Page 619 - AI for Good Innovate for Impact

AI for Good Innovate for Impact

Use Case- 12: AI to lift people out of poverty

Country: USA (and all countries w/ poverty population) 4.6: Finance

Organization: Era-X Corporation, dba SERA

Contact Person(s):
Primary contact: Phong Nguyen, phong@ getsera .io
Secondary contact: Marlon Monroy, marlon@ getsera .io
Any other contacts: Mohan Navaratna, Mohan@ ninegemsinvestments .com

1 Use Case Summary Table

Item Details

Category Finance
Problem People in poverty often rely on credit cards to survive. But with low income and
Addressed high interest rates, escaping that debt is nearly impossible. Worse, many lack
the tools or knowledge to manage money effectively, making poor financial
health both a root cause and a trap of poverty [1].
Key Aspects of SERA aims to lift people out of poverty with a double -sided solution: 1- Help
Solution pay down CC debt faster without any loan nor extra payment and 2- Enable
people to manage and control their finances to build financial stability. We use
the Offset Principle to speed up CC debt elimination without extra payment
nor good credit, we call it Debt Offset. Furthermore, it uses AI heavily toward
their custom built budget so they can manage/improve their spendings through
these AI measures: Trimming, Budget ReBalancing, Income Boosting, and
Credit Leveraging. Debt Offset solves the immediate CC debt trap, and Smart
Budget solves the root cause of debt/poverty: managing finances.
Technology AI, Agentic AI, LLM.
Keywords
Data Availabil- SERA uses users' private data when they connect their checking account
ity and credit card accounts to us. We extract their expenditure data from these
accounts to create a custom budget for them. Then we use Debt Offset to help
reduce their CC debt faster and Smart Budget measures to help them manage
and improve their spending for future stability. Smart Budget uses public data
for Trimming, Income Boosting, and Credit Leveraging [6]. For example, SERA
uses public yet localized data to recommend using Mint Mobile to reduce their
cell phone bills instead of using Verizon or AT&T. It can recommend ways to
boost their income in case of needs by doing committed gigs (such as driving
for DoorDash or Uber) or uncommitted gigs (such as donating plasma, doing
secret shopper), or getting emergency money help from local agencies or social
services. With localized data training and continuous user-initiated improve-
ment, it can help anyone in any country [6].
Metadata All data is electronic financial information about the users (income, expen-
(Type of Data) ditures, credit score, assets and obligations) and their local public financial
offerings pertaining to their own situation/qualifications.

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