Automating marketing processes for a financial services organization

Automating  marketing processes for a financial services organization


Many organizations from finance sector that provide services such as lending and credit cards have a complex process architecture that has evolved over decades. Traditionally, these organizations need to deploy several resources to undertake repetitive and mundane tasks, often using old technologies. This approach has introduced high levels of manual handoffs, bottlenecks, and data inaccuracies. Also, it has resulted in lower productivity, profitability, and overall growth.

Customer Background Customer Background

  • The customer is a US based financial services firm providing loans for small to medium-sized businesses.
  • The customer is focused on providing fast access to funding for expansion, working capital, inventory, payroll, marketing & equipment.
  • They have channel partners in all the fifty states of the US. Loans are administered and serviced by customer’s channel partners who have the authority to determine loan eligibility.

Requirement Requirement

  • The customer wanted to have an automation solution for a part of its lending process, that can allow its decision makers to make fast decisions related to approve / decline loans or ask for additional information, based on the information available in the emails received from partners.
  • They wanted to track opportunity pipeline for loan requirements in near-real time manner.
  • The data and information needed for decision making is scattered across disparate business emails received from the lending channel partners.
  • Since the current process was manual, it was prone to errors and time consuming as well as generating reports was difficult. They wanted to have a simplified solution to overcome all these issues.

Scope Scope

  • Designing and implementing a solution to automate loan submissions process.
  • This entails scraping the data from the emails received from partners and searching for various data elements like highest approval amount, highest term and longest buy rates, within the email body.
  • Updating the status of a loan request in Salesforce CRM as ‘ Accepted’, ‘Declined’ or ‘ Additional Information needed’. Also, all email information needs to be included in the respective Opportunities in Salesforce CRM.
  • Optimize the run time frequency of the automation bot/ Python script so that the data on Salesforce side is refreshed in near real-time mode.
  • Test and deploy the automation bot/ Python script on Google Cloud Platform.

Solution Solution

  • Aress assigned a team of developers to work on designing and deploying a scalable automation bot that runs every 10 seconds and performs following tasks:
    • Log into the business email server
    • Read content from emails received.
    • Extract fields relevant to the lending opportunity (these fields could be part of the email or may need to be extracted from a link embedded within the email)
    • Log into Salesforce CRM and populate these fields in the relevant opportunity along with related attachments.
  • The automation approach needed to be implemented for an initial set of 36 lenders and the design needed to be scalable to accommodate newer lenders.

Business Benefits Business Benefits

  • Making better lending decisions - the automation solution provided data and information to improve sales productivity and efficiency/ accuracy of lending decisions.
  • A scalable marketing automation solution - Aress developed and deployed an automation solution to meet all the necessary information capture requirements, provided by the decision makers. The solution is developed considering scalability needs in the future.
  • Cost advantage - The cost of development and deployment of the automation solution was fractional, as compared to an equivalent solution implemented using industry standard automation products like UiPath, Blue Prism or Automation Anywhere.

Marketing automation helps in increasing sales productivity and in reducing overall marketing overheads.