Schwab Hackathon for UT Austin Students

Are you ready to unleash your creativity and learn something new while innovating with others? How about a chance of winning prize money in a fun high energy team environment?

Schwab invites you to our Austin campus for a 24 hour hackathon starting at 3pm on January 25, 2019. We call it a Schw-ackathon... Game on!

 

Agenda

Day 1
January 25, 2019 
2:30pm - 3:00pm       Student Registration
3:00pm - 4:00pm Schwab Technology Services & Student Mixer
4:00pm - 4:15pm Welcome to Schwab
4:15pm - 5:00pm Schwab Panel, "Why is Schwab winning and what role can you play?"
5:00pm - 5:45pm Overview of Project Use Cases and Q&A
5:45pm - 6:00pm Review Team Assignments & Mentors
6:00pm - 7:00pm Dinner and Azure Workshop presented by Microsoft
7:00pm - 9:00pm Hacking begins!

9:00pm - 9:30pm 

9:30pm - 10:00pm

10:00 -

Machine Learning Workshop

Design Thinking & Journey Mapping Workshop

Hacking continues through the night

Day 2
 January 26, 2019
7:00am - 9:00am Rise & Shine with Schwab over Coffee & Breakfast Snacks
9:00am - 11:00am It's Crunch Time! Final Project Submission on DevPost, Hacking Ends!
11:00am-1:00pm          Brunch & Judging Begins
1:00pm - 2:00pm Award Ceremony and Winners present their project

Global Data Technology Use Case

Smart Contracts with Ethereum PoA
Prerequisites
Problem Statement

Data access at Schwab encompasses Authentication, Authorization, and Identity Management. Today, a central system controls how data access is issued, reviewed, and removed in a timely manner. This system is susceptible to common forms of cyber threats, and common availability constraints. Creating a new data access management system that is served by a distributed ledger will make these records of authority impervious to forgery, and extremely resilient to downtime.

Deliverable

Create an Ethereum distributed application (DAPP) that is a data access management system. The application should behave such that the users of the system are able to perform their data activities, such as requesting and approving data access, using a familiar web-based interface and process workflow.

Smart Contracts Use Case Deliverable

Datasets

N/A

Resources
  • Student must provide their own computer to develop on. Windows, Mac, or Linux will be supported. Modern hardware (within the last 5 years) is recommended.
  • Newcomers may follow these introductory guides about blockchain, Ethereum, and DAPPs (1, 2, 3).
  • Example sequence diagrams, use cases diagrams, and entity relationship diagrams that describe a basic data access management system will be provided to help students orient and ideate!

Key Use Case Assumptions
  • Assignment of identities (Ethereum addresses) will be handled outside of this application.
  • Students should use a local testnet. Creating the blockchain infrastructure is not required.

Advisor Services Technology Use Case

Keeping it in the family - Identifying and keeping At Risk Clients
Prerequisites
  • Understanding of AI based predictive models and Natural language processing
  • Experience working with big data sets
  • Marketing & Customer Engagement
  • Customer Relationship Management
Problem Statement

Advisors lead their client’s investment strategy as a trusted partner - building strong, lasting relationships. There are nevertheless times when internal and external influencers can put the relationship at risk. Planned generational wealth transfer, private investment opportunities, or the passing of a client are just a few examples. How can advisors identify an at-risk relationship early to begin re-building that trust and loyalty before it’s too late?

Deliverable
  • Provide risk exposure index for every client and identify the vectors for managing the risk
    • Build additional channels for information that can be feed into the system to identify clients more accurately
  • Build a marketing campaign and customer engagement process that can be targeted to each risk group
    • Identify how customer relationships can be maintained and monitored
Datasets
  • Provide a subset of Advisor services data for multiple clients
    • History of accounts and portfolio
    • Securities and their performance
    • Transaction history of all the trades
    • Activity related to contributions and withdrawals
  • Provide Client Account Information
    • Age
    • Address
    • Account history - When they joined, left, came back to Schwab
    • Additional details known about clients
      • Industry they work in
      • Company Name
  • Spouse or other owners of Account
Resources
  • Technology
    • Analyze client’s portfolio performance, historical performance against industry standards
    • Compare other financial transaction that client might be doing outside of him portfolio investment
    • Build an engine that analyzes these datasets to provide risk ranking and potential risk vectors, estimated portfolio target for the future ex: 90% chance of meeting client’s goals
    • Engine should be capable of building prospective client profile
  • Marketing & Business
    • Build a client questionnaire to determines client’s investment goals
    • Develop a marketing campaign
    • Targets different Risk groups ( Age, Marital Status, Job Industry, etc... )
Sample datasets
  1. https://www.kaggle.com/finintelligence/nasdaq-financial-fundamentals
  2. https://www.kaggle.com/c/two-sigma-financial-modeling/data
  3. https://www.quandl.com/search?query=500%20one%20minute%20bars
  4. https://toolbox.google.com/datasetsearch
  5. Price Data for Portfolio Analysis https://www.kaggle.com/pap1996/price-data-for-portfolio-analysis
  6. US Household Income Statistics +32,000 records, with granularity on a neighborhood scale (mean, median, Stdev) https://www.kaggle.com/goldenoakresearch/us-household-income-stats-geo-locations
  7. Sharadar Core US Equities Bundle https://www.quandl.com/databases/SFA
Key Use Case Assumptions
  • Experience with Python, Panda, Numpy or similar libraries

Schwab R&D Use Case

Hey, don't I know you? Moving beyond the password in authentication.
Prerequisites

Web or app development experience, basic knowledge of authentication, web APIs and databases.

Problem Statement

Passwords suck. We forget them, reset them endlessly, they get phished, stolen, reused. There must be a better way!

Deliverable

An application or website that allows users to access their personalized content via passwordless authentication.

Datasets

A simple spreadsheet with examples of user account data.

Resources

You can bring your own development machine (BYOD), or contact us if you need one set up.

Key Use Case Assumptions

Once authenticated, all the app needs to display to the authenticated user is their name and account balance. Anything extra is just gravy.

View full rules

Eligibility

The Contest is open only to full-time students currently enrolled as undergraduate, graduate, or professional students in the McCombs School of Business, the College of Natural Sciences or Cockrell School of Engineering at the University of Texas.  All students must be at least eighteen (18) years old as of January 25, 2019, and will be required to show identification confirming their student status at the University of Texas as part of the application/registration process.

Requirements

Each team will need to select one of the three Contest Categories below in which your Team would like to compete.   The Contest Categories are:

  1. Smart Contracts on Ethereum PoA.  Teams in this category will be asked to create an Ethereum distributed application (DAPP) that is a data access management system.  The Application should behave such that the users of the system are able to perform their data activities, such as requesting and approving data access, using a familiar web-based interface and process workflow.
  2. “Hey, Don’t I Know You?” – Moving Beyond the Password in Authentication.  Teams in this category will be asked to create an Application or website that allows users to access their personalized content via password-less authentication.
  3. Keeping It in the Family with AI – Identifying and Keeping At-Risk Clients.  Teams in this category will be asked to create a risk exposure index for clients and identify the vectors for managing the risk.  The Application should provide additional channels for information to be entered into the system to identify clients more accurately.  Teams will also be asked to develop a marketing campaign and customer engagement process that can be targeted to each risk group and to propose how customer relationships can be maintained and monitored.

How to enter

Eligible students on the pre-registration/rsvp list must be physically present at the In-Person (Official) Registration Desk at Charles Schwab, 2309 Gracy Farms Lane, Austin, TX 78758 between 2:30 pm -3:00 pm on the day of the Contest – Friday, January 25, 2019.  Each entrant must be physically present at the Event Site during this time period to complete the entry form at the registration desk and to show proper student identification.  Entrants will be asked to provide the following information: first and last name, UT student identification number, phone, email, degree program, and team name (if known).

Judges

Freddy Marichal

Freddy Marichal
Schwab Global Data Technology

Mark Greene

Mark Greene
Schwab Global Data Technology

Jay Bodduna

Jay Bodduna
Schwab Advisor Services Technology

Anuj Rohatgi

Anuj Rohatgi
Schwab Advisor Services Technology

Colin McGraw

Colin McGraw
Schwab Technology R&D

No avatar 100

Mitch Patel
Microsoft

No avatar 100

Jatin Grover
Microsoft Azure Architect

No avatar 100

Shimail Gillani
Microsoft Data AI Specialist

Judging Criteria

  • Innovative Solution
    25 points
  • Technical Proficiency
    25 points
  • User Experience and User Interface
    25 points
  • Presentation and Live Demontration
    25 points