f[t_] := -0.024*sqrt[(x'[t])^2 + (y'[t])^2]*(x'[t])
g[t_] := -9.8 - 0.024*sqrt[(x'[t])^2 + (y'[t])^2]*(y'[t])
sol = NDSolve[{x''[t] == f[t], y''[t] == g[t], x'[0] == 11.63,
y'[0] == 8.14, x[0] == y[0] == 0}, {x, y}, {t, 0, 10}]
This is supposed to solve for the position of a projectile experiencing quadratic air resistance, but that error is what it keeps returning.
It’s a harsh truth that while data and technology in the fraud business abound, true domain expertise is a scarce resource. Meet Andy Procter, one of FICO’s fraud specialists. Having spent much of his career on the front lines fighting fraud at Citibank, Andy is now one of FICO’s Fair Isaac Fraud Advisors, where he specializes in fighting identity-based fraud including application fraud.
Today we are excited to pick Andy’s brain on the hot topic of how to fight identity-based application fraud.
Andy: I’ve seen many things that have shocked me, some for the sheer audacity of the perpetrator and others at the incredulity of the organization not having means in place to prevent them.
Andy: Credit risk is the bigger player in account originations. The overall question the organization is asking is ‘should we extend credit to this(these) individual(s)?’
To answer that, there are more underlying questions: Does the application meet with credit policy – do we think they can afford to repay? Will they be profitable? What terms should we offer? Are they telling us the truth?
Only that last question is of concern to the fraud team. In fact, even if they are telling the truth, are they a fraudster? To answer those questions there are equally many checks to do. The order of those varies across organizations according to their business preferences and other factors such as regulations. However, where possible I recommend a cost- and time-efficient process. This often involves early credit policy knockouts, followed by early fraud knockouts. Only after that should you go out and pay for additional information.
Once all information is in and knock-outs have happened, apply the credit risk policy to determine those you want to accept. The applicants left at that point pose a potential risk of fraud loss, so carry out the fraud checks then. Some clients save their pricing and limit setting until after the fraud check. I like this process: Any flags for potential first-party fraud that aren’t sufficiently strong to deny the application can still have an impact on the potential loss by impacting credit lines, limit increase periods, cross-selling periods etc.
Andy: Across the world, I’ve seen varying levels of automation with varying levels of success. If done right, automation is great – it gives a fast, consistent and smooth experience for applicants. After all, the fraud team as much as anyone wants genuine applications pushed straight through and low false positives. Some organizations think automated decisions are bad or even non-compliant. That need not be the case. Automated declines on limited information is a recipe for a headache, but data-rich applications with an automated decision to request additional information or trigger OTP, for example, can be positive even for false-positives.
Andy: Connected decisions – we use it a lot but it is valid. We certainly do see siloed set-ups. Sometimes we see the credit card team linked with the unsecured personal loans, but the auto finance, mortgage and SME/corporate loans have completely separate policies, processes and systems.
As long as I’ve been in fraud the key strength is sharing data – that’s what the fraudsters do. I’ve seen clients share with competitor organizations but not with other parts of their own business.
As well as connected decisions, a successful application fraud program requires three main practices:
Andy: Analytics. Feedback loops and defect analysis help drive false positives down. Also, I’ve seen some controversial fraud rules in my time, but some can be justified by their low false positives. Obviously, it is easy to lower false positives but not so easy to do it while maintaining or increasing the fraud detection rate (number of frauds found proactively by the detection tool as a proportion of all frauds detected).
The third metric in this trilogy is the referral rate. Most closely linked to the false-positive rate, this is the one that incurs the operational costs…and the one where human error comes into play. Some fraud teams have their strategies limited by the size of their operations team, some others have strict limits on referral rate placed on them by the business (without regard to the fraud rate of the organisation).
Regardless of the driver, the referral rate should be optimized in conjunction with the false-positive and detection rate.
For more on application fraud, check out the other posts in our series:
About Fair Isaac Fraud Advisors: FICO has a global team comprised of former fraud managers and domain experts who have a combined experience of 150+ years in fraud management. The practice helps organizations optimize operational processes, carry out complex analytical engagements, and build out a robust fraud program. They have undertaken engagements in 45 countries across 6 continents where they have coached and steered organizations towards best practices, data-driven approaches, and strategic change management.
Is your team as excited as mine is, about the Dynamics 365 October ’18 update? As soon as we heard about the upcoming features in this release, everyone on the Beringer Technology Group Dynamics Team was ready to dive in.
A key area in Dynamics 365 is the Marketing module, focusing on creating campaigns that put your company information in front of the right customer contacts. We are expecting the October ’18 release to cover a total of nine updates to Marketing features. In this blog I will be looking the at two of these exciting updates.
First, let’s talk about content. The key to reaching your audience is beautiful, persuasive content. A lot of effort goes into creating email content for campaigns, and it’s a real shame you cannot reuse the elements you spent the most time on. Oh, but wait, after the October ’18 release, you will be able to do this! Microsoft is introducing the capability to create “reusable content blocks”.
So, if your Marketing team creates specific headers or other elements that support your company’s branding effort, these can be saved and instantly used again. This allows your Sales, Service and every other team in the company to use the same content, for uniform messaging to all contacts through Dynamics 365. In addition, these reusable content blocks can be locked, so that the content is not altered, assuring that all communication has the same branding imagery. It won’t make your content “greener”, but it will save your company time on content design.
The other awesome new feature I want to share is the use of videos within Marketing content. We know that there is a strong trend toward using video content to demonstrate products, instead of flat images or text. With the October ’18 release, you can embed videos in your Marketing emails to help you grab and keep your targets’ attention. This will be accomplished through the designer’s toolbox by placing a “video block” element on your page and then selecting the video to display in the box.
These are just two of the many new features to come in Dynamics 365 October ’18. To read about all of the new features in this release, take a look at the overview site here:
Beringer Technology Group, a leading Microsoft Gold Certified Partner specializing in and . We also provide expert , , and
Katt Williams told police that Wanda Smith’s husband, Lamorris Sellers, pulled a gun on him and pointed it in his face outside the Atlanta Comedy Theater.
Comedian Katt Williams and Atlanta radio host Wanda Smith allegedly got into a fight outside the Atlanta Comedy Theater in Norcross that ended with Smith’s husband pulling a gun on Williams, according to a report from the Gwinnett County Police Department.
Smith and Williams reportedly started arguing at the club about an interview Smith did with Williams on Saturday, Sept. 15 around 9:30 p.m. According to the police synopsis, Williams told police that Smith’s husband, Lamorris Sellers, pulled a gun on him and pointed it in his face.
Williams and his security guard ran to the Food Depot next door to meet with police.
Sellers told police that Williams had a verbal fight with Smith, and Williams indicated he wanted to fight, according to the report. Sellers approached Williams and chased him into the Food Depot, then turned back to the Atlanta Comedy Club, police said.
Sellers admitted to police he had a gun, and that it fell from his waistband while he was chasing Williams, and he stopped to retrieve it, according to the report. He denied pointing a gun at anyone.
No independent witnesses came forward to talk with officers about what happened, according to police.
Gwinnett Police said surveillance video from the Food Depot surveillance cameras shows Sellers chasing Williams into the store, but does not show Sellers holding a gun.
The officer was told the Atlanta Comedy Theater has surveillance cameras but they could not be accessed at the time. Williams told police he did not wish the press charges.
Police said if the video surveillance shows any crimes, criminal charges could be filed.
Your business’s IT systems show their vulnerabilities when faced with disaster. Business owners always wish they had a more robust and safeguarded IT system when it’s too late: after a natural disaster like an earthquake, hurricane, or flood, or a human-caused attack like a computer virus or hacking scandal, has already struck. Be proactive– now is the time to institute disaster recovery systems and protocols before an IT disaster strikes.
Right now, Microsoft and other IT service providers are working with businesses in the path of Hurricane Florence to make sure they can get back up and running as soon as possible. Those with disaster recovery plans already in place had their data backed up to the cloud and their data restore services regularly tested before Hurricane Florence was even on their radar. They regularly reviewed their staff and customer contact lists and made sure their virtual cloud systems were working once their on-premises systems inevitably lost power in the event of a disaster. The catastrophic flooding brought by Hurricane Florence may have already destroyed these businesses’ IT systems, but they will be quickly replaced and back up and running as soon as those business owners are ready to open their doors again– even if those doors are virtual while their brick-and-mortar locations are repaired.
Unfortunately, businesses with robust disaster recovery protocols are in the minority. Many businesses will be suffering the consequences of data loss and other IT disasters in the wake of Hurricane Florence for months or years ahead, or may never open again as a result.
Learn from these businesses today and have a plan in place for when disaster strikes in your area. Unfortunately, that once a business loses a significant amount of data, 93% of them shut down within the next 5 years. 80% of those close within a year, while a staggering 43% immediately shut down and never open back up again. Your business, and everything you’ve worked hard to achieve with it, deserves more than getting washed out with the next flood or computer attack.
Consider this: when was the last time you backed up the data for your business, and where are those backups located? If you answered that they are on the same premises as your business, that backup data is just as exposed to a disaster as your primary IT systems. Would you be able to absorb the cost of the significant time it would take to restore that data? What if you lost that data; what would that mean for your organization?
Eric Raff, Cloud Solutions Architect at JourneyTEAM, says that with “today’s modern technology… modern businesses don’t need to suffer a setback or shut their doors” once an IT system failure occurs. JourneyTEAM is a Microsoft Gold Partner and can help evaluate your company’s infrastructure. They will provide you with a custom Managed Disaster Recovery Plan to account for any IT disaster that may strike. Their customized Microsoft Azure Recovery Strategy will assess any potential impacts, account for your existing systems like Dynamics 365, Office 365, and SharePoint, and create a response plan.
Become a proactive business owner in the face of potential IT disasters. or give them a call at 800-439-6456 and assess or create your business’s Disaster Recovery Strategy today. Once catastrophe strikes, you’ll be glad you did!
Article by: Dave Bollard – National Director of Marketing
JourneyTEAM is an award-winning consulting firm with proven technology and measurable results. They take Microsoft products; Dynamics 365, SharePoint intranet, Office 365, Azure, CRM, GP, NAV, SL, AX, and modify them to work for you. The team has expert level, Microsoft Gold certified consultants that dive deep into the dynamics of your organization and solve complex issues. They have solutions for sales, marketing, productivity, collaboration, analytics, accounting, security and more. www.journeyteam.com
TIBCO NOW presented a unique opportunity for the C-level executives in attendance. In parallel with the annual conference on September 5-6, TIBCO held the Executive Summit, catering to executives across all companies and industries. With over 40 executives in attendance, it was a great opportunity for networking and for companies to learn about how they can implement their own innovation initiatives.
The purpose of the event was to give a condensed, C-level experience around innovation at the edge, the theme of this year’s user conference. This event was exclusive by invitation only to bring together some of the best minds in innovation and digital transformation. Attendees consisted of TIBCO customers, partners, and other special guests.
After a networking dinner the evening of September 5, the summit officially opened the morning of September 6 with opening keynotes from TIBCO CEO Murray Rode and COO Matt Quinn. The two executives talked about innovation from the TIBCO perspective as well as their own, while answering questions from the crowd. During the morning, attendees also got to hear from the CEO of Change Healthcare (a TIBCO partner), Neil De Crescenzo, about innovating in the healthcare industry and serving their customers with analytic insights.
Afterwards, TIBCO CTO Nelson Petracek hosted a blockchain panel with the CTO of Change Healthcare, Aaron Symanski; Martha Bennett, an analyst at Forrester, and Manager for Blockchain, Carlo Donadio, from Accenture. The panel discussed how companies are leveraging the emerging blockchain technology for business use cases. This wasn’t a discussion of the technology itself, but rather how it can be used for innovation and improving businesses from a line of business perspective.
The summit continued with TIBCO’s Senior Director of Analytic Strategy, Shawn Rogers, who shared the results of the 2018 TIBCO CXO Innovation Survey. The survey was an in-depth research study conducted with over 550 respondents worldwide about how and why today’s businesses are innovating. The results clarified that the companies who are investing in digital transformation are more successful than those who are not. Businesses who have digitally transformed are constantly innovating to disrupt their industries. On the other hand, those who are not investing in digital transformation find it more difficult to disrupt their industries.
The afternoon kicked off with a fireside chat between Dr. Peggy Whitson, former NASA astronaut, and TIBCO CMO Thomas Been. The chat focused on innovation in space, a preview of what the audience was going to get from her keynote at the final general session later in the day. Then, Rode chatted with Brian Sheth from Vista Equity Partners about innovation from Vista’s perspective.
As the afternoon progressed, Quinn came back to host an artificial intelligence/machine learning panel for those in attendance. The panel consisted of VP of Product Management at Marketo, Ajay Awatramani; Managing Director at Morgan Stanley, Katherine Wetmur; VP of Technology and Innovation at PerkinElmer, Karen Madden; and Senior Product Manager for SageMaker at Amazon Web Services, Kumar Venkateswar. The panelists gave perspectives about the use of AI and ML from the eyes of the business user and how it can improve operations and customer experiences across companies.
The Executive Summit concluded with Rode and Managing Director Murat Sönmez from the World Economic Forum discussing their final thoughts on innovation from a world perspective. This served as the final takeaway for attendees to take back to their own companies to inspire the beginning of their own digital transformation journeys.
In order to get an organization on board with innovation efforts, it must first come from support at the C-level. This Executive Summit was catered specifically towards executives with this in mind. It provided a valuable learning opportunity and experience for those at the C-level to get inspired to innovate at their own companies while learning how others are doing it at theirs.
UiPath, a robotic process automation (RPA) platform that helps companies automate repetitive tasks, has raised a whopping $ 225 million in a series C round of funding co-led by Alphabet’s late-stage venture capital (VC) fund CapitalG and Sequoia Capital, with participation from Accel.
This latest raise comes just six months after UiPath raised $ 153 million in its series B round, and the company has now raised north of $ 400 million since it was founded in 2012.
Additionally, the company said that its valuation is now pegged at $ 3 billion, up nearly $ 2 billion since its series B round valuation in March.
UiPath was founded initially out of Romania, though it is now officially headquartered in New York. The platform’s core selling point is that it brings automation to enterprises’ processes. It builds what it calls “intelligent software robots” that help businesses carry out what are often laborious and repetitive tasks using computer vision and rule-based processes.
Above: UiPath Studio
The technology sits atop business applications such as enterprise resource planning (ERP) software and customer relationship management (CRM) tools to emulate a task that is usually carried out by a person sitting manually pressing buttons at their desk. These “robots” are trained to observe the interface to see and understand what is happening, and then carry out the task as a human would.
As with all machine learning applications today, the ultimate promise here is that it improves accuracy and productivity, allowing human employees to focus on other areas of work. Or, as a more cynical person might conclude, put humans out of work.
“We are enabling a future where employees at every organization are empowered to automate tedious and time-consuming work, enabling them to focus on creative, challenging problems,” UiPath cofounder and CEO Daniel Dines said.
UiPath claims some big-name clients already, including NASA, Airbus, HP, DHL, Equifax, Lufthansa, Autodesk, and nearly 2,000 companies around the world. Without giving specific numbers, UiPath said that it expects its annual recurring revenue (ARR) to increase by 400 percent by the end of this year compared to 2017, while it anticipates its employee headcount to grow 300 percent to 1,700 across 16 countries.
With another $ 225 million in the bank, it added that it plans to accelerate its product development, build out its partnerships, and acquire some more companies. The company made a rare acquisition earlier this year, when it snapped up a software platform belonging to Cluj-based smart data company Recognos, but UiPath hasn’t made any other known acquisitions in the past.
“We strongly believe that RPA is a primary route for organizations to benefit from AI, and UiPath is proving this potential with its unparalleled growth and incredible customer impact,” added CapitalG partner Laela Sturdy.
Last week, I ran my friend and thought leader Esteban Kolsky’s first part on how to think about data in a post-big data world — and it was a hit. Now, to end the suspense, we have part two, where EK looks at how data impacts B2C and B2B differently and what has to be done with that data. All this came as a result of research Esteban was asked to do by Radius, as I mentioned last week. Kudos to them for inspiring this excellent piece.
So, now, Esteban, onto part two.
What did you think of the last post on evolution of data?
If you know where you came from, you know where you are going. And to see where we are going, we need this second part: How have data platforms evolved?
Data has been the “blood” of business since the early days of computing in the 1960s. Along the way changes brought different tools to collect, store, process, and manage data, all the while not asking the essential questions: Why are we doing this? Why do we need data? What are we doing with it? How do I know if we are doing the right things?
There is a difference in how data affects traditional mass market (B2C) organizations and those that sell to other businesses (B2B). There are issues related not just to the potential size of the market (a B2C company targeting hundreds of millions of potential customers versus a business targeting a few hundreds to a few thousands of other organizations) but also the complexity of the data models used.
Also: IBM Cloud Private for Data preps Red Hat OpenShift certification, queryplex search tool
We’ve had data aggregation happen in mass market organizations (buying and aggregating credit card information, for example, or collecting and sharing loyalty information about customers’ needs and actions) for a long time — we call that segment differentiation in B2C organizations. While this aggregation is interesting for those organizations, it is also far simpler than doing it for B2B worlds. And the tools necessary to solve those problems are focused on managing large quantities, not in focusing on the best data.
In a B2B world, the problem becomes more complex and requires better tools and processes to be resolved. We cannot say that, for example, 120 of our 200 potential targets belong to the same segment. It becomes impossible to differentiate and very hard to serve properly.
We need better data models that are more focused on our sales processes and our customers’ intents.
Also: Apache Flink takes ACID
The amount of data is not a problem in B2B, as in B2C markets, because the potential markets are far smaller, making the data easier to find, but the quality and aggregation of the data represent a bigger challenge. This is where data platforms began to shine.
A combination of easy access to the right data for multiple purposes and generating effective insights is what makes data platforms and insight engines so powerful — not just the data aggregation. It is not the amount of data stored and potentially used, but the necessary data that is used at the appropriate time. We need to rely on aggregated data to optimize processes and on the and insights generated from those transactions.
The chart shows the evolution of data platforms and data storage over time, including the pros and cons of each. It also includes guidelines as to what each model can accomplish and how it works best.
Matching these tools to the planned outcomes from using data is the first step in generating insights and this is not without problems.
Also: Digital transformation: Getting beyond the hype
The amount of data stored after big data systems were deployed has created, or exacerbated, the three critical problems for B2B companies seeking to optimize data in their digital transformation initiatives:
1. Trusted data aggregation: When organizations have too much data from too many sources, some of the datum may overlap and even conflict. Using insights as the outcome of aggregating data in platforms differentiates between trusted data sources based on the outcomes of the processes and those that should not be used as much.
2. Simple access and updates: Just because the data was collected, aggregated, and stored does not mean that the data is never going to change. In our always-on-the-go world, data changes as often as many times a day (in case of operational data) to every few weeks (in case of segmentation or identifying data).
3. Optimized data use: Business functions rely on having the most accurate and most current data to make the proper decisions. Businesses in the digital era demand the right data at the right time, to make the right decisions.
Until now, organizations have used most of the tools described in the chart to aggregate, consolidate, and centralize data in different versions of platforms used by myriad processes and functions. While this has given them a starting point and the illusion of movement and progress, the reality is that for B2B organizations making data-based decisions in real time requires not just more data but better-quality data and insights. Tools that simply focus on aggregating data regardless of the use of it don’t understand what’s needed and can’t do the job.
Also: Big data is now economics and not just technology TechRepublic
Master data management, for example, is a discipline and set of tools that focused on aggregating as much data as possible. This is done for creating a better centralized store of data that then becomes “the single source of truth.” While it creates massive, optimized data stores, there is no purpose or knowledge of the outcome, thus it misses the mark on knowing or highlighting what data to collect, store, and use for each different process.
Customer data platforms are a more modern model and intends to solve the problem of MDM systems by going beyond simply creating a single source of truth to focus on uses for that data. It consolidates data, provides access to many different systems, and ensures that data flows freely from A to Z and is used appropriately in between for known processes. While it does a good job of creating an ODS (operational data store) on the cloud, it fails in the same places where huge data stores failed: It does not know what happened to the data once it was used, whether it was good or needs to be updated or improved, and what were the outcomes.
Very often, data-use initiatives are focused on achieving one or more KPI change: Increase revenue, decrease costs, generate more customers, and many others. Traditionally, methodologies already exist for achieving these simple outcomes. For example, to acquire more customers, the steps are simple: Identify a target segment, understand what they need, create an offering that fulfills that need, generate marketing to match the need and identify customers, implement high-pressure sales tactics, and close the deal.
Thus, the next time more customers are needed, a variant of the above will be implemented, and results will be there. It has proven to work well so many times, it will continue to be repeated — usually the same way as before. With data platforms and aggregated data, the system can optimize the above model so that it reflects both real-time needs as well as lessons learned and insights from past occurrences.
If an organization wanted to optimize or transform based on lessons learned, it would create some sort of report post-event and analyze what could’ve been done differently. This is a way to generate delayed insights (or post-facto insights). It works but does not help optimization since by the time we learned what needs to be done, the event is over, and changes cannot be made anymore.
Also: Turning Big Data into Business Insights
Learnings and changes can be made in near real-time using real-time insights, artificial intelligence, and advanced analytics. Optimizations happen quickly, and results are captured dynamically, creating the insights that help improve the event this time and every other time. Campaigns can be optimized with a better message, sale cycles can use updated pricing and even bundling, marketers can use better content that has seen results, and so forth.
Instead of waiting until the end and potentially the next event to see if changes worked (and in the process ignore the fact that conditions changed already between events), an organization can use insights from aligning the right data, the right processes, and the right outcomes to improve operations on the fly.
Of course, to do this requires not just a different set of tools (not focused on storing and aggregating data only) but also a different mentality. And a different methodology.
And for that, we have a framework — but you will have to download the paper to see what it is.
Back to you, my friend.
Thank you, Esteban. This was awesome. Come back if you want to expand on this — anytime.
NOTICE: The CRM Watchlist 2019 registration and the registration for The Emergence Maturity Index Award for 2019 is closing on Sept. 30 with no extensions possible. So, if you want to make sure that you are part of these (see the links in the names for the details), then you have roughly two weeks to go (a little less). I’d do it, if I were you, though I’m not. You, that is.
To request the registration form for either of them, please email me at mailto:paul-greenberg3@the56group.com.
What to do with the data? The evolution of data platforms in a post big data world
Thought leader Esteban Kolsky takes on the big question: What will data platforms look like now that big data’s hype is over and big data “solutions” are at hand?
The past, present, and future of streaming: Flink, Spark, and the gang
Reactive, real-time applications require real-time, eventful data flows. This is the premise on which a number of streaming frameworks have proliferated. The latest milestone was adding ACID capabilities, so let us take stock of where we are in this journey down the stream — or river.
Arcadia Data brings natural language query to the data lake
Arcadia Data provides a search engine-style text box as its latest query interface, bringing BI natural language query to the data lake.
This startup thinks it knows how to speed up real-time analytics on tons of data
Making sense of the vast amounts of data gathered by businesses is a problem for business that Iguazio says it’s cracked.
Digitalist Magazine, online edition, covers a wide variety of topics around the challenges businesses face in the digital economy. Whether you’re interested in the future of work, customer experience, digital economy, the Internet of Things, or digital supply networks, we provide a vast array of thought leadership and real-life stories on the practical application of digital technology.
Each week on Digitalist Magazine, the editorial team discusses its top picks of the week from across our content categories. Here’s a list of blogs that caught out attention this week, and we hope you find these articles valuable, informative, and interesting too.
Ensuring A Healthy Future At The Nelson Mandela Children’s Hospital
Tariffs, Inventory Optimization, And Digital Business Planning
Canine responsibility.
“Good boy feeding the farm animals!.”
Image courtesy of https://imgur.com/gallery/ZvNSk7K