5 applications of Artificial Intelligence that are disrupting the banking sector – IBS Intelligence

5 applications of Artificial Intelligence that are disrupting the banking sector By Joy Dumasia

The adoption of AI in different enterprises has increased due to the COVID-19 pandemic. Since the pandemic hit the world, the potential value of AI has grown significantly. The focus of AI adoption is restricted to improving the efficiency of operations or the effectiveness of operations. However, AI is becoming increasingly important as organizations automate their day-to-day operations and understand the COVID-19 affected datasets. It can be leveraged to improve the stakeholder experience as well.

Artificial Intelligence (AI) has been around for a long time. AI was first conceptualized in 1955 as a branch of Computer Science and focused on the science of making intelligent machines machines that could mimic the cognitive abilities of the human mind, such as learning and problem-solving. AI is expected to have a disruptive effect on most industry sectors, many-fold compared to what the internet did over the last couple of decades. Organizations and governments around the world are diverting billions of dollars to fund research and pilot programs of applications of AI in solving real-world problems that current technology is not capable of addressing.

Artificial Intelligence enables banks to manage record-level high-speed data to receive valuable insights. Moreover, features such as digital payments, AI bots, and biometric fraud detection systems further lead to high-quality services for a broader customer base. Artificial Intelligence comprises a broad set of technologies, including, but are not limited to, Machine Learning, Natural Language Processing, Expert Systems, Vision, Speech, Planning, Robotics, etc.

The following are 5 applications of Artificial Intelligence that are disrupting the banking sector:

Automated advice is one of the most controversial topics in the financial services space. A robo-advisor attempts to understand a customers financial health by analyzing data shared by them and their financial history. Based on this analysis and goals set by the client, the robo-advisor will be able to give appropriate investment recommendations in a particular product class, even as specific as a specific product or equity.

Chatbots deliver a very high ROI in cost savings, making them one of the most commonly used applications of AI across industries. Chatbots can effectively tackle most commonly accessed tasks, such as balance inquiry, accessing mini statements, fund transfers, etc. This helps reduce the load from other channels such as contact centres, internet banking, etc.

AI is instrumental in helping alternate lenders determine the creditworthiness of clients by analyzing data from a wide range of traditional and non-traditional data sources. This helps lenders develop innovative lending systems backed by a robust credit scoring model, even for those individuals or entities with limited credit history. Notable companies include Affirm and GiniMachine.

One of AIs most common use cases includes general-purpose semantic and natural language applications and broadly applied predictive analytics. AI can detect specific patterns and correlations in the data, which legacy technology could not previously detect. These patterns could indicate untapped sales opportunities, cross-sell opportunities, or even metrics around operational data, leading to a direct revenue impact.

AI can significantly improve the effectiveness of cybersecurity systems by leveraging data from previous threats and learning the patterns and indicators that might seem unrelated to predict and prevent attacks. In addition to preventing external threats, AI can also monitor internal threats or breaches and suggest corrective actions, resulting in the prevention of data theft or abuse.

ALSO READ: Applications of Artificial Intelligence In Banking Q1 2022

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5 applications of Artificial Intelligence that are disrupting the banking sector - IBS Intelligence

Is artificial intelligence the future of writing? – The Rude Baguette

Its not new that the emerging artificial intelligence technology aims to take over the writing space.

High-end and intermediate writers have expressed cynical views and even fears over the AI writing software introduction.

For proponents of the AI writing application, its not so! According to them, the concept behind the creation is to help lessen the workload of writers.

In the meantime, the number of AIs has surpassed expectations. From small companies to big names in tech, AIs are attempting to become the next big thing for content marketing.

In fact, due to the improvement in its machine language and data analytics, some companies prefer AI content marketing.

This begs the question, is AI the future of writing? Or will it replace the human writing form?

Read on!

If youve been wondering what goes on behind every AI, its simple, a machine language.

AI writing tools usenatural language generationto produce written words from mere data. You just input data in, and the rest is history.

An AI is effective when a large amount of data needs conversion into written language that anyone can understand.

Scientists didnt stop at a mere natural language generation; more work began after the discovery in 2016.

They rebranded and created a more advanced AI that didnt need data labeling while saving time and money.

In May 2020, another model was created. Its called OpenAIs GPT-3 (Generative Pre-trained Transformer-3).

This new and advanced machine language is the largest neural network globally. The machine has a model with over 175 million parameters.

The GPT-3 is different from other AIs because it processes information like the human thinking faculty.

It executes tasks like answering questions, filling in blanks, publishing articles, writing songs, jokes, and even questions about the philosophical aspect of life!

There are even better and more advanced ALs being created. In particular, some companies have copied the language system of the OpenAIsGTP-3and made better improvements.

In May 2020, Google launched a new chatbot called LAMDA. Its designed to hold meaningful, emotional, and intellectual conversations.

Whats more, Beijing has attempted to create the first living AI. In June 2020, the Beijing Academy of Artificial Intelligence (BAAI) launched a new AI calledWu Dao 2.0.

The AI gave life to its first virtual student,Hua Zhubingto write songs and codes and possess a large memory.

This has become a lingering question in every writers mind and probably a writers worst fear, especially writers in the business ofcontent writing or copywriting.

While AI technology keeps advancing, its arguably not going to be the future of writing.

Writers are more skilled in capturing the essence and reader perception. Itll take years of research for any AI to exhibit such traits. An AI cant write emphatically as a human would.

Although AI has shown great dexterity and expertise in writing, there are still major gaps that cant be filled.

Below are a few reasons why writers need not worry about AIs for now:

An AI lacks the uniqueness human writers bring to their articles. Its an intricate factor that distinguishes the pro from the amateur.

AIs may be perfect for data gathering and analyzing complex words but possess poor creative analytics.

They poorly express themselves due to a lack of cognition and emotion. Only humans can process such complexities.

AIs produce whatever you run into them. The process is like garbage in garbage out.

The workload still falls on a human to carefully reread and edit AI-generated articles.

Yes, it might be difficult to detect an AI-written article. However, AIs struggle to compose coherent and engaging content to captivate readers. Engagement is the footstone of every good content.

Writers are more skilled in capturing the essence of every article. It may take years of research for AIs to exhibit such traits.

If theres one thing an AI greatly lacks in information presentation, its a lack of direct and multiple evaluations.

For instance, an AI cant interpret a proverb or an idiom. They arent recognizable in data analysis.

Also, they cant differentiate between the linguistic complexities, like when not to use offensive words.

For now, human writers have nothing to worry about. AIs and humans can coexist symbiotically without one dominating the other.

Though many believe its economical and more reliable than human writers. However, the barrier to the above statement is the cost of an AI to start up. Only big tech companies can afford excellent and effective AI writing tools.

The risk-on human writers are quite low. However, it shouldnt stop you from honing your skill!

Sam Altman, CEO of Open AIs, in a tweet published in early June 2021, stated that AIs might likely affect physical jobs more than remote jobs such as coding, writing, administrative jobs, and co.

Whether we like it or not, AIs are here to stay. We cant fight them. However, we can create a means to incorporate them into the physical fold without any job losses.

They immensely contribute to accelerating a writers process and simplifying the workload.

We already use low-resource AIs like Grammarly and plagiarism checkers. Still, human editors and proofreaders are thriving.

Photo by Reports Monitor from Flickr

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Is artificial intelligence the future of writing? - The Rude Baguette

SparkCognition Government Systems (SGS) Brings AI Readiness to the Department of Defense Through Joint Artificial Intelligence Center Award – PR…

SGS awarded Data Readiness Artificial Intelligence Development Program, a potential five-year $241.6M agreement for advancing use of AI in defense

AUSTIN, Texas, April 12, 2022 /PRNewswire/ --SparkCognition Government Systems (SGS), developing trusted artificial intelligence (AI) solutions for defense and national security, announced it has been awarded to the Data Readiness Artificial Intelligence Development (DRAID) Program through the Joint Artificial Intelligence Center (JAIC). The DRAID Program is a potential five-year, $241.6 million basic ordering agreement (BOA) focused on enabling the Department of Defense (DoD) to optimize its vast data resources to leverage AI to enhance its mission effectiveness.

"We are honored to have been selected for this critical initiative, building on our commitment to helping the DoD solve their most pressing challenges," said Logan Jones, President and General Manager of SGS. "Our leadership in AI, machine learning, natural language processing, and computer vision will be instrumental to our work with JAIC, advancing the DoDs use of diverse data sets and driving innovative AI applications across the department."

The goal of the DRAID program is to ensure DoD AI readiness, with a special focus on preparing data for building AI systems. As an awardee of the DRAID contract, SGS will apply its patented AI, machine learning, and natural language processing technologies to the challenges JAIC will focus on solving through the DRAID vehicle, including data cleanliness and readiness, and delivering data science techniques that lead to actionable insights. This ultimately enables the DoD to deploy solutions like SGS' offerings, which empower mission readiness, enhance decision making, and deliver efficient operations.

To learn more about SparkCognition Government Systems, visit http://www.sparkgov.ai.

About SparkCognition Government Systems SparkCognition Government Systems (SGS), a wholly-owned subsidiary of SparkCognition, is the first artificial intelligence (AI) company devoted entirely to government and national defense. By developing and operationalizing next-generation AI-powered systems, SGS enables government organizations to meet the needs of their most pressing national security missions. SGS advances government operations by analyzing complex data to inform and accelerate intelligent decisions, applying predictive and prescriptive analytics to improve logistics, deploying autonomy technology for power projection systems, using AI and machine learning for large-scale processing of unstructured data, and more. For in-depth information about SGS and its offerings, visit http://www.sparkgov.ai.

Contact Info Cara Schwartzkopf Communications Manager [emailprotected] 251-501-6121

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SparkCognition Government Systems (SGS) Brings AI Readiness to the Department of Defense Through Joint Artificial Intelligence Center Award - PR...

Artificial intelligence keeps the spirits up during the pandemic – The Australian Financial Review

The days when technology strategy was the sole preserve of IT specialists have long gone, and businesses are looking to have digital leaders across departments and dotted around the boardroom table.

However, that doesnt mean that business tech has become homogenous. There is significant competitive advantage that comes from doing things smarter than rival operators.

ADAPTs director of strategic research Matt Boon says well-established retailers are turning to tech solutions after their business models were upended by the pandemic.

It is always remarkable to me as I go around the world that companies are at different stages of digital transformation, in terms of their migration to the cloud, and in terms of their usage of data, CEO of global tech services giant Cognizant Brian Humphries tells The Financial Review.

In basic terms, every company in the world is trying to accelerate growth, protect themselves from next-generation companies, trying to upsell and cross-sell, and trying to maximise customer and employee satisfaction.

Big companies know that whether they are in insurance or healthcare, there are start-ups that are so disruptive, that they have to become much more digital if they want to survive.

Humphries was in Australia to visit local clients, including Telstra and Australia and New Zealand Banking Group, and says across industries, the emergence of easily accessible software-as-a-service, with AI-based functionality on tap means companies have adopted a fail fast culture, more associated with start-up disruptors.

Humphries says even organisations that have previously been tech laggards have had a change of attitude in recent years.

Ill probably have met 15 to 20 clients in Australia and New Zealand on my visit and every single one of them no longer thinks of IT as a cost, Humphries says.

They think of it as an investment and as core to the business; it is now the difference between winning and losing.

For a report entitled Embracing the Future: Top 12 Strategic Priorities for 2022, technology research firm ADAPT conducted a study based on interviews with over 650 senior Australian executives about their attitudes towards tech investment and how technology is being deployed.

Like Coles adoption of software to streamline and prioritise stock ordering, ADAPT found a desire to become data driven and improve operational effectiveness were the key aims of most of the execs surveyed.

Well-established retailers saw their business models upended by the pandemic, and have been compelled to re-imagine business functions and develop new product and service lines only possible through accelerated digitisation programs, ADAPTs director of strategic research Matt Boon says.

Those leading the pack now realise digital transformation isnt an end goal, but a constant state of flow needing executive support.

Hampering efforts across Australian businesses to achieve these aims of being data-driven, according to ADAPT, are a number of main hurdles. First, data often resides across disparate systems and applications, making it hard to analyse effectively.

There is also a general lack of sufficient data skills in many organisations, a lack of executive ownership from non-technology focused business leaders and insufficient budget dedicated to making it happen.

Boon says that while 60 per cent of Australian IT leaders have indicated a focus on developing IT culture in their organisations, ADAPT considers just 43 per cent of C-suite executives and board directors to be digitally savvy.

Companies need to adopt emerging technologies, but are being held back by low levels of digital literacy from the boardroom all the way down through an organisation, Boon says.

IT leaders are right to prioritise the development of their organisations digital savviness, as the success of new initiatives in the future depends upon their teams willingness to support them.

While a broader shift of systems on to cloud-hosted infrastructure, and the installation of myriad systems to try and protect against cyber security threats are responsible for a significant portion of tech budgets across all companies, ADAPTs study shines a light on the relatively nascent technologies also being trialled.

Machine learning, artificial intelligence and robotic process automation are the most common of these areas to be attracting funding, ahead of chatbots, blockchain, the internet of things (IoT) and virtual or augmented reality.

Australian companies including Lendlease and Newcrest Mining have both spoken in recent times about how the combination of IoT sensors with cloud-based systems and virtual and augmented reality have allowed them to reap significant benefits from building digital twins.

These virtual representations of real-world conditions at their various assets, such as building sites or gold mines, can be analysed from the safety of an office, with potentially lucrative benefits.

Newcrest estimates that a digital twin of its flagship Cadia mine in NSW could unlock hundreds of millions of dollars of untapped value a year, through more efficient maintenance and enabling the mining of more gold.

Mikko Krkkinen, the CEO and co-founder of Relex Solutions, the software firm helping Coles get the right drinks on its liquor store shelves, says that while his company focuses on the retail sector, the focus on supply chain planning and the use of AI and machine learning-based technology is relevant across industries.

Were seeing a need for retailers to be able to analyse and integrate unprecedented amounts of data across various parts of their business, and we know AI to be a powerful tool for optimising wider parts of the business, Krkkinen says.

The pandemic made retailers, along with everyone else, realise how unpredictable the world has become.

Its impossible to predict every twist and turn the market will take in the future, whether near or distant. Companies committed to long-term future success understand this and invest in solutions that help them remain agile and adaptive in their approach and plans, regardless of how the market evolves going forward.

Top 10 business priorities:

(Source: ADAPTs Embracing the Future: Top 12 Strategic Priorities for 2022 report)

Top challenges to technology initiatives

(Source: ADAPTs Embracing the Future: Top 12 Strategic Priorities for 2022 report)

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Artificial intelligence keeps the spirits up during the pandemic - The Australian Financial Review

New York Citys New Law Regulating the Use of Artificial Intelligence in Employment Decisions – JD Supra

On Nov. 10, 2021, the New York City Council passed a bill that regulates employers and employment agencies use of automated employment decision tools in making employment decisions. The bill was returned without Mayor Bill de Blasios signature and lapsed into law on Dec. 11, 2021. The new law takes effect on Jan. 1, 2023. This new law is part of a growing trend towards examining and regulating the use of artificial intelligence (AI) in hiring, promotional and other employment decisions.

Requirements of the New Law. The new law regulates employers and employment agencies use of automated employment decision tools on candidates and employees residing in New York City. An automated employment decision tool refers to any computational process, derived from machine learning, statistical modeling, data analytics, or artificial intelligence, that issues simplified output, including a score, classification, or recommendation, that is used to substantially assist or replace discretionary decision making for making employment decisions that impact natural persons.

The new law prohibits an employer or employment agency from using an automated employment decision tool in making an employment decision unless, prior to using the tool, the following requirements are met: (1) the tool has been subject to a bias audit within the last year; and (2) a summary of the results of the most recent bias audit and distribution data for the tool have been made publicly available on the employer or employment agencys website. A bias audit is defined as an impartial evaluation by an independent auditor, which includes the testing of an automated employment decision tool to assess the tools disparate impact on persons of any component 1 category required to be reported by employers pursuant to 42 U.S.C. 2000e-8(c) and 29 C.F.R. 1602.7.

The new law also requires employers and employment agencies to satisfy two notice requirements. First, at least 10 business days before using the tool, the employer or employment agency must notify a candidate or employee who resides in New York City of the following: (1) that an automated employment decision tool will be used in assessing the candidate or employee; and (2) the job qualifications and characteristics that the tool will use in the assessment. The employer or employment agency must allow the candidate or employee to request an alternative process or accommodation. However, the law is silent as to the employer or employment agencys obligation to provide such alternative process or accommodation. Second, the employer or employment agency must disclose on their website or make available to a candidate or employee within 30 days of receiving a written request, the following: (1) information about the type of data collected for the automated employment decision tool; (2) the source of the collected data; and (3) the employer or employment agencys data retention policy.

Penalties for Violations. Violations of the new law will result in liability for a civil penalty of up to $500 for the first violation and each additional violation occurring on the same day as the first violation, and a civil penalty between $500 and $1,500 for each subsequent violation. Importantly, each day the automated employment decision tool is used in violation of the law constitutes a separate violation and the failure to provide any of the required notices constitutes a separate violation.

Recommendations for Timely Compliance. Employers with candidates or employees who reside in New York City can take several steps now to facilitate compliance with this new requirement when it goes into effect on Jan. 1, 2023. Employers should ensure that any covered automated employment decision tool that they plan to use in 2023 or thereafter to assess New York City candidates and employees is subject to a bias audit by an independent auditor and the results of such audit are available on their website. Additionally, we recommend that employers and employment agencies work with their legal counsel to develop and implement practices that comply with the notice provisions required by the new law.

Other Regulations on Automated Employment Decision Tools. Several states and cities have passed or are considering similar laws regarding the use of artificial intelligence and other technology in employment decisions. For example, Illinois Artificial Intelligence Video Interview Act, which took effect Jan. 1, 2020, requires employers using AI interview technology to provide advanced notice and an explanation of the technology to applicants, to obtain the applicants consent to use the technology and to comply with restrictions on the distribution and retention of videos. Similarly, Maryland enacted a law that took effect Oct. 1, 2020, which requires employers to obtain an applicants written consent and a waiver prior to using facial recognition technology during pre-employment job interviews. California and Washington, D.C. have also proposed legislation that would address the use of AI in the employment context.

Additionally, on Oct. 28, 2021, the U.S. Equal Employment Opportunity Commission (EEOC) launched a new initiative aimed at ensuring artificial intelligence and other technological tools used in making employment decisions comply with the federal civil rights laws. As part of its initiative, the EEOC will gather information about the adoption, design and impact of employment-related technologies, and issue technical assistance to provide employers with guidance on algorithmic fairness and the use of artificial intelligence in employment decisions.

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Artificial intelligence can spot the signs of PTSD in your text messages – Study Finds

EDMONTON, Alberta A text message may be able to reveal if someone is dealing with post-traumatic stress disorder (PTSD), a new study finds. Researchers from the University of Alberta say a machine learning program a form of artificial intelligence is capable of reading between the lines to find potential warning signs in the way people write.

The team believes this program could become an inexpensive tool that helps mental health professionals detect and diagnose cases of PTSD or other disorders. Psychiatry PhD candidate Jeff Sawalha performed a sentiment analysis of texts using a dataset created by Jonathan Gratch from USCs Institute for Creative Technologies.

Study authors explain that a sentiment analysis takes a large amount of data and categorizes it. In this case, the model took a massive amount of texts and sorted them according to positive and negative thoughts.

We wanted to strictly look at the sentiment analysis from this dataset to see if we could properly identify individuals with PTSD just using the emotional content of these interviews, Sawalha says in a university release.

The text sampling came from 250 semi-structured interviews conducted by an artificial interviewer (Ellie) who spoke with real participants using video conferencing calls. Eighty-seven people had PTSD while the other 188 did not.

From their text responses, the team was able to identify people with PTSD through their scores reflecting how often their words displayed neutral or negative thoughts.

This is in line with a lot of the literature around emotion and PTSD. Some people tend to be neutral, numbing their emotions and maybe not saying too much. And then there are others who express their negative emotions, Sawalha says.

Study authors note that this process isnt black and white. For example, a phrase like I didnt hate that could be confusing for the algorithm. Despite that, the machine learning system was able to detect PTSD patients with 80 percent accuracy.

Text data is so ubiquitous, its so available, you have so much of it, Sawalha continues. From a machine learning perspective, with this much data, it may be better able to learn some of the intricate patterns that help differentiate people who have a particular mental illness.

The team is planning to integrate other types of data, including speech patterns and human motions, which they say may help the system spot mental health disorders better. Moreover, signs of neurological conditions like Alzheimers disease are detectable through a persons ability to speak.

Unlike an MRI that takes an experienced person to look at it, this is something people can do themselves. I think thats the direction medicine is probably going, toward more screening tools, says Russ Greiner, a professor in the Department of Computing Science.

Having tools like this going forward could be beneficial in a post-pandemic world, Sawalha concludes.

The study is published in the journal Frontiers in Psychiatry.

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Lakeland’s busiest intersections will get artificial intelligence sensors to prevent crashes – ABC Action News Tampa Bay

LAKELAND, Fla. Lakeland is using artificial intelligence to reduce the number of deadly car crashes.

Weve all seen that driver who speeds into the intersection trying to beat the red light. The City of Lakeland is using artificial intelligence so that traffic signals can identify reckless drivers before they cause a crash.

Vehicles caught running through red lights in Lakeland

It will tell us as a car is approaching the intersection, the likelihood of it stopping, said Jeff Weatherford, traffic operations manager for the City of Lakeland.

Lakeland's Intersection Collision Avoidance Safety Program, or iCASP works by delaying the green light of cross-traffic up to four seconds, when sensors detect a vehicle is going to run a red light.

There are actually several sensors, but the furthest one out is about 150 feet from the stop line, Weatherford said.

The Florida Department of Transportation is investing $500,000 to expand the citys red light-running detection program, to 25 high-impact intersections. Lakeland has already been operating the red light running sensors at four major intersections, in a pilot program since last February. The data shows a significant amount of red-light runners putting the lives of other drivers at risk.

In a 24-hour period, there were 45 cars that ran the red light, were in the intersection while the light was red, at that intersection headed eastbound and we had zero crashes that day, Weatherford said.

The smart system makes a split-second decision, potentially avoiding deadly collisions.

The city is also looking at incorporating a new mobile app with iCASP to alert drivers of a red-light runner.

Phone apps that will run in the background, being able to send out an alert to a driver that will warn them, caution, watch for crossing traffic,' said Weatherford.

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Shopping with Fraud Protection and Adaptive Artificial Intelligence – CIO

Online Shopping Surges

With the worldwide pandemic, consumer behavior has shifted significantly. There has been substantially less travelemployees havent been driving to the office, flying on planes, or taking cruises. Many have gone out less, stopped going to movies, and dont hang out on Friday night after work.

This has caused a major disruption in the financial flow. To survive, many businessessmall and largehave pivoted to bring and scale their businesses online. The result is a tremendous surge in online shopping. Experts suggest that e-commerce has been accelerated on the order ofthree to five years.

And these changes arent expected to go away. While buying everyday necessities like groceries online has been a safety strategy for many consumers, the convenience of online shopping is compelling enough for many to continue. At the same time, with the greater number of online transactions, fraud becomes an increasingly more expensive problem.

Scaling Transaction Processing to Fight Fraud

The amount of money lost to card-not-present fraud in 2020 was six times greater than what merchants lost in 2019,according to the Nilson Report. That wasnt a fluke either, as the 2019 numbers were four times higher than 2018. That means companies need to be able to process more transactions faster with greater accuracy. Mastercard, for example, manages more thantwo billion cardsand processes 165 million transactions per hour across 210 countries and territories.

Processes is an understatement. Using artificial intelligence (AI) and machine learning, more than 1.9 million rules are applied to each transaction to assess its risk. And this process needs to be completed in milliseconds.

High performance computing (HPC) is the only way to stay ahead of fraud as new schemes are devised and security vulnerabilities are discovered. HPC is also the foundation for evolving AI technologies. The more use cases AI must accommodate, the more data is involved and the more complex the data pipeline can become.

Today, 10% of data is processed outside of the data center and that figure isexpected to rise to 75% by 2025. At the same time, to minimize response time, AI needs to be implemented closer to the edge. However, as new data is uncovered and algorithms adapt, these changes will also need to be able to scale back out to deploy throughout the worldwide network.

Deploy Adaptive AI at Scale

Consider evaluating the risk of accepting payments from a new merchant will little to no history. An initial assessment must be made quickly and accurately. However, given the ability of defrauders to operate anywhere in the world, data useful in identifying fraud could be available and leveraged anywhere in the global system.

AI and HPC are key to gathering valuable data, generating analytics, and dynamically adapting algorithms that identify fraud as quickly as possible anywhere at any time. Dell Technologies offers a wide range of customizable solutions to match the requirements of financial institutions of all types that need to process data quickly, accurately and securely. These solutions are designed to scale as a company grows.

Dell Technologies is also supported by a wide ecosystem of partners to assist FinTech companies of all natures with their individual needs.Converge Technologies, for example, is a Top 50 CRN Solution Provider that helps organizations find the right infrastructure to support leading-edge AI technology. Their solutions include Dell PowerEdge servers with IntelXeonScalable processors and Intel Optanememory, PowerSwitch networking and PowerScale storage for fast data processing, movement and storage.Scaling doesnt have to be challenging. With the right technologies and partners, financial companies can expand their operations and successfully combat fraud. Learn more about new types of HPC/AI scalability for financial markets atHPC & AI on Wall Street.

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Intel Technologies Move Analytics Forward

Data analytics is the key to unlocking the most value you can extract from data across your organization. To create a productive, cost-effective analytics strategy that gets results, you need high performance hardware thats optimized to work with the software you use.

Modern data analytics spans a range of technologies, from dedicated analytics platforms and databases to deep learning and artificial intelligence (AI). Just starting out with analytics? Ready to evolve your analytics strategy or improve your data quality? Theres always room to grow, and Intel is ready to help. With a deep ecosystem of analytics technologies and partners, Intel accelerates the efforts of data scientists, analysts, and developers in every industry. Find out more aboutIntel advanced analytics.

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Artificial intelligence may help trainee teachers with assessments study – Irvine Times

Artificial intelligence (AI) could be used to mark the work of trainee teachers who are trying to identify pupils with potential learning difficulties, a study suggests.

Researchers said it could be an effective substitute when personal feedback is not readily available.

In a trial, 178 German trainee teachers were asked to assess six fictionalised pupils to decide whether they had learning difficulties such as dyslexia or Attention Deficit Hyperactivity Disorder (ADHD), and to explain their reasoning.

They were given examples of their schoolwork, as well as other information such as behaviour records and transcriptions of conversations with parents.

Immediately after submitting their answers, half of the trainees received a prototype expert solution, written in advance by a qualified professional, to compare with their own.

This is typical of the practice material that German trainee teachers usually receive outside taught classes.

The others received AI-generated feedback, which highlighted the correct parts of their solution and flagged aspects they might have improved.

The tests were scored by researchers, who assessed both their diagnostic accuracy whether the trainees had correctly identified cases of dyslexia or ADHD and their diagnostic reasoning: how well they had used the available evidence to make this judgement.

The average score for diagnostic reasoning among trainees who had received AI feedback during the six preliminary exercises was an estimated 10 percentage points higher than those who had worked with the pre-written expert solutions.

The reason for this may be the adaptive nature of the AI, according to the study, led by academics at Cambridge University and Ludwig Maximilian University in Munich

Because it analysed the trainee teachers own work, rather than asking them to compare it with an expert version, the researchers believe the feedback was clearer.

There is no evidence, therefore, that AI of this type would improve on one-to-one feedback from a human tutor or high-quality mentor, but if such close support was not readily available, it could have benefits, particularly for trainees on larger courses.

Dr Michael Sailer, from LMU Munich, said: Obviously we are not arguing that AI should replace teacher-educators: new teachers still need expert guidance on how to recognise learning difficulties in the first place.

It does seem, however, that AI-generated feedback helped these trainees to focus on what they really needed to learn.

Where personal feedback is not readily available, it could be an effective substitute.

The study used a system capable of analysing human language and spotting certain phrases, ideas, hypotheses or evaluations in the trainees text.

It was created using the responses of an earlier cohort of pre-service teachers to a similar exercise.

By segmenting and coding these responses, the team trained the AI system to recognise the presence or absence of key points in the solutions provided by trainees during the trial.

The system then selected pre-written blocks of text to give the participants appropriate feedback.

Riikka Hofmann, associate professor at Cambridge Universitys Faculty of Education, said: Teachers play a critical role in recognising the signs of disorders and learning difficulties in pupils and referring them to specialists.

Our findings suggest that AI could provide an extra level of individualised feedback to help them develop these essential competencies.

The research is published in the journal Learning and Instruction.

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Artificial intelligence may help trainee teachers with assessments study - Irvine Times

Why It’s Time To Say Goodbye To ‘one-size-fits-all’ In Insurance – Forbes India

Companies will target newer age groups, such as millennials and gen Z, who traditionally tend to underestimate the importance of health insurance; Image: Shutterstock

In chaos theory, the butterfly effect is the idea that small things can have a non-linear impact on a complex system. The flapping of a butterfly's wings in the Amazonian jungle, for instance, could create tiny changes in the atmosphere that lead to a tornado in Texas. Just like the minuscule yet deadly novel coronavirus in 2019 triggered a storm of changes that swept across all sectors in the world, including the insurance industry.

Analysing risks and planning for a crisis is what the insurance business is about. While the pandemic has wreaked havoc on the industry, it has done better than most other. The industry has changed structurally, mostly for the better. The changes, forced into the industry in a tearing hurry, have proved to be sticky and durable. And whether intended on not, have put the customer firmly at the centre. Lets dive in.

Tech-first approachConsider this: India has 1.18 billion mobile connections, 700 million Internet users, 600 million smartphones, and a population that has the highest data consumption in the worldabout 12 GB per person a month (National Health Authority of India, 2021). Today, being digitally versatile is central to every decision and every interaction made by both individuals and companies. The insurance industry was among the first to recognise this and made the best possible use of technology, investing early in collaborative tools like social media, WhatsApp, Zoom, Microsoft Teams, and so onas well as digital technology assets such as mobile apps for insurance, chatbots, and tools that allow processes like faster KYC verification and onboarding, automated underwriting, virtual claims adjusting, and so on. Digital technology that is cheap, scalable, functional, and replicable is here to stay. Heres a pro tip: Watch out for the seismic impact of Artificial Intelligence (AI) on all parts of the insurance value chain.

Choice is niceA marked increase in awareness about health during the pandemic has resulted in an uptick in demand for health insurance. But the one-size-fits-all approach is a thing of the past. With a plethora of choices and a greater appreciation for the gift of health, people are taking a more holistic approach to their health. This means customers today demand customised, personalised, and intuitive policies that were not covered by companies earlier. For example, policies specially designed for Covid-19, mental health issues, certain types of cancer, seasonal illnesses such as dengue, malaria, or even a cover for those with adverse medical history who were denied cover earlier. As customer demands and expectations continue to change, insurers will have to find a way to adapt their business model to meet new demands and win trust.

Innovate or perishDuring the pandemic, the changing consumer behaviour spurred companies to reimagine and build new product strategies to offer relevant products that sustain customer interest. This is a trend that will continue for the foreseeable future and companies that adopt a mix of hyper-segmentation and innovation are the ones that will emerge stronger than others.

For instance, an innovative cyber insurance product, especially now, due to the increased risk of vulnerability, cyberattacks, data and identity theft. Companies will target newer age groups, such as millennials and gen Z, who traditionally tend to underestimate the importance of health insurance. Innovative products in insurance are not restricted to just health either. Hourly car insurance, women-only drivers insurance that rewards good drivers with lower premiums, pet insurance, trip delay or cancellation insurance just for honeymoons (anyone who tied the knot during the pandemic will vouch for the need for this)innovation is the mantra for success.

Flexi-cultureDuring the pandemic, like the rest of the world, the insurance industry too adopted the work-from-home model. However, remote working comes with challenges, such as a fragmented workforce, the blurred lines between working and personal hours, mental fatigue, and the challenge of building a cohesive organisational culture with a distributed workforce. Hybrid work culture is the future. Make no mistake, there is no going back to a 9 AM to 6 PM, five-days-a-week workplace.

While the physical demands of travel to the office and other locations and cities have diminished, the demands on the employee's time have increased and will continue to stay elevated. Or worse, in most cases, employees have to fend for themselves and take responsibility for their sanity and well-being. Distance between the organisation and employees, and between employees themselves, could lead to the serious consequence of the company distancing itself from the customers. Of all the changes, this is the most significant and impactful one. How this is dealt with will have the biggest bearing on the future and success of an organisation.

The secret of change is to focus all of your energy, not on fighting the old, but on building the new, said Socrates. How we build the new will separate the wheat from the chaff and the winners from the also-rans.The next five years promise plenty of drama and upheaval. Let's grab the best seats in the house and enjoy the show.

The author is the Managing Director & CEO of Future Generali India Insurance.

The thoughts and opinions shared here are of the author.

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The rest is here:
Why It's Time To Say Goodbye To 'one-size-fits-all' In Insurance - Forbes India