Morningstar Equity Helper

Users of Morningstar.com like to have up-to-date information on their stored portfolios, as well as manage their portfolios in a more friendly way.

What it does : Portfolio At A Glance

Morningstar.com is an investment research resource with both a free and a paid tier. It allows users to store a portfolio of their holdings, and look up both publicly available data and our Morningstar premium data for that holding. For instance, if Morningstar recommends buying or selling a stock at the current price, a user can see that information through a slack bot without having to pull up morningstar.com and navigate through. This bot was developed with a specific user persona in mind. Morningstar.com has many users who like to actively manage their equity investments for at least a portion of their overall holdings, and appreciate having ready access to up-to-date information for those holdings. We think that creating a frictionless version of this transaction will lead to a better experience for these customers, and increase user engagement with Morningstar.com.

How we built it

We spoke extensively with our product people to come up with a way to add value to .com. We connected a lex bot based on the ScheduleAppointment bot to our existing internal APIs, and used response cards to guide the conversation. We then published the bot on a slack channel.

Challenges we ran into

Account Linking Linking the accounts and portfolios of existing users proved to be a major challenge. We have several APIs that can accomplish this, but none that were ideal. In the end, we used SSM Automation to store the credentials for a sample user, which we can then leverage to authenticate to the API. This POC is working for our sample user.

Demonstrating the full capabilities of our bot We wanted to ensure that we could provide a complete enough service that users didn't need to default to going to morningstar.com to complete every simple task, but not so much that the bot loses focus and becomes convoluted and confusing. To do this, we focused on a somewhat narrow use case (at least initially), and also made liberal use of response cards to demonstrate possible selections.

Accomplishments that we're proud of :

We're proud to provide a more seamless service to our users.

What we learned

We learned about how to integrate different AWS products, how to identify a solid use case for a chatbot, more about our internal APIs, and how to work with Amazon lex (of course).

What's next for Morningstar Equity Helper

We would like to include stored user preferences in our bot, and leverage those to implement a version of IFTTT. For instance, if a stock that a user has been looking at drops to a 5-star price (Morningstar speak for a favorable price to fair-value ratio), we would want to alert the user that this is a good time to buy. Conversely, if a stock in the user's portfolio becomes overvalued, we would also want to send an alert, and allow the user to pull up some data through the bot.