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Qlik FinServ

A private group designed to enable innovation, share best practices and educate QlikView users in the Financial Services industry. You will not see any content if you are not a member, you can request to join by pressing "Join the Group"

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  • Insurance Claims 2019 - Updated

    A very Happy 2019 to you all.  I thought I'd start the year off in our new Community Site with an updated version of the Insurance Claims Ap... Show More

    A very Happy 2019 to you all. 

    I thought I'd start the year off in our new Community Site with an updated version of the Insurance Claims App I created several years ago.  The main update to the app is a new sheet that showcases the new Alternate States capability recently introduced to Qlik Sense... 

    Comparative Analysis.png

    This allows a user to directly compare the data for 2 different dimension values side-by-side.  
    Of course this capability exists in our sister product QlikView, but it's great to have it now in Qlik Sense.

    You can access the new app here from my Download site...
     https://qliktechnologies365-my.sharepoint.com/:u:/g/personal/skb_qlik_com/EYspCvLeIYFArnMMXPoBOP4BcJgAR4lCNyJMvDdDaaZSVA?e=KFYQc9

    Watch this space for further updates and new Insurance Apps this year. 

    Simon

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  • Drag & Drop into Office applications

    We use Qlikview since V10 and upgraded it to Version 11 and in due Course the upgrade to V12 will follow.Since  V10 we tested with Windows 10 and... Show More

    We use Qlikview since V10 and upgraded it to Version 11 and in due Course the upgrade to V12 will follow.
    Since  V10 we tested with Windows 10 and the diffrent Office versions (now Office V16) the Drag&Drop functionality of Charts in our Qlik Reports into PowerPoint but were unable to get it done. There is a green shadow on the selected Chart but then no further step is possible. The Export of the data's into an Excel sheet works but not the Chart. What could be the reasons? We asked during the update of V11 developpers in the UK which could not help us during a webconference.
    Thank you in advance for your replies.

    Best Regards,

    Nicolas

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  • New and Improved: Finance Toolkit 2.0

    We recently embarked on a project to update the Qlik Finance Toolkit for the following reasons:Finance and Accounting use cases are taking off (both i... Show More

    We recently embarked on a project to update the Qlik Finance Toolkit for the following reasons:

    As time has gone by since the original post on Qlik Community, I have worked with customers, partners and other Qlik employees to overhaul and modernize with the latest and greatest.  Thanks to all involved, it has been a team effort!

    So here it is, our second round, the new & improved version of the Finance Toolkit:

    https://demos.qlik.com/qliksense/FinanceToolkit?function=Finance

    More to come on this in the form of videos & blogs but wanted to use this forum to announce that the new version has been posted on the demo site.

    Enjoy and share this with your Finance, Accounting and Audit co-workers!

    PVS

    (note:  if you sign into the demo site, you can download the demo itself)

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  • Stock Prices - Volatility, SMA & Bollinger Bands

    Tinkered with some formulas to start building a Stock Price Technical Analysis app, right now i have these things built into it and will continue to a... Show More

    Tinkered with some formulas to start building a Stock Price Technical Analysis app, right now i have these things built into it and will continue to add:

    - Volatility

    - Historical Volatility

    - 20 Day Moving Average

    - Upper Bollinger Band

    - Lower Bollinger Band

    - Dynamically linked to Google News based on Dates selected

    Qlik Community help acquired from several great posts but here were two of the best resources:

    etk‌ post on 'Accumulative Sums'

    kush141087‌ post on Bollinger Bands in QlikView

    Both were extremely helpful...thanks!

    2018-04-10 15_24_35-Barchart Stock API Data - Copy - BarChart API Data - AMZN _ App overview - Qlik .png

    Instructions on setting up:

    1. Download QVF and save the file in qlik/sense/apps folder (see attached .qvf file)

    2. Install variable extension (use your favorite, I am not sure the name of the one i am using), reload button & mediabox extensions

    3. to re-run the script, you need to get a free key from barchart.com.  Then go into the script and past your API Key on line 62.

    2018-04-10 15_52_35-Barchart Stock API Data - Copy _ Data load editor - Qlik Sense.png

    4. In addition, add a "connection" called "Barchart Historical API" using the following:

    https://marketdata.websol.barchart.com/getHistory.json?apikey=PASTEYOURAPIKEYHERE&symbol=$(vTicker)&type=daily&startDate…

    2018-04-10 15_36_29-Clipboard.png

    That should do it, you now have access to the Qlik Sense Stock Price Technical Analysis.  Would love for people to add additional analysis to this and post it back.

    PVS

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  • applymap function

    hi Teamone of my requirement says to bring a new field into the existing table .so i used applymap to bring the new field, I did like shown below,Fac_... Show More

    hi Team

    one of my requirement says to bring a new field into the existing table .

    so i used applymap to bring the new field, I did like shown below,

    Fac_Fee_map:

    Mapping

    LOAD facility_id,

         FMSPrePaymentFee

    FROM $(vQVDPath)fac_fee.qvd (qvd);

    ApplyMap('Fac_Fee_map',FMSFacilityID, null()) as FMSPrePaymentFee,

    but i see difference in the facilityID's, i want to get all the facility Id's data, can anyone suggest me how to do that?

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  • Qlik Sense and the App On-Demand

    There has been significant chatter over the past several months about On Demand App Generationand how this approach expands the potential use cases fo... Show More

    There has been significant chatter over the past several months about On Demand App Generation

    and how this approach expands the potential use cases for Business Discovery, enabling business users to conduct associative analysis on larger data sources.  We at Bardess Group Ltd. became very excited about the possibilities of applying this approach to FDIC Summary of Deposits data that we had modeled a few years ago, and running that data through Alteryx to go even deeper with our analyses.


    We have developed a custom "app on demand" extension that can be configured to send data through other data engines, read the output back into Qlik Sense, and load the enhanced data set into a new application for focused analysis.  We happen to think it's pretty great, and invite you to try it yourself.  We also just posted the extension to Qlik Branch.

    Thanks to Ian Crosland , Paul Van Siclen and others at Qlik for collaborating.

    App-On-Demand_Flow.png

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  • New utility to monitor QlikView Server usage

    Hello, This utility reads in QlikView Server session logs from a user configured windows folder. The dashboard shows # sessions, # distinct users, pea... Show More

    Hello,

    This utility reads in QlikView Server session logs from a user configured windows folder. The dashboard shows # sessions, # distinct users, peak concurrent sessions, cumulative duration of sessions and a session:user ratio.

    The utility can be used to analyze peak concurrency events, solution adoption, most active users (and candidates for Named Cals), and it  drills down to individual session details (sessions tab). Use the trend chart on the concurrency tab to drill down to the minute level of detail !

    Hope you find it handy and feel free to send me your suggestions.

    Jonny

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  • A Qlik Financial Services compass

    Hello FS Group,I posted a blog last month that provides an overview of our external facing industry content.  This includesTop 12 Solution in FS ... Show More

    Hello FS Group,

    I posted a blog last month that provides an overview of our external facing industry content.  This includes

    Top 12 Solution in FS whitepaper

    Resource Library - webinars, whitepapers and videos

    QlikView and Qlik Sense demos on Demo Site

    Qlik Community FS Group (here)

    My Qlik Cloud account


    Check it out here:

    http://global.qlik.com/us/blog/posts/paul-van-siclen/a-financial-services-compass

    i just ran some analytics on the number of views of this group and am impressed with the number of people utilizing this resource.  We will strive to continue to post and keep you updated on industry related content.

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  • Bank stress-testing analytics with QlikView and Deloitte

    Hello Financial Services Group QlikCommunity members:We held a very interesting webinar with Deloitte this week and I wanted to pass along a the link:... Show More


    Feel free to post your comments on this discussion thread!

    Paul Van Siclen

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  • Financial Services Master Data Management (MDM) Console

    With increasing regulatory obligations and potential for litigation aimed at the Financial Services industry over recent years, Master Data Management... Show More

    With increasing regulatory obligations and potential for litigation aimed at the Financial Services industry over recent years, Master Data Management (MDM) has become a hot topic for most (if not all) firms in this sphere. Here we demonstrate our Qlik Sense driven solution to managing some of the most frequently encountered MDM issues.

    The core principle of the MDM process concerns referencing source data against master records and resolving any exceptions. This can be achieved in numerous ways but one of the most exciting and innovative solutions involves the use of blockchain technology.

    A private blockchain will improve data governance and create a fully transparent MDM workflow for all parties involved. The blockchain contains a set of pre-defined rules that act as the gatekeeper of data quality, regulating the way in which data is mapped to existing records, and governing the conditions that allow the creation of new records.

    Our demo app is based on a Transactional FX Business and provides a method for appraising Master Data Management performance as well as a route to improving MDM processes. In this app, we focus on data steward performance from a product and client master data perspective.

    Check out our demo video attached. If the situations described sound all too familiar, and you are looking for a rapidly deployable, versatile and effective solution to your MDM challenges, we would love to hear from you. Our website is pomerolpartners.com.

    Video Link : 4792

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  • Information Analyst & QlikView Developer - Majedie Asset Management, London, Uni...

    Job descriptionWe are looking to recruit an information analyst to assist in developing and maintaining our BI applications, alongside ad hoc data and... Show More

    Job description

    We are looking to recruit an information analyst to assist in developing and maintaining our BI applications, alongside ad hoc data and programming projects for our other information systems. The successful candidate will join a small, close-knit team with a strong collegiate culture. Majedie’s information team is very much integrated within the wider business, and so the ability to communicate with colleagues across all levels is important.

    Required skills and experience:

    • 2 years’ solid experience of developing/designing applications in QlikView or QlikSense, including advanced data models and expressions
    • Good knowledge of Microsoft Excel
    • Numerate and analytical
    • Track record of picking up others’ development work
    • Familiarity with SQL technologies would be a bonus
    • Experience or familiarity with the asset management industry would be advantageous but is not essential

    This is a full-time, permanent role based in London - candidates must have a UK work permit.


    We are looking to fill this position as soon as possible.  This is a permanent full-time role based in the UK.

    Company


    Majedie Asset Management, established in 2002, is an independent investment boutique that actively manages equities for institutional investors, wealth managers and endowments across a range of UK and Global strategies.


    Majedie was founded by a team from Mercury Asset Management with a clear aim: simply to make money for our clients. We are proud of our distinctive, long-term track record - but remain as hungry to perform today as we were on day one.


    Importantly, every Majedie employee owns equity in the business; we are in partnership with our clients and here to stay. Similarly, our fund managers all invest in Majedie funds, further aligning our interests with those of our clients.


    We view our capacity as scarce; we believe investment performance suffers from diseconomies of scale if assets under management grow too large. We are determined to maintain the size advantage for our clients and therefore limit the available capacity in each of our funds.


    Assets under management total approximately £11bn ($16bn).

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  • Quantitative Risk Analysis - Monte Carlo Simulation in Qlik Sense

    What is it?This demonstration is a quantitative risk analysis of a single project that demonstrates the speed of the Qlik engine and the ability to no... Show More

    What is it?

    2016-05-20 16_19_50-Monte Carlo Simulation - Quantitative Risk Analysis - Single Project Example _ S.jpg

    This demonstration is a quantitative risk analysis of a single project that demonstrates the speed of the Qlik engine and the ability to not only interact with the model but also drill through to the detailed model output.

    The model in this case is the "Total Profit Equation" and an analysis of the range of possible outcomes provided the model assumptions.


    Total Profit = (Price * Quantity Sold) - (Variable Costs * Quantity Sold) - Fixed Costs


    This is a simple example for demonstration purposes.  The technique can be ported into virtually any model for many other use cases.  Here are some examples I captured from a document I found on the web (written by Natalie Humphreys, Associate Head of Actuarial Program at University of Texas):

    1. General Motors (GM) uses simulation to estimate both the average return and the riskiness of new products.
    2. Wall Street uses to price complex financial derivatives and also determining Value at Risk (VaR) of an investment portfolio
    3. Procter & Gamble models an optimally hedged foreign exchange risk
    4. Financial Planners determine an optimal investment strategy for their clients' retirement

    All interesting (and possible) and this particular model is simply a basic template to head down the path.

    How to get started:

    Step 1: Install Qlik Sense Desktop and download the .qvf file to qlik/sense/apps directory

    Step 2: Go to Branch.Qlik.Com and install the following Qlik Sense extensions:

    Step 3: Make adjustments to the inputs

    Step 4: enter the number of Simulations you want to run/analyze

    Step 5: Click on the Reload button

    I find it best to interact with this app through my browser, to navigate through the browser, you type in the following url: http://localhost:4848/hub/my/work (make sure Qlik Sense Desktop is running)

    Some add'l notes:

    • Thanks to Brian (https://community.qlik.com/people/bbu‌) @bbu for building the baseline Monte Carlo Simulation in Qlik Sense.  I have enhanced his great work and am posting here for the broader community.
    • Thanks to hic for his description on how to build a histogram in Qlik.  This was a great improvement and here is his post that i used (Note that it worked slightly different in Qlik Sense but similar/same result: Recipe for a Histogram
    • A Normal Distribution is used for every variable.  I kept it this way to keep it simple but hic‌ also talks about distributions in Qlik here: Monte Carlo Methods
    • The current file is set at 1,000 simulations but feel free to move it to 100,000 to see how long it takes to run a larger model set.  What about 1 million simulations?
    • At Qonnections 2016 this year, Deloitte presented a model of a gold mine that forecasted a full balance sheet, income statement and cash flow of a gold mine with every variable being simulated.  Further, it uses Qlik's powerful Time Value of Money functions to calculate the Net Present Value of Free Cash Flow generated by the model.

    Enjoy,

    Paul V.S.

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  • Stock Performance (Relative to Benchmark)

    HiI've a table which shows performance of stocks. In 1st column there's list of stocks and in the 2nd column performance of each of the stocks. Now is... Show More

    Hi

    I've a table which shows performance of stocks. In 1st column there's list of stocks and in the 2nd column performance of each of the stocks. Now is need to add a third column which represents the performance of the benchmark which is S&P500. The tricky part is when I add the third column for S&P 500 returns it needs to be static i.e. the return of S&P500 will be the same number repeated for each of the rows irrespective of the corresponding list of stocks in each of the rows.

    Please look at the attached image and kindly help if you can?

    Thanks

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  • Finance Toolkit

    Hello Qlik Financial Services community members,Qlik Sense v2.1 was recently released and this new version provides a method of creating/editing varia... Show More

    Hello Qlik Financial Services community members,

    Qlik Sense v2.1 was recently released and this new version provides a method of creating/editing variables.  With this new functionality, I decided to take a shot at consolidating some of the tools I have created into one killer Finance App.  The app has been pretty popular so far so I added some additional functionality and am posting it here.

    Here is a YouTube Video/Webinar that walks through the app:

    FinanceToolKit.png

    A brief explanation of the tabs in the application:

    1.  Introduction to the Associative Model

    This is a simple view of several list boxes which demonstrate the ability of the user to drive analysis through an unlimited combination of Divisions, Products, Cost Centers and Accounts.

    2.  Essbase Expenses

    The source of this tab is an essbase extract.  Note that a QlikView connector is available on our download site which can completely streamline this process and we have several customers who have successfully implemented this.  I don't have a date when the Qlik Sense version of the connector will be available but you can copy the script from QlikView and paste it into Qlik Sense.

    3.  Stock Price Analysis

    Data captured from HTML tables provided by the Nasdaq site.  You have the ability to type in any ticker and click on the Reload button to capture a different set of data.

    4. Valuation

    This is a dynamic IRR calculation on a population of 299 different investments.  An unlimited combination of dimensions can be selected to see the IRR.  The formula being used here is =rangexirr() which is a very powerful function for this purpose.  I have used this to value a actual portfolio of earning assets in the past and it was very powerful.

    5. CAGR

    The =Rate() function calculates the Compound Annual Growth Rate of a portfolio.  Data is made up of 2 divisions (Commercial and Consumer) and 30+ business units.  The power of this analysis is that the CAGR formula is tied to the dates selected.  For example, make a selection on the last 5 quarters and compare that portfolio CAGR to the previous periods.

    6.  Amortization, Forecasting & Time Value of Money

    If you can create an accurate model for a single loan, then you can model an entire portfolio.  This is a Single Loan Model which forecasts the AUM and Interest Income over the selected term of the loan.  It is not a stretch to combine this with other data points/vintages and build a model for an entire portfolio.

    7. Break Even Analysis

    A simple formula applied to the "profit equation" displayed in a "Line" which is an important step to the next few tabs.

    8. Option Valuation & Greeks

    Demonstrating the inputs related to the Black-Scholes model (which is a built in function of Qlik).  The chart is simply demonstrating the impact of changing the volatility assumption on the price.  The higher the volatility, the higher the value/price.

    9.  Simulation

    The total profit equation with one of the variables (Price Per Unit) assigned to a normal distribution with a Standard Deviation assumption.  This entire simulation is calculated in memory and becomes very interesting when you add a 0 to the # of simulations (1000; 10,000; 100,000 simulations all run very quickly on my laptop).  Used in practice, you may consider putting this formula into the script, build a table, store the model in a qvd (with other scenario runs) and reload all of the data into memory.

    10. DataMarket - FX Conversion

    Demonstration of FX Conversion with currency data from Qlik DataMarket.

    -------------------------------------------------------------------------------------------------

    To get all of this to work, you need Qlik Sense Desktop v2.1 and to follow these instructions (can be completed in 10-30 minutes, depending on your familiarity with the steps):

    1.  Download the app called FinanceToolkit20150916.qvf into your Qlik/Sense/Apps folder


    2.  Download/Install the following Charts extensions from QlikBranch in Qlik/Sense/Extensions folder

         http://branch.qlik.com/projects/showthread.php?498-Qlik-Sense-Reload-Button&highlight=reload+button

         http://branch.qlik.com/projects/showthread.php?379-Sense-Boxplot&highlight=boxplot

         http://branch.qlik.com/projects/showthread.php?396-qsVariable&highlight=variable

    + the Horizontal List extension added to this post

    3.  Download these source files in a directory of your choice (i.e. c:\FinanceToolkitData)

        - PortfolioData.xls,

        - Data.xls,

        - Dim.QVD

        - Fact.QVD

    4.  Go into the "Data Load Editor" of the app and re-point each data source to the directory you put your source files in

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  • How Lending Institutions use Qlik

    Video Link : 4036 The above video was recorded for the purpose of discussing Qlik Visual Analytics uses cases for lending institutions.  There a... Show More

    Video Link : 4036

    2016-02-08 14_54_35-Qlik Sense Desktop.jpg

    The above video was recorded for the purpose of discussing Qlik Visual Analytics uses cases for lending institutions.  There are three areas discussed:

    1. Pipeline Analytics - Approval ratios, Conversion ratios, Days to Fund, Prioritizations, etc
    2. New Business Volume - proforma profitability of newly funded business
    3. Portfolio Analytics - performance of a loan portfolio over time

    The first demo is using data from a company called "The Lending Club" that is a P2P FinTech lender that has made its loan data publically available on this site:

    Lending Club Statistics - Lending Club

    The four .CSV files were downloaded and imported into Qlik Sense to develop the demo discussed in the video and the demo is attached to this post.

    Things to look out for:

    • 700K records analyzed; aggregations NOT pre-built but all calculated on the fly
    • All metrics use weighted averaging based on loan amount (yield, credit score)
    • Dynamic Compound Annual Growth Rate
    • Natural language "Dynamic Variance Analysis" provided by Qlik Partner Narrative Science
    • Trended Yield/Interest Rate for total portfolio held on chart to compare to Trended Yield/Interest Rate for selected portfolio.  Achieved through a differentiator call "Set Analysis"
    • Global Search across entire data set (for example, search on "60 months AZ 2014" for all 60 month term loans originated in Arizona, in 2014.
    • Scatter diagram on second page provides some visibility into the pricing practices at the Lending Club.



    Extensions needed for this application:


    Narratives for Qlik® | Free Narrative Extension for Qlik Sense® | Narrative Science


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  • Aggr. Function

    I want to create a continuous line chart with the output of the set analysis below.  I believe i can do it with the AGGR function.  I think ... Show More

    I want to create a continuous line chart with the output of the set analysis below.  I believe i can do it with the AGGR function.  I think the issue with my output is that I need the chart to ignore the Curve Date (always selected).

    =sum({$<[DealType]={'NG Storage Contract', 'NG Pipeline Contract'},[FlowMonth]={"$(vCurrentAcctMo)"}>} [ProfitLoss])/MaxDaysInMonth*(day(CurveDate))

    +sum({$<[DealType]={'NG Fin NYMEX*','NG Fin Basis*','NG Fin Fixed*','Futures'},[FlowMonth]={"$(vCurrentAcctMo)"}>} [ProfitLoss])/MaxDaysInMonth*(day(CurveDate))

    +sum({$<[DealType]={'NG Fin NYMEX*','NG Fin Basis*','NG Fin Fixed*','Futures'},[FlowMonth]={"$(vCurrentAcctMo)"}>} [Adjusted ProfitLoss])/MaxDaysInMonth*(day(CurveDate))

    +sum({$<[DealType]={'NG Ph*','NG Simpl*'},[FlowMonth]={"$(vCurrentAcctMo)"},[RiskType]={'Unknown'} >} [ProfitLoss])/MaxDaysInMonth*(day(CurveDate))

    +sum({$<[DealType]={'NG Fin Index*','NG Fin Swing Swap'},[FlowMonth]={"$(vCurrentAcctMo)"},RiskType={'Settled','Unknown'}>} [ProfitLoss])

    +sum({$<[DealType]={'NG Fin Pipeline*'},[FlowMonth]={"$(vCurrentAcctMo)"}>} [ProfitLoss])

    +sum({$<[DealType]={'NG Fin Swing Swap','NG Fin Index*'},[FlowMonth]={"$(vCurrentAcctMo)"},[RiskType]={'Cash'} >} [ProfitLoss])

    +sum({$<[DealType]={'NG Ph*','NG Simpl*'},[FlowMonth]={"$(vCurrentAcctMo)"},[RiskType]={'Cash'} >} [ProfitLoss])

    +sum({$<[RiskType]={'Settled'} >} [GDDiffAmount])

    +sum({$<[DealType]={'NG Ph*','NG Simpl*'},[FlowMonth]={"$(vCurrentAcctMo)"}>} [Adjusted ProfitLoss])

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  • Resident load taking too long

    Can someone help me change a resident load to a traditional load from the original QVD files?  This is my resident load script.ConcatenateEOM:LOA... Show More

    Can someone help me change a resident load to a traditional load from the original QVD files?  This is my resident load script.

    Concatenate

    EOM:

    LOAD

              Date(CurveDate,'MM/DD/YYYY') as 'CurveDate',

         Num(ProfitLoss,'$#,##0.00;($#,##0.00)') as 'PnL',

         Date(Monthend(RangeBegDate), 'MM/DD/YYYY') as 'LastDayofMonth',

         Source,

         DealType,

         ProfitCenter,

         Portfolio,

         RiskType

    resident PnL

    where

    Date#(MonthEnd(CurveDate), 'MM/DD/YYYY') =Date#(CurveDate,'MM/DD/YYYY')

    and

    Date#(MonthEnd(CurveDate), 'MM/DD/YYYY')=Date#(Monthend(RangeBegDate), 'MM/DD/YYYY')

    I'm trying to create a end of month total.  When i changed the source of data from resident to qvd I got nothing???

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  • Qlikview and Fund management

    HelloI'm using Qlikview in order to create an app that allows to pilot Dashboard in Asset Management...I have create a POC to manage an Middle Office ... Show More

    Hello

    I'm using Qlikview in order to create an app that allows to pilot Dashboard in Asset Management...

    I have create a POC to manage an Middle Office activit with reconcilition, check between NAV-1 and NAV of the day, cash margin call ect...

    Someone use it in the same area ?

    best regards

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  • NPrinting in Financial Services

    I've seen a lot of interesting activity going on with Financial Services companies leveraging NPrinting, for example:A leading bank used NPrinting to ... Show More

    I've seen a lot of interesting activity going on with Financial Services companies leveraging NPrinting, for example:

    • A leading bank used NPrinting to cut 400 hours per week from generating customized PowerPoint briefs.
    • One insurance company used NPrinting to eliminate business objects for reporting saving over $100k/year.
    • Another bank sends emails whenever G10 rate changes will impact their risk portfolio making their business operation more secure and less likely to show up on the front page of the journal.

    Qlik will be hosting a webex on Wed Dec 2 10ET, and Thurs Dec 3 1ET. Register contact:

    Adam Rizzo
    Direct: +1 610-994-5845
    Email:  Adam.Rizzo@qlik.com


    This community page contains a video describing how NPrinting is used in Financial Services - and builds a NPrinting report from scratch.

    Video Link : 3678


    QlikView NPrinting- Overview for Financial Services - YouTube

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  • Big Data approach presented by IPC Global

    We held and event with IPC Global (Qlik Global Partner of the Year) who has proven Qlik success in the US Banking industry.  This is Customer Exp... Show More

    We held and event with IPC Global (Qlik Global Partner of the Year) who has proven Qlik success in the US Banking industry.  This is Customer Experience, Profitability, Big Data and Internet of Things addressed with Hadoop, AWS and Qlik.

     

    - 44B records

    - 22 million games played

    - 3.3 million customers

     

    The analogy to banking and banking profits can be drawn with MANY lines.

     

    Please excuse the quality as this was recorded on my Iphone (but too good not to share):

     

    https://youtu.be/yvW0l97NXXg

     

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Group details
Qlik FinServ
Qlik FinServ
408 members Open Group Since ‎2013-02-15 03:39 PM
A private group designed to enable innovation, share best practices and educate QlikView users in the Financial Services industry. You will not see any content if you are not a member, you can request to join by pressing "Join the Group"
A private group designed to enable innovation, share best practices and educate QlikView users in the Financial Services industry. You will not see any content if you are not a member, you can request to join by pressing "Join the Group"
Group Admin
PVS Employee
Members (408)