is essential for our bodies to live. Air is 99.9% nitrogen, oxygen, water vapor and inert gases. Human activities can release substances into the air, some of which can cause problems for humans, plants, and animals. There are several main types of pollution and well-known effects of pollution which are commonly discussed. These include smog, acid rain, the greenhouse effect, and holes in the ozone layer. Each of these problems has serious implications for our health and well-being as well as for the whole environment. One type of air pollution is the release of particles into the air from burning fuel for energy. Diesel smoke is a good example of this†¦show more content†¦Data from continuous monitoring of air quality reveals that suspended particulate matter levels still far exceed stipulated standards, there is a significant downward trend as indicated in the following tables. Due to phenomenal growth in the number of motor vehicles Delhi and power generation based on a fired power stations, total amount on coal fired power stations, and total amount of pollutants received by the city is around 3000 tonnes as compared to 100 tonnes a decade ago. Sixty five percent of these pollutants are produced by motor vehicles. Annual average maximum, levels of SPM in Delhis air has increased from 7.6 times the permissible limit in 1987 to 16.7 time in 1995. The steep increase in vehicle population has resulted in a corresponding increase in pollutants emitted by vehicles. Petrol consumption has increased from 133 thousands tons in 1980-81 to 449 thousand tons in 1996-97 and HSD consumption from 377 thousands tons to 1,234 thousand tons during the same period. Two wheelers, which constitute 66% of the vehicles registered in Delhi, are the major source of air pollution. Thermal power plants contribute to 13% of air pollution. The main pollutants are stack emissions; fly ash generations and fugitive emission in coal handling. All thee thermalShow MoreRelatedThe Effects Of Air Pollution On Human Health Essay1381 Words   |  6 PagesObjectives 1. To establish the definition of air pollution and pollutants and determine their chemical nature. 2. To identify the causes of Air pollution 3. To define air pollution in India with respect to law as stated in the Indian Constitution. 4. To describe the Supreme Court interjection due to Delhi’s pollution and its results. 5. To assess the air pollution level in Delhi and compare the levels before and after Diwali 6. To find the level of pollution caused by different sources and the data supportingRead MoreThe Health Impacts Of Long Term Exposure Essay1157 Words   |  5 PagesThe purpose of this report is to determine and evaluate the health impacts of long-term exposure to PM2.5 in Delhi. Several possible self-protective solutions for people in Delhi will be discussed. Researches are done by critically comparing, summarizing and analyzing the data from academic articles. Delhi pollution control committee is proposed to be our client. The ambient PM2.5 in Delhi is 15 times higher than the WHO guidelines, which is identified as the most significant pollutants threateningRead MoreIndia s An Environmental Hazard Essay1071 Words   |  5 PagesIn early November 2016, Delhi, India faced an environmental hazard that put citizens in a dangerous position. The air was filled with toxins that made it almost impossible for people within the city to go about their daily lives. Everywhere, people asked who was responsible for the problem and whose job it was to implement protections in order to avoid future difficulties. For one to fully understand this issue, they must analyze the monumental growth of cities in the 20th century, previous environmentalRead MoreThe Effects Of Indoor Air Pollution On The Environment996 Words   |  4 PagesHumans, animals, and plants need air to survive, but how can they survive if the air that they breathe is polluted? Every cell in your body needs oxygen in order to live. The air that every one breathes contains oxygen and other gases. Hazardous chemicals escape into the environment to pollute the air from numerous human activities. The ever growing combustion of fossil fuels in the last century is responsible for the biggest progressive change in the atmosphere. Despite the other numerous environmentalRead MorePublic Health Organization, Central Pollution Control Board, World Bank Development Research Group3151 Words   |  13 PagesJournals, Government Reports and Publications, World Health Organization, Central Pollution Control Board, World Bank Development Research Group, Centre for Atmospheric Sciences, Government Of India Ministry Of Environment Forests, Development Centre Working Papers, The Indian Journal of Chest Diseases Allied Sciences, PNAS, Independent organizations. Word Count: 2378 What are the primary air pollution problems in your community (select and describe a setting that you are most familiarRead MoreStakeholder Analysis Of Delhi s Odd Even Policy1510 Words   |  7 Pagespolicy has directly or indirectly impacted a wide variety of people especially those living in Delhi. Due to the complexity of the demographic structure and transportation system in Delhi, this experiment has drew intense attentions from the public and brought pressure to the government. The citizens in Delhi were highly impacted by this drastic measure. Meanwhile, the high court in Delhi and the Delhi government played the key roles in determining and implementing the policy. It is crucial to understandRead MoreAir Pollution During The Industrial Revolution1580 Words   |  7 PagesAIR POLLUTION 1. Introduction 1.1. Air Pollution Air pollution has been a major problem throughout world for the past 5 decades i.e. a few years after the industrial revolution. There are two types of air pollutions a) Natural and b) Anthropogenic, of which the natural causes (volcanoes, forest fires and tornadoes) are not in the control of man (Mosley 2010). Anthropogenic air pollution on the hand is a type of anomaly in the atmosphere where foreign objects are released into the air entirely byRead MoreA Brief Note On The Consequences Of Pollution1467 Words   |  6 Pages The Consequences of Pollution Among the fourteen billion pounds of garbage produced across the globe annually, only a mere one to two percent of it becomes recycled, leaving the rest to be littered across the world’s oceans. To make matters worse, our freshwater supply is also polluted by oil spills and corroded pipelines. As if that was not enough, everyday our air becomes a mixture of chemicals and other harsh air pollutants that result in more damage to the earth. For our convenience, we managedRead MoreSaving The Future Generation : Talking The Business Model Essay3336 Words   |  14 Pagescreated with fresh water air and forest he might only able to see smoke concrete building and garbage. There is a serious problem which is needed to be solved as early as possible. The problem is not how polluted the cities are, the major problem is that we are not doing anything to save our environment. Garbage is there at all the places, it’s been collected by different municipal cooperation at different cities. It’s been collected and then dumped at other places. Water pollution is a serious issue inRead MorePublic Interest Litigation Of Delhi3237 Words   |  13 PagesAnuradha Garg M.Sc Environment Science and Resource Management 22nd November, 2014 Public Interest Litigation in Delhi Environmental pollution is the one of the greatest common international problem of this century. No country in this world has been left untouched with its harmful effects. India also, is one of the greatest polluters in today’s world. Pollution is nothing but the unwanted substances that are thrown, disposed or released in the environment causing serious impacts on our ecosystem

Plaintiff That Too In A Reasonable Manner †Myassignmenthelp.Com

Question: Discuss About The Plaintiff That Too In A Reasonable Manner? Answer: Introduction Psychiatric injury is something for which the damages are granted under tort of negligence. A leading case where the psychiatric injury was contested was the case of Annetts v Australian Station (2002) 211 CLR 317. In Annetts v Australian Station, the duty of care owed to the son of the plaintiff was established as the child died as a result of the mental harm which took place when he ran away. The plaintiff in this case had made a claim that they had received psychiatric injury as a result of the breach of duty of care of the defendant. However, the court did not uphold these claims and out rightly quashed the claims made by the plaintiff of this case (Sappideen, 2009). In this report, the case has been discussed and the side of the defendant has been taken. Apart from giving the facts of the case, the arguments raised and the decision of the case, the decision has been critically analysed to decide if the undertaken decision has been right. Facts of the Case The name of plaintiffs son was James Annetts who had departed from his home back in Aug 1986, which was in NSW and at that time, he was only 16 year old (Quizlet, 2017). He had left his home to go to WA for working with the defendant. Before James left for WA, his mother had a word with the defendant and asked about the working conditions at WA. She was assured by the defendant that his son would be properly supervised and was set to work in Flora Valley, where he would get a shared room and would be looked after in a proper manner (Federation Press, 2017). For seven weeks, James continued to work to work at Flora Valley. On Oct 13, 1986, James was sent to work at a place which was 100 kilometres away from his promised place of work, despite the earlier assurances to Jamess mother. On Dec 03, 1986, it came to light that James had disappeared and was believed to be in danger of injury/ death. Jamess parents, who were the plaintiff in this case, were informed about their son being missing on Dec 06, 1986 and that took over the phone where they were told that James ran away, by a NSW police officer. Upon hearing this tragic news, Jamess father collapsed and Jamess mother continued the telephonic conversation. On April 09, 1987, Jamess skeleton was discovered and after the examination of it, it was revealed that James has died due to hypothermia, exhaustion and dehydration on Dec 04, 1986. And he had died in a place which was quite far from the place where he was supposed to work, as he died in Gibson Desert (Federation Press, 2017). The pl aintiff blamed the defendant for the death of their son and also for the psychiatric injury which they sustained as a result of the tragic news (Health Law Central, 2017). Defendants Issues and Arguments From the very beginning, the employer denied the allegation made by the plaintiff and stated that a duty of care was not breached, which was only owed to James and so the claim of plaintiff that a duty of care was also owed to them was denied by the defendant. For establishing that a duty of care was not owed in this case, the defendant referred to the basics of negligence, and followed the procedure which is required to make a claim of negligence (Harvey and Marston, 2009). For making a case of negligence, there is a need to show that a duty of care was owed which was violated, and this violation resulted in a loss, which was not remote, and which was foreseeable in a reasonable manner, where the injury was in direct causation to the violation (Gibson and Fraser, 2014). The English case of Donoghue v Stevenson [1932] UKHL 100 was referred to here. In this case, the defendant was said to have owed a duty of care to the plaintiff due to the proximity of their relationship and the loss being reasonably foreseeable (Abbott, Pendlebury and Wardman, 2007). In the current matter, there was an absence of the psychiatric injury being reasonably foreseeable as the defendant could have never known that hearing this news; a psychiatric injury would b e caused as the death of James was also not reasonably foreseeable. Hence, only a duty of care could be shown towards James, owing to the proximity and relationship of employer employee but not towards the plaintiff of this case. Also, the duty of care towards James was fulfilled whereby the defendant provided safe working conditions and took so many steps to locate him when he doubted that James could be in danger (Austlii, 2017). Reference was also made to Caparo Industries plc v Dickman [1990] 2 AC 605, where the three fold risk was stated (Lunney and Oliphant, 2013). As per this test, there is a need to show that risk of harm was reasonably foreseeable, there was proximity between parties and the imposition of penalties would be fair (E-Law Resources, 2017). It has already been shown that a duty of care was not owed to the plaintiff. The risk of psychiatric injury was not reasonably foreseeable. And due to the lack of these two tests, the imposition of penalties cannot be deemed as fair (Austlii, 2017). The case of Wyong Shire Council v. Shirt (1980) 146 CLR 40 was also highlighted by the defendant for showing the foreseeability of risk of harm. As per this case, the view of a prudent person has to be considering for judging if the risk was reasonably present (Jade, 2017). In the present case, even a prudent person, let alone the defendant, could not have reasonably foreseen that after running away from the work, the employee would die after being lost in the Gibson Desert. This was because James was assigned a different work place and the worker was found dead at a very faraway place. So, this risk of harm was not reasonably foreseeable. Also, the psychiatric injury was not caused to James, for which a claim can be made against the defendant (Austlii, 2017). The proximity of the relationship and reasonable foreseeability was highlighted by Justice Deane in Jaensch v Coffey [1984] HCA 52. In this case, the judge stated that a person would be considered as having the capacity of foreseeing a specific thing once the particular situation was properly analysed. In this regard, the type of relationship on the basis of which the lawful duty is attached is to be considered from which the reasonable care has to be understood. And for these purposes, the interest of other people also had to be taken into consideration. Hence, on the basis of this case, the foreseeability of the loss and the nature of relationship are required to establish negligence (Swarb, 2015). In order to take into consideration the relationship between James and the defendant, the type of work which was given to James, had to be analysed (Robertson and Tilbury, 2016). The defendant owed an obligation of care towards James, only in context of his working conditions and the thing covered within his work and was not to be stretched beyond work. Eloping of James, which ultimately led to his untimely death, was not a thing which could be deemed as violation of duty of care of the defendant. James was the one who violated the obligation of care, towards himself. And in case the defendant is held liable for this, it would not be just as an employer cannot reasonably foresee if an employee would run away. Thus, the lack of foreseeability would mean no duty of care or its breach (Austlii, 2017). To establish psychiatric injury in this case, it has to be shown that this was a result of a direct perception or an abrupt fright which occurred right after the accident. The news of James disappearing was given to his parents in a step based method. This information was given over a period of time and at a distance from the accident place. So, there was an absence of things which could be stated as being immediate or a thing of shock. The plaintiff did not witness the starvation or the exhaustion of their child which could have caused a sudden shock. Sudden shock was something where the child immediately fell off the cliff. Hence, the element of shock was also not present to contribute to psychiatric injury, thus, defeating the claim of injury of the plaintiff (Austlii, 2017). Judgement of Court The unanimous decision of the Court of Appeal of the Supreme Court of Western Australia in this case remains a key decision till present date. The decision was delivered by Ipp J where he rejected the appeal of the plaintiff and stated that the defendant did not owe a duty of care towards the plaintiff as the psychiatric injury of the plaintiff was not something which could have been reasonably foreseen, nor was a duty of care owed by the defendant to the plaintiff. There was an absence of the shock element which could have resulted in a psychiatric injury as there was an absence of abrupt sensory perception, which had to result from the breached duty of care in temporal and physical way. For establishing a case of psychiatric injury, it had to be shown that the plaintiff was so distressful that the psychiatric injury was caused (Allens, 2017). And on the basis of these points and the arguments raised by the defendant, the Court of Appeals denied the appeal made by the plaintiff. This was because in common parlance, the risk of harm was not foreseeable in a reasonable manner in this case, and allowing a case of psychiatric injury to be made against the defendant, just because the parent lost their child was an unfair thing to do, for the defendant. There was a need to differentiate between a loss of child from an ordinary incident and a shocking incident to make a claim of recognized psychiatric injury. Also, there was a sheer lack of proximity between the plaintiff and defendant where the actions of one could have affected another in sense of time and space. The court also took into consideration that he occurrence of Jamess death and the psychiatric injury of the plaintiff was quite far to be blamed upon the duty of care violation. The court requested the plaintiff to accept the passing away of their son and that Jamess d eath was not the fault of the defendant. Ultimately, the appeal of the plaintiff was rejected due to the lack of element of negligence and the lack of duty of care of the defendant towards the plaintiff (Allens, 2017). Critical Analysis The decision was a remarkable one in the view of the writer, due to the fact that the court differentiated from the emotional burden of this case and gave a practical decision where they rightly upheld that the death of James could not have been reasonably foreseen by any of the parties, which even included the plaintiff of this case. No one could have guessed that James would run away and would meet such a horrific end. Had there been some signs where there was even a slight possibility of such happening, the defendant could have been made liable. But, the defendant did everything in his power to ensure James was safe in a general manner and upon a threat on Jamess life, he took special efforts to save him. The claim of psychiatric injury was a wrong one as a duty of care was only owed by the defendant to James and not to the plaintiff due to a lack of foreseeability, the lack of proximity and relationship between the two parties. In short, the defendant was rightly ruled in favour by the court, in this case. References Abbott, K., Pendlebury, N., and Wardman, K. (2007) Business Law. 8th ed. London: Thomson. Allens. (2017) 2001 Annual Review of Insurance Law - Duty of Care, General Tortious and Trade Practices Act Liability. [Online] Allens. Available from: https://www.allens.com.au/pubs/ari/2001/care.htm [Accessed on: 12/09/17] Austlii. (2017) Tame v New South Wales [2002] HCA 35; 211 CLR 317; 191 ALR 449; 76 ALJR 1348 (5 September 2002). [Online] Austlii. Available from: https://www.austlii.edu.au/cgi-bin/sinodisp/au/cases/cth/HCA/2002/35.html?stem=0synonyms=0query=Annetts%20v%20Australian%20Station [Accessed on: 12/09/17] E-Law Resources. (2017) Caparo Industries PLC v Dickman [1990] 2 AC 605 House of Lords. [Online] E-Law Resources. Available from: https://www.healthlawcentral.com/cases/tame-v-new-south-wales/ [Accessed on: 12/09/17] Federation Press. (2017) Tame v New South Wales Annetts v Australian Stations Pty Ltd. [Online] Federation Press. Available from: https://www.federationpress.com.au/pdf/Tame%20v%20New%20South%20Wales.pdf [Accessed on: 12/09/17] Gibson, A., and Fraser, D. (2014) Business Law 2014. 8th ed. Melbourne: Pearson Education Australia. Harvey, B., and Marston, J. (2009) Cases and Commentary on Tort. 6th ed. New York: Oxford University Press. Health Law Central. (2017) Tame v New South Wales; Annetts v Australian Stations Pty Limited [2002] HCA 35. [Online] Health Law Central. Available from: https://www.healthlawcentral.com/cases/tame-v-new-south-wales/ [Accessed on: 12/09/17] Jade. (2017) Wyong Shire Council v Shirt. [Online] Jade. Available from: https://jade.io/article/66842 [Accessed on: 12/09/17] Latimer, P. (2012) Australian Business Law 2012. 31st ed. Sydney, NSW: CCH Australia Limited. Lunney, M., and Oliphant, K. (2013) Tort Law: Text and Materials. 5th ed. Oxford: Oxford University Press. Quizlet. (2017) Torts B Lecture #1--Pure Psychiatric Harm. [Online] Quizlet. Available from: https://quizlet.com/45679268/torts-b-lecture-1-pure-psychiatric-harm-flash-cards/ [Accessed on: 12/09/17] Robertson, A., and Tilbury, M. (2016) Divergences in Private Law. Oxford: Hart Publishing. Sappideen, C., at al. (2009) Torts, Commentary and Materials. 10th ed. Pyrmont: Lawbook Co, pp. 255-63. Swarb. (2015) Jaensch v Coffey; 20 Aug 1984. [Online] Swarb. Available from: https://swarb.co.uk/jaensch-v-coffey-20-aug-1984/ [Accessed on: 12/09/17]

Big Data for Fraud Detection in Banking Sector - Free Samples

Question: Discuss about the Big Data for Fraud Detection in Banking Sector. Answer: Introduction The detection of fraud in banking sector is an important part to eliminate risks of any cyber-attack or data breach. Banks are often vulnerable to fraud and this affects banks and customers (Flood, Jagadish and Raschid 2016). Most of the frauds in banking sector occur due to either human negligence or any malpractice or system defect. Frauds in banking sector impact customers and bank itself in a very negative way because both banks and customers can lose sensitive data and money. Nowadays, big data analytics has emerged as a game changer in every sector and it provides a more reliable and flexible usage in working of every sector (Fuschi and Tvaronavi?ien? 2014). Banking sector has now started to adopt big data analytics for its operations due to its usefulness, reliability and speed. The purpose of this report is to analyze big data use in banking sector and how big data analytics help banking sector to detect fraud. The outline of the report is data collection and storage system, consumer-centric product design, recommendation system and business continuity plan in case of power outage. The data in banking sector collected are credit card usage details, personal emails sending and receiving or account details or any other regular actions on a daily basis. The data collected are not only from internal source of banking sector but also from external sources which sometimes requires permission from third party. These sources are internet based navigation sites such as social media, Yahoo, Google or Bing. Google and Yahoo provide Gmail and Yahoo mail respectively (Srivastava and Gopalkrishnan 2015). The data are categorized into two types and they are primary data and secondary data. Primary data are information about employees, their head supervisors, managers, senior managers and customers, which are collected for proper functioning of banking sector. Secondary data are information of internal and external behavior and working of banking sector which are collected for different purposes and used for betterment of banking sector (Kim, Trimi and Chung 2014). Both types of data are in the form of structured, semi-structured or unstructured data. Therefore, they are arranged in orderly manner to access and operate easily on each form of data. The data in banking sector are unstructured data mainly and they are complicated to use in its initial form. Big data deals with this type of data and in banking sector, unstructured data are either machine or human generated. Machine generated unstructured data are scientific data or photographs and videos such as security or surveillance photos or images. Human generated unstructured data are internal texts within document files, logs, credit card or debit card details and emails, and website content (Raju, Bai and Chaitanya 2014). The data collection is through various sources are then mined that is data mining is done on the collected data. Data mining is exploring and analyzing of collected data to find data suitable for different purposes in banking sector. Data mining technique is used for five major categories of banking sector. They are customer retention, automatic credit card approval, fraud detection in banking sector, marketing and risk management. Data after data mining is used mainly for risk management and fraud detection in banking sector (Pouramirarsalani, Khalilian and Nikravanshalman 2017). This is explained as when data is stored in storage then big data has features of protecting thes e data from going into hands of fraudsters. Storage system Banks have massive amounts of data which needs to be stored in an efficient way. The new storage systems in banking sector for big data provides solutions and they are reconstructing the backup systems with improved performance that will not change the existing backup routine. The second solution is building a Disaster Recovery (DR) system that will help in an emergency case such as disaster or power outage. The third solution is managing data lifecycle for improvement of data utilization efficiency (Chitra and Subashini 2013). The explanation for first solution is to upgrade physical tapes from existing Disk-to-Tape (D2T) mode to the new Disk-to-Disk-to-Tape (D2D2T). The new tape provides more reliability and space to store data of size more 9TB and has high backup speed. The description of second solution is new Disaster Recovery system which is built after upgrading local backup system using tape. The Disaster Recovery system is used for storing data at different location in banking sector. The full back up in first solution using tapes is further stored in storage system that is Disaster Recovery system (Jones, Aggarwal and Edwards 2015). The storage is done by identifying unique blocks of huge data and store in Disaster Recovery system. The next backup is done to match the unique block with the blocks stored in the system to destroy duplicate data and then save all unique data. The leftover data is again checked so that no data is left vulnerable to any fraud. The left over data is also checked to analyze if any data can be effective for future purpose. The third solution is that the data is processed and stored on peripheral system and near-line data (twenty to thirty days old) is backed up regularly and stored on disks (Rao and Ali 2015). These data is tested for integration and effectiveness and to recover if any fault occurs. The long- term data (ninety days old or older ) is backed up regularly and stored on physical tapes. Both the data is then stored at different locations in Disaster Recovery system. This new storage system solution helps in better backup performance, recovery process is quick, and data storage is multi-level. Consumer-centric product design The long-term relationships with customers will require fulfilling demands and needs of customers. This is achieved through customer relationship management (CRM) systems. Customer relationship management is used by organizations to optimize contact with customers and build long-term relationships (Elgendy and Elragal, 2014). The various ways are telephone calls or emails to attract and retain customers. Customer relationship management system is based on infrastructure of customer data and information technology. Electronic customer relationship management systems provides all ways of communication with the customers. The ways are sales, delivery, email, online marketing and purchasing, online banking or many other online services. Customer relationship management system in banking sector is achieved by maintaining relationships with existing customers and creating relationships with new customers (Dalir et al. 2017). The benefits are providing better service to existing and new cus tomers and identification of specific values related to each sector of the business environment and existing or new customers. The other are dividing different market segments to improve long-term relationships with target customers and service fees which is charged increases revenue for banking sectors. The additional benefits are implementation of this system helps in increasing customer satisfaction and their loyalty and interest rates are increased to attract more customers (Baesens, Van Vlasselaer and Verbeke 2015). The seventh one is online advertising to attract customers and increased effectiveness and classification of customers. Electronic customer relationship management system in banking sector has a structure which is based on two factors and they are trust and satisfaction. They are commitment, loyalty, customer retention, and recommendation willingness. The other factors which construct the system through customers point of view are information, convenience and communication channel (Srivastava and Gopalkrishnan 2015). Trust is important for customers and bank relationship and the trust is referred to protection of every individuals bank account details and credit card or debit card details. Customer satisfaction is a quality in bank and customer relationship that will help them to trust on banks. Customer satisfaction in bank is very important to retain existing customers. Commitment is to partner close relationship with customers for valuable effort. Loyalty provides future benefits to banking sector even when there is a strong competition (Moro, Cortez and Rita 2015). Loyalty is a commitment to banks from customers to deal with them. Loyal customers will also recommend particular banks to their relatives or customers. Customer retention is important as exiting customers are more profitable than new customers. Therefore, fulfilling needs of existing customers is more important. The above factors help customers to willingly recommend services of bank to others as they are satisfied with services of bank. Information is correct, accurate or updated are not is necessary for the structure of the system. Convenience is important as customers will come after considering location of bank (Greenberg 2014). Geographic location of bank with working hours and others are included in the system. Communication channel like mobile, ATM, text, e-mail are used by customers to know bank services. Recommendation System Recommendation system is used as a tool in banking sector to help customer by giving service when bank employees are not available on a particular time. Recommendation system provides precise and timely information to customers. The system is virtual consultant to customers providing better information and services (Ravi and Kamaruddin 2017). The recommendation system can be explained by the following process. The system analysis provides specifications that are authenticated with username and password for logging into system and questionnaire type survey for the user regarding product interest. The next two specifications are giving advice to user after the completion of interview and when there is query regarding search engine, explanation term should be there in the search engine (Lin et al. 2015). The last two specifications are to provide answers by the expert to questions by the customer and also update the knowledge base in system (Davenport and Dych 2013). The system design c ontains human expert, knowledge acquisition facility, knowledge base, inference engine, working memory, user interface and the user. This is the system bank follows in recommendation system. Recommendation system is tested using black-box and white-box testing to know that the system is properly functioning and also integrated (He, Tian and Shen 2015). The testing is also done to ensure satisfactory working of every feature. The testing is done on the database so that the data can be accessed with respective attributes and required data can be fetched. The application is important in recommendation system because it provides a platform for direct communication of user and banking sector (Ng and Kwok, 2017). This is a place where user can register and then they can login with username and password. This is a place where user can get details about banking process in about us section and also contact details of bank in contact us section. The system design is implemented in application and the working of system structure is defined in application. These are the features and functions of recommendation system and this helps in clearing customers doubts and queries. The custo mers can also give feedback in recommendation system (Flood, Jagadish and Raschid 2016). The recommendation system in banking sector are developed using information system and are also called expert system in other sectors. Business continuity plan Survival of online business in case of power outage or any other disasters is a major discussion for any banking sector. The business continuity plan has four steps in banking sector and they are business impact analysis, risk assessment, risk management and monitoring and testing. The first step is business impact analysis that helps to identifies critical business functions and impact of loss of functions for example operational and financial on banking sector. This process is analyzed by senior management representatives and board of directors. The business impact analysis is required at times when there is disruption in power outage and any disaster (Harvard Business Review, 2017). The second step is risk assessment which helps to determine cause of power outage or other disasters. Senior management analyzes the risk through risk assessment processes and then develop program to tackle the risks. The third step is risk management which is important to develop and maintain business continuity plan in baking sector. Risk Management in banking sector is based on first two steps that is business impact analysis and risk assessment (West and Bhattacharya 2016). These realistic events can be formally declared and updated by senior management annually to employees in banking sector. The fourth step is monitoring and testing which is a confirmation to business continuity plan in banking sector that all the steps are revised and evaluated without overlooking any significant changes. This step is finally evaluated by senior bank management (Forbes.com 2017). This is when they can commit necessary workforce, budget and time to test the program for validation of business continuity plan in an event of any disruption in banking sector. Conclusion The above discussions conclude that fraud detection in banking is a very important process and big data analytics is used in banking sector for fraud detection techniques. The discussions shows that the data collection system in banking sector is complicated as there are huge data sets in banking sector. The data collected need to be stored in places where there is security and proper storage place to be chosen. The actions to be taken on collected data that is services to customers and system to recommend customers are also discussed. The business continuity plans on the basis of possible disruptions were the key points of this report. The report overall concludes that implementation of big data and big data analytics is necessary for banking sector. Big data and big data analytics are used to collect data and store and finally use for various purposes in banking sector. Banking sectors regularly produce huge data that are sensitive and can be controlled through big data and big dat a analytics. Therefore, it can be concluded that big data and big data analytics can help banking sector to detect fraud and prevent the risks of fraud using various processes. References Baesens, B., Van Vlasselaer, V. and Verbeke, W., 2015.Fraud analytics using descriptive, predictive, and social network techniques: a guide to data science for fraud detection. John Wiley Sons. Chitra, K. and Subashini, B., 2013. Data mining techniques and its applications in banking sector.International Journal of Emerging Technology and Advanced Engineering,3(8), pp.219-226. Dalir, M., Zarch, M.E., Aghajanzadeh, R. and Eshghi, S., 2017. The Role of e-CRM in the Quality of Customer-Bank Relationship.Human Resource Management,4(2), pp.12-22. Davenport, T.H. and Dych, J., 2013. Big data in big companies.International Institute for Analytics,3. Elgendy, N. and Elragal, A., 2014, July. Big data analytics: a literature review paper. InIndustrial Conference on Data Mining(pp. 214-227). Springer, Cham. Flood, M.D., Jagadish, H.V. and Raschid, L., 2016. Big data challenges and opportunities in financial stability monitoring.Banque de France, Financial Stability Review,20. Flood, M.D., Jagadish, H.V. and Raschid, L., 2016. Big data challenges and opportunities in financial stability monitoring.Banque de France, Financial Stability Review,20. Forbes.com. (2017).Forbes Welcome. [online] Available at: https://www.forbes.com/sites/tomgroenfeldt/2013/06/11/banks-use-big-data-to-understand-customers-across-channels/#22286a453218 [Accessed 9 Dec. 2017]. (Forbes.com, 2017) Fuschi, D.L. and Tvaronavi?ien?, M., 2014. Sustainable development, Big Data and supervisory control: service quality in banking sector.Journal of security and sustainability issues,3(3), pp.5-14. Greenberg, M.R., 2014.Protecting seniors against environmental disasters: From hazards and vulnerability to prevention and resilience. Routledge. Harvard Business Review. (2017).How Banks Are Capitalizing on a New Wave of Big Data and Analytics - SPONSOR CONTENT FROM COGNIZANT. [online] Available at: https://hbr.org/sponsored/2016/11/how-banks-are-capitalizing-on-a-new-wave-of-big-data-and-analytics [Accessed 9 Dec. 2017]. (Harvard Business Review, 2017) He, W., Tian, X. and Shen, J., 2015. Examining Security Risks of Mobile Banking Applications through Blog Mining. InMAICS(pp. 103-108). Jones, S., Aggarwal, A. and Edwards, H., 2015. Creating Futures Through ResearchMeeting Challenges, Embracing Opportunities Delivering Impact. Inaugural Collaborative Research Conference, INtel Institute of Higher Education, Nairobi. Kim, G.H., Trimi, S. and Chung, J.H., 2014. Big-data applications in the government sector.Communications of the ACM,57(3), pp.78-85. Lin, C.C., Chiu, A.A., Huang, S.Y. and Yen, D.C., 2015. Detecting the financial statement fraud: The analysis of the differences between data mining techniques and experts judgments.Knowledge-Based Systems,89, pp.459-470. Moro, S., Cortez, P. and Rita, P., 2015. Business intelligence in banking: A literature analysis from 2002 to 2013 using text mining and latent Dirichlet allocation.Expert Systems with Applications,42(3), pp.1314-1324. Ng, A.W. and Kwok, B.K., 2017. Emergence of Fintech and cybersecurity in a global financial centre: Strategic approach by a regulator.Journal of Financial Regulation and Compliance,25(4), pp.422-434. Pouramirarsalani, A., Khalilian, M. and Nikravanshalmani, A., 2017. Fraud detection in E-banking by using the hybrid feature selection and evolutionary algorithms.IJCSNS,17(8), p.271. Raju, P.S., Bai, D.V.R. and Chaitanya, G.K., 2014. Data mining: Techniques for enhancing customer relationship management in banking and retail industries.International Journal of Innovative Research in Computer and Communication Engineering,2(1), pp.2650-2657. Rao, K.V. and Ali, M.A., 2015. Survey on Big Data and applications of real time Big Data analytics. Ravi, V. and Kamaruddin, S., 2017, December. Big Data Analytics Enabled Smart Financial Services: Opportunities and Challenges. InInternational Conference on Big Data Analytics(pp. 15-39). Springer, Cham. Srivastava, U. and Gopalkrishnan, S., 2015. Impact of big data analytics on banking sector: Learning for Indian banks.Procedia Computer Science,50, pp.643-652. Srivastava, U. and Gopalkrishnan, S., 2015. Impact of big data analytics on banking sector: Learning for Indian banks.Procedia Computer Science,50, pp.643-652. West, J. and Bhattacharya, M., 2016. Intelligent financial fraud detection: a comprehensive review.Computers Security,57, pp.47-66.