Hack with ZAFIN-tech!

Social Media based Financial Analysis

Objective: To perform social analytics of a Customer’s financial behaviour & categorize into various behavioural buckets.

Description: Extract & analyse financial data from social platforms (Eg: Twitter, Facebook etc.) & categorize the social media exchanges/conversations into various buckets (with a provision to add more buckets dynamically) using specific keywords.

• For Example: “Spending Bucket” to be identified by keywords like 'new', 'bought', 'got', 'paid', 'purchased', 'transferred', 'exchanged'.
• Banks can leverage on the transactions/history through social media, which are not literally captured on the banking end, for example, customer buying goods through "Cash on delivery methods". Customers though talk about their purchase behaviour or experience on social media platform and also categorise it as new buying/exchange etc.
• Social Analytics of a Customer’s financial transaction behaviour from his social media conversations/posts can be utilized for pro-active Customer Profiling (like Segmentation, Credit Profiling, Risk Profiling etc), which can be leveraged during various phases across sales & service.

Technology to be used: Any Technology based on preference of the participant(s).

Data to be used: Participant(s) is/are free to use/create the Financial information and Financial data to be used for this Hackathon topic in their desired format. Participant(s) is/are requested to use new/existing social media profile(s). Financial information to be tapped & Financial data for this analysis can either be existing/newly created in these social media profiles. Importantly, realistic data has to be used in this exercise.

APIs to be used: Suggested to use all/any of these: Twitter API, Facebook Social Plugins API, Google Plus, RShiny API etc. Note: Any other API(s) can also be used.

Desired Output: Any format based on preference of the participant(s).

Campaign/Offer Evaluator

Objective: The intended purpose could be 'New Customers', 'New Accounts', 'Increase net new money', 'Encourage certain types of transactions' etc by evaluating the behavior of the customer.

Description:

• The campaign/offer evaluator provides a means to evaluate if a campaign/offer will achieve the intended purpose
• The evaluator should be able to identify as a whole using real data and/or behavioural data to identify if a campaign will meet its target/purpose
• The evaluator may need to run various scenarios to be able to identify the above
• The evaluator may take inputs to be able to generate data for the various scenarios

For example
A banker wants to create a new offer that would let existing customers bring more money and keep it in the bank. The bank will in turn incentivize the customer by providing a bonus interest rate or a waiver. The banker uses the evaluator to setup the offer and run the evaluation. The evaluator may need some inputs from the banker so that it can evaluate/simulate/extrapolate. The evaluator then provides the results back to the banker which MAY indicate the probability that this offer will be profitable to the bank, and maybe other information that will allow the banker to make tweaks to the offer bonus interest rate to make it profitable.

Technology to be used: Any Technology

Campaign/Offer Suggester

Objective: To suggest offers/campaigns to the customers which should be beneficial to them, and in-lieu could bring revenue to the bank too.

Description: - The campaign/offer suggester provides an analytical means of suggesting offers based on behavioural and trend analysis.

For example
A banker wants to get suggestions on offers to be able to increase relationship of existing customers. The suggester does some analysis and provides a list of possible offers based on the fact that the trend on previous offers (internal and external to the bank) that gives rebates on certain type of transactions for a given period for a given segment of customers.
Internet Banking Usage: Campaign to increase the Internet banking usage based on past data.
Most of the time customer may be using one type of transaction through internet banking (say fund transfer) but there will be other transactions such as mobile bill payment, utility bill payment etc. which will earn more revenue to bank. Internet banking usage can be identified based on the past data. So based on the past internet banking transaction data, bank can identify and come up with new campaigns. To increase the volume of transaction, bank will start new campaigns such as provide cash back or loyalty points to customers based on the 'mobile bill payment' and 'utility bill payment' transaction amount and thereby unknowingly force the customer to use those services. Which in fact increase the revenue of the bank.

Technology to be used: Any Technology

Sample data to be provided: The data could be derived from the bank or can use data derived from other sources across similar banks.

User Metrics

Objective: Collect Metrics on how a user uses an application. This will allow UX designers to design better flows through an application.

Use case: Small Business Loan, P2P Loan, Loan application form, Credit profiling

Description: The metrics that could be collected include the flows that a typical user takes to move through an application, the number of clicks it takes to accomplish a task in the application, the time spent on a given page within the application. These metrics will allow UX designers to build better flows and add the ability to guide typical users through the application.
Design a small prototype app, with screen and buttons and also use a technology to capture the data.

Technology to be used: Any Technology based on preference of the participant(s)

Desired Output: The ability to collect information - on how users use an application.

Please send only your queries regarding problem statements to hack.2017@zafin.com
Subject line should be: Problem statement #: Name of the problem statement.