Smart Vision

Inspiration

 Having to deal with sight loss or low vision is merely one of the challenges that the visually challenged\Impaired are facing when living life.  There are many problems faced by people with disabilities when they consider banking and financial services.  Like finding bank branches to check some loan offers, visiting ATM\login Mobile or Internet banking for account information and even telephone banking will make people to wait in Queue for their chance and some person should be there to assist.  Most of the above options are not easily accessible for the visually challenged.  These obstacles mean that a person with disability always has to latch on to someone who is fully capable to help them. Without such help in the form of guarantors or co-borrowers who are fully capable, the chances of obtaining benefits from the banks are low.  Moreover, not allowing a visually impaired individual to perform a task by themselves, does not give them the room to learn how to do so independently.  So, to support the world to overcome this challenge, We Integrated PEGA with Alexa and built a “Smart Vision” application.  Using this application VC people can perform banking services independently by using their voice as medium of communication whenever required.

What it does

 We have used PEGA to build “Smart Vision” application and integrated with ALEXA to support Visually Challenged\Impaired people in banking services.  VC people can use their voice to connect with Alexa and they can check for eligible offers, account information and they can schedule meeting with customer relationship manager.  When customer needs banking help , can ask alexa help or smart vision to connect CBank smart vision pega application .  Then Alexa will ask for customer id for authentication and ID will be passed to pega for validation.  If customer ID is valid then Alexa welcomes user and give list of banking services.  Customer can choose the list of banking services and can get benefits.

How we built it

 Created Smart Vision pega implementation application and added required authors.  Added recent Pega Alexa component application, rule set from pega market place to application stack.  Updated Alexa service package access group to application access group.  From Pega configured channels and interface for Alexa and updated Skill ID from Alexa dev console.  Added Pega endpoint urls in Alexa dev console for proper communication.  Using Alexa dev console, we have created skills, intents and slots to invoke Smart Vision pega application from Alexa.  Created Smart Support case type for CBank organization from app studio. The stages are:  Initiate – process is to authenticate customer,  Verify offers – process will return eligible next best offers using decision strategy and data flows.  Account Information – Helps customer with account details like credit score, balance, child account creation.  Contact Customer Relationship Manager – Used OOTB tasks process to create task.  Created customer data types, Security questions data type to support basic authentication.  Added when rules based on the customer preference from Alexa dev console and moving to different stage back and forth.

Challenges we ran into

 Faced authentication issue between pega and Alexa. So, we have updated Alexa authentication utility from OOTB Pega Alexa component.  Unable to use built in Yes or No, dropdown options from conversational flow.  OOTB Pega Alexa component rule set impacted our application guardrail compliance score. Pega can enhance the OOTB Alexa component by addressing severe and moderate warnings. Few activities can be converted to data transforms. We tried to verify actual guardrail compliance score by removing Alexa rule set from application rule set stack and the score is 97%.  The solution or the problem statement is too vast to be covered as part of this project and can spawn out big project.

Accomplishments that we're proud of

With awesome pega capability, we are able to create smart vision microjourney application and easily extend any Pega enterprise application to have a conversational user experience through Amazon Alexa.

What we learned

 We learned about how pega and Alexa integration, communication happens.
 Utilized and learnt some conversational flows, shapes than usual process flows.  Used Pega low code platform and its capability very well.