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Personal Finance Digital Assistant - PFDA


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PFDA is a smart assistant as service into your digital bank account that will make your personal finances, budgeting and savings fun again, without any effort from users.
Mob: +4794875183

Published in: Data & Analytics

Personal Finance Digital Assistant - PFDA

  1. 1. Personal Finance Intelligence Another approach to Personal Finance Applications by BeyondIT AS
  2. 2. Some facts about Personal Finance This is US facts based on surveys, numbers Globally are even worst: • Just 32 percent of Americans keep a household budget and 10 percent Globally.[1] • 30 percent of Americans prepare a long-term financial plan such as savings and investment goals, while 7.5 percent Globally. [1] • Persons most likely to create future financial plans are those with at least some college education and those making $75,000 a year. [1] • Americans spend 12-18 percent more when they use credit cards instead of cash, nearly same Globally. [2] • 76 percent of Americans live paycheck to paycheck, up to 80% Globally. [3] • Half of the American population has less than one month’s income saved for emergencies. (It is recommended that a family of four have at least $5,887 saved up or three times their monthly income at the poverty level). [4] • 44 percent of US households are “liquid asset poor”. Meaning they have less than three months of savings. [4] Source: • [1] • [2] • [3] • [4]
  3. 3. Existing Personal Finance solutions • Existing solutions (software, apps etc..) are manually handled • Manual input for every transaction you commit • Manual planning and budget • No Forecasting options
  4. 4. Reason why existing PF software does not help? 0 1 2 3 4 5 6 7 8 9 Usage of Software Household engagement Budget Planning Benefits from Software Good Neutral Bad
  5. 5. PFDA breakthrough: Our solution PFDA vs Standard PF software Opinion on main features Standard PF vs PFDA • Automated Data Update-right from your bank transactions • Automated Budgeting- based on predefined datasets of your segmentation (ex: calculate the average of the segmentations you belong and sets that as budget) • Automated Forecasting: based on Predictive analytics models and ML algorithms Service Category Standard PF PFDA Data Input 5% 95% Budget 12% 88% Forecastin g 10% 90%
  6. 6. PFI: From Idea to the Final Product Idea/Planning Technical and Human Resources Solution Architecture Testing/QA and Implementation
  7. 7. PFDA: The Idea in a nutshell Personal Finance Digital Assistant -PFDA represents the tech solution for personal finance and budget planning embed into your digital bank account or as an application for both desktop and mobile users, life fed directly from your bank account(s). All you need is install your app, authenticate with your bank account and everything will integrate simultaneously. Further, you do not need to maintain your data input manually as data generated from your transactions will populate the app back-end service and you will be able to see in the application in real-time. The application will feature benchmarking against a pre-defined data set that is usually the data set which you belong (ex: average family with 3 children, with 60.000-80.000$ yearly income, from a selected region, etc..) to help you have clear picture of your economy against the population you match most. Machine learning algorithms will make the application act better by learning it from huge data sets coming from other customers that will be willing to share their transactions anonymously Based on the capabilities we mentioned, the application will be able to serve you fully automated personal finance assistance.
  8. 8. PFI: Planning and Design Technical solution and back-end development
  9. 9. Technical/human Resources to accomplish the project Back End Technical Resources: Business Intelligence Servers for back-end/front-end solution, Load Balancer, Applications Servers Human Resources: BI Devlopers, Data Scientists. UX Designers and App Developers
  10. 10. Solution Architecture Back End: gathering data (ETL example) Front End: user interface (dashboard example) *Both designs are subject of changes based on the request and conditions. *Note that dashboards in the front-end are only if we want to analylize our finances, otherwise the goal of the project is to create a digital advisor that will alert you regarding your finances.
  11. 11. Back-End: Extracted bank transactions Here are example of data generated from my bank account via ETL tool like SSIS, from csv to a table and from there starts the magic. 
  12. 12. Staging of the data • Data get stagged from data capture tables • MetaData and Data quality transformations • Defined mapping for the DataMart (small DW) • Defined etntities: Stagging for Dimensions, Staging for Facts etc.. • Aggregations, disctincts, counters and other neccessary transformations
  13. 13. DW or Data Mart • Define DW architecture: Kimball vs Inmon • Define Dimensions and Facts • Define Mapping • Defined data quality process: CheckSum, Attributes etc.. • Consider Big Data and other external data
  14. 14. OLAP solution on top of DW/DataMart 1. Better query performance 2. Well established back-end service 3. Set measures and important KPI’s 4. Set flaging regarding benchmarking budget values
  15. 15. Front-End interface 1. Note: the main purpose of the project is having automated alert system embed in your bank account 2. The extended GUI is just to get better picture of your finances 3. You can do extended analytics yourself because its user friendly
  16. 16. QA and Beta Testing 1. Functional Testing 2. Security Testing 3. Exception Testing 4. Design/UX Testing
  17. 17. CONTACT US Contact: Email:, Mob: +4794875183 Web: Twitter: @beskotw , use: #DataForGood #PDFDA Support the idea on Kickstarter: finance-digital-assistant Support us on Crowdfunder:
  18. 18. The man behind the Idea Besim Ismaili, Data Scientist "A decade of experience in the field of Information Technology, where 6 years of experience in Business Intelligence, Data Analysis and Design, Data Warehousing, Data Modeling, Mathematical Modeling, Statistics and lately Data Science. • Expertise in Data Modeling, Data Analytics and Predictive Analytics SSAS, MDX and DMX • Experience in development of Data warehouse, Data Extraction, Transformation, and Loading ETL • Excellent record of accomplishment in developing and maintaining enterprise wide web based report systems and portals in Finance, Enterprise wide solutions of BI&Strategy applications • Two times finalist of DND (“Den Norske Dataforeningen”) best solution in Business Intelligence • Certified from the best Universities in the World including MIT, Harvard University, Stanford University, UC at Berkeley in relevant fields"' Contact: Email:, Mob: +4794875183 Web: