This is Dr. Toa Charm's presentation from the 15 May 2014 meeting of the Hong Kong Big Data community. Along with Daniel Ng and myself (Scott Drummonds), Dr. Charm presented on big data in Hong Kong to a joint session of HKBD and the Chinese University of Hong Kong MBA consulting club.
Big Data Alchemy: How can Banks Maximize the Value of their Customer Data?Capgemini
This document is a point of view on how banks can maximize the value of their customer data using big data analytics. While the volume of data has been increasing in recent years, many banks have not been able to profit from this growth. Several challenges hold them back. The PoV explores these challenges and suggests actions for banks in order to scale-up to the next level of customer data analytics.
Digital, Data & Analytics, Disruption in DealsAnand Rao
Presentation at the PwC Midwest Deals Summit by Dr. Anand Rao, John Sviokla and Andrea Fishman.
The presentation looks at impact of digitization, data and analytics and the disruption they cause in retail, healthcare, agribusiness, and financial services. We look at how this is leading to more deals across the spectrum from large M&A's to private equity to venture capital
Leveraging Geo-Spatial (Big) Data for Financial Services SolutionsCapgemini
For effective decision making, Big Data needs to be delivered at the right level of granularity at the right time. Capgemini’s FS BIM Innovation Practice, working through our Mastermind and Greenhouse processes to ensure a focus on real-world client issues, has developed a Reference Architecture (RA) based upon HP HAVEn to achieve these goals.
While Geo-Spatial Data has traditionally been applied to non-FS domains, effective application of this data has the potential to improve decision-making in FS, including in the areas of underwriting and pricing, claims, and bank and credit card fraud.
Presented at HP Discover Barcelona 2014 by:
Guillaume Runser - WW Solutions Marketing, HP
Ernest Martinez - Global Head - FS BIM Banking, Capgemini
Stephen Williams - BIM Innovation Practice Head, Capgemini
Business Intelligence and Analytics in banking has advanced with time and has been invariably helping banks to leverage the banking data and utilize it for utmost business value. BI enables banks to manage data, gain actionable insights and make informed decisions for better profitability.
Staying ahead in the cyber security game - Sogeti + IBMRick Bouter
Cyber security is center stage in the world today, thanks to almost continuous revelations about incidents and breaches. In this context of unpredictability and insecurity, organizations are redefining their approach to security, trying to find the balance between risk, innovation and cost. At the same time, the field of cyber security is undergoing many dramatic changes, demanding organizations embrace new practices and skill sets.
Cyber security risk is now squarely a business risk – dropping the ball on security can threaten an organization’s future – yet many organizations continue to manage and understand cyber security in the context of the it department. This has to change.
Big Data Alchemy: How can Banks Maximize the Value of their Customer Data?Capgemini
This document is a point of view on how banks can maximize the value of their customer data using big data analytics. While the volume of data has been increasing in recent years, many banks have not been able to profit from this growth. Several challenges hold them back. The PoV explores these challenges and suggests actions for banks in order to scale-up to the next level of customer data analytics.
Digital, Data & Analytics, Disruption in DealsAnand Rao
Presentation at the PwC Midwest Deals Summit by Dr. Anand Rao, John Sviokla and Andrea Fishman.
The presentation looks at impact of digitization, data and analytics and the disruption they cause in retail, healthcare, agribusiness, and financial services. We look at how this is leading to more deals across the spectrum from large M&A's to private equity to venture capital
Leveraging Geo-Spatial (Big) Data for Financial Services SolutionsCapgemini
For effective decision making, Big Data needs to be delivered at the right level of granularity at the right time. Capgemini’s FS BIM Innovation Practice, working through our Mastermind and Greenhouse processes to ensure a focus on real-world client issues, has developed a Reference Architecture (RA) based upon HP HAVEn to achieve these goals.
While Geo-Spatial Data has traditionally been applied to non-FS domains, effective application of this data has the potential to improve decision-making in FS, including in the areas of underwriting and pricing, claims, and bank and credit card fraud.
Presented at HP Discover Barcelona 2014 by:
Guillaume Runser - WW Solutions Marketing, HP
Ernest Martinez - Global Head - FS BIM Banking, Capgemini
Stephen Williams - BIM Innovation Practice Head, Capgemini
Business Intelligence and Analytics in banking has advanced with time and has been invariably helping banks to leverage the banking data and utilize it for utmost business value. BI enables banks to manage data, gain actionable insights and make informed decisions for better profitability.
Staying ahead in the cyber security game - Sogeti + IBMRick Bouter
Cyber security is center stage in the world today, thanks to almost continuous revelations about incidents and breaches. In this context of unpredictability and insecurity, organizations are redefining their approach to security, trying to find the balance between risk, innovation and cost. At the same time, the field of cyber security is undergoing many dramatic changes, demanding organizations embrace new practices and skill sets.
Cyber security risk is now squarely a business risk – dropping the ball on security can threaten an organization’s future – yet many organizations continue to manage and understand cyber security in the context of the it department. This has to change.
Creating a Digital Banking Strategy - 01.23.15Calvin Turner
Today, the new buzzword in business is “Digital Strategy”. The problem, however, is that if you ask a group of business professionals to define "Digital Strategy" to you, depending on the industry, who you ask, and the ages of the respondents (yes, the generational perspective makes a difference), you will likely get a wide variety of different responses to that simple question. To illustrate this point, in a December 2014, Digital Banking research study published by Celent, when banking executives were asked what “Digital” means for them, they responded with a diverse – and sometimes inconsistent – set of answers. But invariably, mobile devices and social media are usually included somewhere in the answer. So, let's begin the discussion by clearing up a common misconception: an organization's Digital Strategy is NOT enabling/allowing customers to use mobile devices to communicate and conduct business. They are certainly components of a Digital Strategy, but the true definition of a Digital Strategy is much broader than that.
Three big questions about AI in financial servicesWhite & Case
To ride the rising wave of AI, financial services companies will have to navigate evolving standards, regulations and risk dynamics—particularly regarding data rights, algorithmic accountability and cybersecurity.
The Currency of Trust: Why Banks and Insurers Must Make Customer Data Safer a...Capgemini
Are banks and insurers a safe pair of hands when it comes to customer data? Our global survey of more than 180 senior data privacy and security professionals – as well as 7,600 consumers – found that less than a third (29%) of these organizations offer both strong data privacy practices and a sound security strategy. Just one in five (21%) are highly confident that they can detect a cybersecurity breach.
This picture has so far not unduly affected consumers’ perceptions of the industry. We found that 83% of consumers trust banks and insurers when it comes to data. And while one in four institutions have reported being victim of a hack, just 3% of consumers believe their own bank or insurer has ever been breached. However, with the pending General Data Protection Regulation (GDPR) regulations, this trust factor is likely to change as transparency increases. Financial organizations have to reveal a data breach 72 hours after the incident.
Banks and insurance firms have a clear incentive therefore to fortify their defences. As well as avoiding the prohibitive fines and penalties that will result from compromised data, protecting privacy offers a strategic business advantage. Addressing security concerns will drive greater adoption of low-cost digital channels. We found that security concerns deter nearly half of consumers (47%) from using digital channels. It will also reduce churn and attract competitors’ customers – 74% of consumers would switch their bank or insurer in the event of a data breach.
Preparing to be a trusted data steward is no easy task, however. It means raising the bar on multiple dimensions:
• Aligning data practices with consumers’ expectations
• Finding innovative ways of providing non-intrusive security to consumers
• Building the capabilities required to monitor cyber risks on a real-time basis
• Revisiting the data governance model.
Building your reputation for data privacy and robust security is definitely challenging. But, those who strike the right chord with consumers will enjoy a competitive advantage over their peers. The winners will be those who triumph in the trust game.
Listen to an experienced, global panel of insurance professionals present, discuss and answer your questions on the theme of “Data & Analytics from a Life & Health perspective”.
Brought to you by The Digital Insurer and sponsored by KPMG.
From Smart Meters to Smart Products: Reviewing Big Data driven Product Innova...Nicolai Krüger
My Presentation at the Informatik 2015 conference about a paper by Prof. Frank Teuteberg and me: From Smart Meters to Smart Products: Reviewing Big Data driven Product Innovation in the European Electricity Retail Market
As soon as the final publication of the paper is available, I will share the link here as well.
Cybersecurity Talent : The Big Gap in Cyber ProtectionCapgemini
Read the latest report from the Digital Transformation Institute titled “Cybersecurity Talent : The Big Gap in Cyber Protection”. The report is based on a survey of 1200 employers and executives as well as social media analysis of 8000+ employees. It focuses on skill gap in cybersecurity and offers eight key recommendations to organizations to address two areas – acquisition and retention of cybersecurity talent.
Learn more at https://www.capgemini.com/resources/cybersecurity-talent-gap
A significant CAGR of 53.8% during the forecast period of 2018-2023, is anticipated for the global Robo-advisory market, propelling its value to roughly USD 74 Bn, by 2023 – in contrast to its 2015 value of USD 5.9 Bn. A shift in preference towards automation, cost reduction and simplified client experiences will bring this new wave of technology to the fore in the wealth management industry. The hybrid model - an integration of human and robo-advisors – is the most prominent trend being observed in the market.
Early Stage Fintech Investment Thesis (Sept 2016)Earnest Sweat
Here is an example of a personal investment thesis that I created to share with venture capital firms. In this example, I provide my personal perspective on the fintech sector. For details on how I build this thesis check out my blog (https://goo.gl/CU4Qid).
Note: Some of the confidential information has been redacted for privacy.
I delivered a talk on application of Artificial Intelligence in Fintech to the visiting students of University of Applied Sciences, Wurzburg-Schweinfurt, Germany at Christ University
The 7 Biggest Technology Trends To Disrupt Banking & Financial Services In 2020Bernard Marr
New technology changes the operations and realities of organizations in all industries when it is widely adopted. It's no different with the latest innovation introduced by artificial intelligence, blockchain, and other technology. Here we look at the 7 biggest technology trends that will disrupt banking and financial services in 2020.
Purpose: The slides provide an overview on the Cognitive Computing trend for IBM clients and external stakeholders
Content: Summary information about the Cognitive Computing trend is provided along with many links to additional resources.
How To Use This Report: This report is best read/studied and used as a learning document. You may want to view the slides in slideshow mode so you can easily follow the links
Available on Slideshare: This presentation (and other HorizonWatch Trend Reports for 2015) will be available publically on Slideshare at http://www.slideshare.net/horizonwatching
Please Note: This report is based on internal IBM analysis and is not meant to be a statement of direction by IBM nor is IBM committing to any particular technology or solution.
Data visualization in data science: exploratory EDA, explanatory. Anscobe's quartet, design principles, visual encoding, design engineering and journalism, choosing the right graph, narrative structures, technology and tools.
Creating a Digital Banking Strategy - 01.23.15Calvin Turner
Today, the new buzzword in business is “Digital Strategy”. The problem, however, is that if you ask a group of business professionals to define "Digital Strategy" to you, depending on the industry, who you ask, and the ages of the respondents (yes, the generational perspective makes a difference), you will likely get a wide variety of different responses to that simple question. To illustrate this point, in a December 2014, Digital Banking research study published by Celent, when banking executives were asked what “Digital” means for them, they responded with a diverse – and sometimes inconsistent – set of answers. But invariably, mobile devices and social media are usually included somewhere in the answer. So, let's begin the discussion by clearing up a common misconception: an organization's Digital Strategy is NOT enabling/allowing customers to use mobile devices to communicate and conduct business. They are certainly components of a Digital Strategy, but the true definition of a Digital Strategy is much broader than that.
Three big questions about AI in financial servicesWhite & Case
To ride the rising wave of AI, financial services companies will have to navigate evolving standards, regulations and risk dynamics—particularly regarding data rights, algorithmic accountability and cybersecurity.
The Currency of Trust: Why Banks and Insurers Must Make Customer Data Safer a...Capgemini
Are banks and insurers a safe pair of hands when it comes to customer data? Our global survey of more than 180 senior data privacy and security professionals – as well as 7,600 consumers – found that less than a third (29%) of these organizations offer both strong data privacy practices and a sound security strategy. Just one in five (21%) are highly confident that they can detect a cybersecurity breach.
This picture has so far not unduly affected consumers’ perceptions of the industry. We found that 83% of consumers trust banks and insurers when it comes to data. And while one in four institutions have reported being victim of a hack, just 3% of consumers believe their own bank or insurer has ever been breached. However, with the pending General Data Protection Regulation (GDPR) regulations, this trust factor is likely to change as transparency increases. Financial organizations have to reveal a data breach 72 hours after the incident.
Banks and insurance firms have a clear incentive therefore to fortify their defences. As well as avoiding the prohibitive fines and penalties that will result from compromised data, protecting privacy offers a strategic business advantage. Addressing security concerns will drive greater adoption of low-cost digital channels. We found that security concerns deter nearly half of consumers (47%) from using digital channels. It will also reduce churn and attract competitors’ customers – 74% of consumers would switch their bank or insurer in the event of a data breach.
Preparing to be a trusted data steward is no easy task, however. It means raising the bar on multiple dimensions:
• Aligning data practices with consumers’ expectations
• Finding innovative ways of providing non-intrusive security to consumers
• Building the capabilities required to monitor cyber risks on a real-time basis
• Revisiting the data governance model.
Building your reputation for data privacy and robust security is definitely challenging. But, those who strike the right chord with consumers will enjoy a competitive advantage over their peers. The winners will be those who triumph in the trust game.
Listen to an experienced, global panel of insurance professionals present, discuss and answer your questions on the theme of “Data & Analytics from a Life & Health perspective”.
Brought to you by The Digital Insurer and sponsored by KPMG.
From Smart Meters to Smart Products: Reviewing Big Data driven Product Innova...Nicolai Krüger
My Presentation at the Informatik 2015 conference about a paper by Prof. Frank Teuteberg and me: From Smart Meters to Smart Products: Reviewing Big Data driven Product Innovation in the European Electricity Retail Market
As soon as the final publication of the paper is available, I will share the link here as well.
Cybersecurity Talent : The Big Gap in Cyber ProtectionCapgemini
Read the latest report from the Digital Transformation Institute titled “Cybersecurity Talent : The Big Gap in Cyber Protection”. The report is based on a survey of 1200 employers and executives as well as social media analysis of 8000+ employees. It focuses on skill gap in cybersecurity and offers eight key recommendations to organizations to address two areas – acquisition and retention of cybersecurity talent.
Learn more at https://www.capgemini.com/resources/cybersecurity-talent-gap
A significant CAGR of 53.8% during the forecast period of 2018-2023, is anticipated for the global Robo-advisory market, propelling its value to roughly USD 74 Bn, by 2023 – in contrast to its 2015 value of USD 5.9 Bn. A shift in preference towards automation, cost reduction and simplified client experiences will bring this new wave of technology to the fore in the wealth management industry. The hybrid model - an integration of human and robo-advisors – is the most prominent trend being observed in the market.
Early Stage Fintech Investment Thesis (Sept 2016)Earnest Sweat
Here is an example of a personal investment thesis that I created to share with venture capital firms. In this example, I provide my personal perspective on the fintech sector. For details on how I build this thesis check out my blog (https://goo.gl/CU4Qid).
Note: Some of the confidential information has been redacted for privacy.
I delivered a talk on application of Artificial Intelligence in Fintech to the visiting students of University of Applied Sciences, Wurzburg-Schweinfurt, Germany at Christ University
The 7 Biggest Technology Trends To Disrupt Banking & Financial Services In 2020Bernard Marr
New technology changes the operations and realities of organizations in all industries when it is widely adopted. It's no different with the latest innovation introduced by artificial intelligence, blockchain, and other technology. Here we look at the 7 biggest technology trends that will disrupt banking and financial services in 2020.
Purpose: The slides provide an overview on the Cognitive Computing trend for IBM clients and external stakeholders
Content: Summary information about the Cognitive Computing trend is provided along with many links to additional resources.
How To Use This Report: This report is best read/studied and used as a learning document. You may want to view the slides in slideshow mode so you can easily follow the links
Available on Slideshare: This presentation (and other HorizonWatch Trend Reports for 2015) will be available publically on Slideshare at http://www.slideshare.net/horizonwatching
Please Note: This report is based on internal IBM analysis and is not meant to be a statement of direction by IBM nor is IBM committing to any particular technology or solution.
Data visualization in data science: exploratory EDA, explanatory. Anscobe's quartet, design principles, visual encoding, design engineering and journalism, choosing the right graph, narrative structures, technology and tools.
Alternative Data is everywhere. We MUST start using them as a competitive edge over the competitors who are all looking to only their traditional data sources
D2 d turning information into a competive asset - 23 jan 2014Henk van Roekel
Understanding the evolution of Business Intelligence and Analytics and the challenges and opportunities that come with it. Exploring CGI's Data2Diamonds™ approach ensuring financial sound, technical viable and socially desirable Big Data initiatives.
AI for Enterprises-The Value Paradigm By Venkat Subramanian VP Marketing at B...Analytics India Magazine
AI is here, call it buzz, cause it a bubble, we are smack in the middle of an AI revolution. While there is a strong view building about consumer AI applications, there still seems to be some scepticism about AI for enterprises, primarily due to the lack of clarity and focus on how AI can actually deliver value for enterprises. At BRIDGEi2i, we believe it is important to have a non-fragmented view of the AI ecosystem and a “Value Roadmap” for AI in the enterprise context. As CxOs, it is important to understand where the enterprise is in the transformation journey and define value accordingly. This talk will throw light on how to look at the enterprise AI ecosystem and build the right roadmap for value.
Anticipating the future is hard. But in today’s fast paced world it’s more critical than ever. And there are techniques available that can help you mitigate innovation risk and be more effective at strategic planning. Daniel Burrus, one of the world’s leading futurists on trends and innovation and NY Times bestselling author, uses his success and expertise to teach others how to build their competency of anticipation.
In this session, Erik Asgeirsson, CEO of CPA.com, and Daniel Burrus will discuss:
The hard trends report gathered from firms at DCPA 2016
What this means for firms
How to capitalize on the opportunities created by these trends.
Get unstuck from analysis paralysis, and gain tools and inspiration to facilitate your firm’s growth with certainty!
How Big Data helps banks know their customers betterHEXANIKA
Enterprises today mine customer data to ensure maximum success by targeting their products and solutions to the right audience. Let us have a look at how Big Data and Customer Analytics are helping businesses use their customer data for maximum benefits.
The objective of this module is to take a look into what big data can bring you in the future.
Upon completion of this module you will:
- See what are the predictions for the future of Big Data
- Take a look at some trends that are emerging
- Get an overview of possible opportunities your company can have with Big Data
- Face some of the start up challenges you might have with Big Data
Duration of the module: approximately 1 – 2 hours
Big Data is the lastest cashcow. Data Analytics has now a crucial role for industries. This article describes as to what is Big Data and Analytics and how a Chartered Accountant will be able to provide value in this field.
Patrick Couch - Intelligenta Maskiner & Smartare Tjänster IBM Sverige
Industriföretag, såväl tillverkare som användare av maskiner, fordon och utrustning, står inför ett paradigmskifte drivet av ökad global konkurrens, kunders förändrade efterfrågan samt det faktum att produkterna nu blir instrumenterade, ihopkopplade och mer intelligenta. Stora datamängder är inte ett buzzword för dessa företag, utan en reell verklighet som de behöver förhålla sig till för att säkra sin framtida verksamhet. I bästa fall omvandlar dessa företag denna teknologiska revolution (populärt kallad Internet of Things, Industrial Internet, M2M, Industri 4.0 etc.) till en motor för att utveckla verksamheten mot tillväxt och effektivare produktion. Detta skifte skapar framförallt stora möjligheter att förflytta sig mot leveranser av tjänster som kraftigt ökar mervärdet för kunderna, deras kunders kunder samt för producenten.
Adjusting OpenMP PageRank : SHORT REPORT / NOTESSubhajit Sahu
For massive graphs that fit in RAM, but not in GPU memory, it is possible to take
advantage of a shared memory system with multiple CPUs, each with multiple cores, to
accelerate pagerank computation. If the NUMA architecture of the system is properly taken
into account with good vertex partitioning, the speedup can be significant. To take steps in
this direction, experiments are conducted to implement pagerank in OpenMP using two
different approaches, uniform and hybrid. The uniform approach runs all primitives required
for pagerank in OpenMP mode (with multiple threads). On the other hand, the hybrid
approach runs certain primitives in sequential mode (i.e., sumAt, multiply).
The Building Blocks of QuestDB, a Time Series Databasejavier ramirez
Talk Delivered at Valencia Codes Meetup 2024-06.
Traditionally, databases have treated timestamps just as another data type. However, when performing real-time analytics, timestamps should be first class citizens and we need rich time semantics to get the most out of our data. We also need to deal with ever growing datasets while keeping performant, which is as fun as it sounds.
It is no wonder time-series databases are now more popular than ever before. Join me in this session to learn about the internal architecture and building blocks of QuestDB, an open source time-series database designed for speed. We will also review a history of some of the changes we have gone over the past two years to deal with late and unordered data, non-blocking writes, read-replicas, or faster batch ingestion.
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Quantitative Data AnalysisReliability Analysis (Cronbach Alpha) Common Method...2023240532
Quantitative data Analysis
Overview
Reliability Analysis (Cronbach Alpha)
Common Method Bias (Harman Single Factor Test)
Frequency Analysis (Demographic)
Descriptive Analysis
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Round table discussion of vector databases, unstructured data, ai, big data, real-time, robots and Milvus.
A lively discussion with NJ Gen AI Meetup Lead, Prasad and Procure.FYI's Co-Found
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.