Giving Credit

Every year people in the United States lend $89B to family, friends, neighbors, and coworkers. Half of these loans are used for basic necessities like paying utilities, bills, and rent. Peer loans are especially vital in low-income communities of color. With large racial disparities in wealth and limited access to low-cost, mainstream banking services, there are around 4.5 million unbanked and 10.8 million underbanked Black and Latinx households that are soft targets for high-cost, exploitative loans. Communities of color are saturated with payday lenders and other high-cost alternative financial services that offer loans at exploitative interest rates. Payday loans extract $9.1 billion from low-income families in the United States annually.

Faced with financial exclusion, people living with low-income create their own financial justice, benefiting greatly when their local ingenuity is harnessed through innovation. Community-lenders, often low-to-moderate income themselves, make unsecured loans to kin and friends at risk to their personal financial well-being. This risk is especially acute for Black and Latinx households who tend to have materially poorer networks than Whites. About 10% of the Black-White racial wealth gap is attributable to Blacks providing financial assistance to lower-income members of their social networks. People should not have to choose between caring for their communities and securing their financial futures.

What if informal banking practices had the same data transparency as mainstream credit and banking services? What if there are people in communities willing and able to lend at no-interest but they are invisible, and their capacity and willingness are unknown to others in their social circles? What if the transparency created through an informal banking platform allowed peer-lenders to better manage requests they inevitably receive from kin and friends? And what if peer-loan repayments were reported to credit bureaus? If these problems could be addressed, the need for predatory services would decline and financial well-being would increase.

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Giving Credit is a web-based social credit network that amplifies community finance by bringing transparency to informal lending networks, protecting peer-lenders against loan loss through loan guarantees, reporting informal loan repayment to credit bureaus, and enabling lenders to deduct loan-loss from income taxes.

1. Social credit line transparency - A central component of formal credit markets is that borrowers know how much credit they have available at any time. Knowing how much credit a potential borrower has available provides a psychological sense of financial security, even when one is not borrowing. The platform reveals people’s social credit lines by enabling them to report how much they would be willing to lend others if they needed a loan. The increased visibility into social credit lowers the cognitive bandwidth tax of financial scarcity and decreases reliance on predatory loans.

2. Loan guarantees - The platform enables organizations to extend loan guarantees to their constituents engaged in peer-lending. The loan guarantees protect the assets of lenders by insuring them against loan loss while further capitalizing informal banking networks.

3. Mainstream credit reporting - People in informal networks demonstrate their credit worthiness through peer-to-peer loan repayment. However, these repayments are not recognized by mainstream finance. We are working toward reporting peer-to-peer loan repayments to community banks and credit bureaus, creating mainstream credit opportunities for the 45M credit invisible households in the country.

4. Write-off loan default on Federal income taxes - When lenders experience a loan default, the application provides a pre-filled tax-filing document for US lenders that lenders can use to deduct the loss from their income taxes.

Peer-lenders and borrowers join the platform through institutional partnerships with nonprofits and community development financial institutions. Partner organizations extend loan guarantees to their constituents. For example, an organization might establish a $100K loan-guarantee pool, extending $500 dollars in loan-guarantees to 200 peer-lenders. We currently have loan-guarantee partnerships with nonprofits in Pittsburgh, Pennsylvania and Menelas, Haiti.

As organizations extend loan-guarantees to constituents, peer-lenders give credit to people in their networks, who in turn give credit to others, growing the social credit network.

Giving Credit is designed to meet the small-dollar credit needs of financially excluded communities. In the United States, where Giving Credit is located, low-income communities of color face the highest degree of financial exclusion and exploitation. In the 1980s as income inequality rose, mainstream banks increased their focus on middle-income and higher-income depositors, shutting the depository accounts of people increasingly deemed too poor to bank. As mainstream financial exclusion accelerated, alternative financial services like payday lenders and pawn shops literally moved in. Specifically, they moved into low-income communities of color, leading to vast levels of racialized financial exploitation that persists today.

Black and Latinx households are twice as likely to be unbanked than White households. Blacks pay twice what Whites pay in loan interest and bank fees every year. Latinx borrowers pay 1.4 times more. Faced with financial exclusion, communities engage in informal finance to meet their financial needs. 25.6M people, or 10% of adults in the United States borrowed from their networks in 2021, including 17% of Black and 15% of Hispanic households.

I know this problem intimately well. My mother, an immigrant from Panama, borrows informally from her network (and me!). I have undocumented family members here in the United States who are excluded from mainstream finance, instead relying on informal social credit networks to meet their financial needs. Giving Credit brings transparency to these social credit networks, capitalization, and mainstream recognition. The current frame of financial inclusion efforts do not meet people where they are, and fail to recognize the ingenuity of community-led financial efforts.

Indeed, even people who are served by the mainstream financial system engage in informal community finance. This is especially true for people living with low-incomes. While having a credit card at middle and high-incomes reduces reliance on peer borrowing, having a credit card does not reduce peer-borrowing for lower-income households. And with good reason. Borrowing from one’s social networks often comes at zero-interest with flexible repayment terms.

I have interviewed dozens of people about their informal lending. I have spoken to people who have avoided eviction and started small businesses with these loans. Unlike loans from mainstream or alternative financial institutions, informal loans are from people who care about you, who care about the impact of the loan, not just repayment. People in communities are not only creating their own financial justice, they are generating tremendous social value, all with their capital. That initiative should be recognized and further capitalized. Giving Credit is the financial technology solution for informal community finance. It is not designed to replace mainstream finance or good financial products. Instead, the aim is to eradicate predatory alternative financial services and provide an on-ramp to wealth building mainstream financial services.

Access to credit is central to human dignity. Princeton professor Frederick Wherry defines “financial citizenship” as having access to the resources you need to do the things you want. I have family members who are undocumented, lacking both country and financial citizenship. My mother immigrated to the United States from Panama in her 20’s. Growing up, I observed her frequently remit money to family back home. She borrowed informally from her network to afford the downpayment to purchase the house she raised me and my brother in. Years later, I saw how the financial system exploited her, leaving her in financial ruin.

Like my Panamanian mother, my undocumented family members bank on each other, and me, creating our own financial citizenship. While predatory finance extracts wealth, community finance is financially regenerative mutual aid. I do this work to recognize and capitalize communities like mine.

I have spent my career working in nonprofit organizations at the intersections of poverty and technology. I was previously the Chief Technology Officer of the national nonprofit UpTogether. At UpTogether I led a team that distributed over $200M in unconditional cash transfers to hundreds of thousands of people living with low-incomes across the United States. At UpTogether I saw how people would lend cash they received to others. I learned to think of cash transfers as capital infusions into hidden banking networks.

Seeing the impact of informal lending in my personal life and again at UpTogether, I started researching informal peer-lending as a fellow at Princeton University. I did not start with books or academic articles, I started with people. I spent months interviewing people living with low-incomes from different parts of the United States. I spoke with a variety of people, from Latin American immigrants in Los Angeles to Black women in Pittsburgh. In my conversations I heard how vital peer-lending is. What I didn’t expect was just how frequent and bi-direcitonal lending tends is, especially in low-income social credit networks.

I expected that people would first get into trouble with a payday lender and then reluctantly turn to their networks for a loan. I found the opposite. People vastly prefer to borrow from their social networks. It’s only when they have tapped out their network (or think they have) that they reluctantly turn to the payday lenders. This insight is foundational to Giving Credit, and directly contradicts the prominent thesis of financial literacy efforts that assume people are too dumb to realize 600% APR loans are a bad deal. Everyone knows that!

Giving Credit is a behaviorally informed solution. The application and approach is based on how people actually behave, designed for what people actually do and how they think. I am building Giving Credit for me, for my mother, for my late wife's family who immigrated to the United States from Mexico. Impactful solutions originate in impacted communities. Too many "solutions" attempt to change people's behavior. Giving Credit amplifies the solutions communities innovate for themselves. Giving Credit exists because everyone deserves financial citizenship.

We currently have 50 people using the application in a staging (testing) environment and a handful of people in the production environment. We are soon to launch a pilot in partnership with three nonprofit organizations that will extend loan guarantees ranging from $250 to $500 to about 80 peer-lenders. Those lenders will seed the social credit network, inviting others onto the platform.

I have deep subject matter expertise in the field of poverty and financial exclusion. I know how to build a product and have led engineering and analytics teams. I am currently a Practitioner in Residence at Princeton University's Center for Behavioral Science and Public policy and a Visiting Fellow at the Federal Reserve Bank of Boston authoring a paper on informal peer-to-peer household debt.

I have no idea how to build a viable business. I am applying to Solve because I know what I’m good at, and more importantly, I know where I need help.

I have not yet incorporated Giving Credit because I am undecided on what the best legal structure is. This is one of many points I could use the MIT Solve community’s guidance on. I am exploring nonprofit, for-profit, and hybrid models. My sole objective is to attract the capital needed to scale Giving Credit to the magnitude of the problem (and opportunity). I don’t yet feel like I know for sure what model best gets the organization where I believe it can go.

I also need guidance on how to test possible business models. One idea is to ethically monetize the social credit network and informal loan repayment data. I have spoken to the CEO of a major credit scoring company that was receptive to the idea and is already incorporating alternative signals in their credit scoring models. However, I don’t know how big this opportunity is, nor do I have the expertise to fully comprehend what type of staffing and financing would be required to reach a scale where such a model might be viable.

Another avenue is to explore monetization opportunities directly with Giving Credit users, such as charging for credit reporting services, tipping models, referrals to values aligned Credit Unions, etc. Again I am out of my depth when it comes to validating these types of opportunities.

I believe there are significant partnership opportunities with Credit Unions and other financial institutions. I plan to tap into the Solve mind-hive to help ideate what potential partnerships might look like and then leverage the Solve network to pilot those partnerships. For example, I am in the early stages of exploring a partnership with a group of Latinx serving credit unions to position Giving Credit as the small-dollar lending solution for their members. Additionally, I am exploring an integration with a neobank serving undocumented people in the United States.

The more people I talk to about Giving Credit, the bigger the opportunity and possibilities seem. Those opportunities and possibilities cannot be achieved on my own. I need your help!

Giving Credit is not innovative. Communities are innovative. Giving Credit provides a modern financial technology platform, capitalization, and mainstream recognition to support community solutions.

The best solutions are the ones created in communities. Where mainstream finance has failed people living with low incomes, communities have forged their own way. Communities are not the problem, they are the solution. Yet for too long the financial inclusion space has focused on the wrong issue, erroneously assuming people living with low-incomes are financially illiterate.

Social credit networks are intricate, effective financial solutions. For the first time, Giving Credit brings transparency to people in social credit networks, leveraging community capital and social underwriting through third party loan guarantees. These mechanisms work together, increasing access to community capital and reporting activity to credit bureaus, building mainstream credit.

Giving Credit is being incubated at Princeton University’s Kahneman-Treisman Center for Behavioral Science and Public Policy. Giving Credit’s approach is (sadly) unique in that we lean into the financial decision making of people living with low-incomes instead of trying to change it. The affiliation with Kahneman-Treisman gives us access to world-class behavioral scientists like Eldar Shafir, who is an advisor to Giving Credit. 

By better understanding how people make financial decisions and the intricate pro-social informal credit networks people participate in, we believe we can catalyze the financial-inclusion space and mainstream finance more broadly to design financial products that enhance the power of informal finance.

Imagining a line between informal and formal finance is a false dichotomy that ignores the reality of how people think and behave. Giving Credit is not simply an on-ramp to mainstream finance. We envision a world where Giving Credit (and many more informal community financial products like it) sit alongside and deeply integrate with mainstream finance. 

In the near term we are focused on optimizing Giving Credit to meet the needs of our target demographic. This means focusing on the efficacy of the application in mapping social credit networks and capitalizing informal loans through loan guarantees. Specifically, we have set a target for Giving Credit users to extend social credit to at least two other people on average, hitting an 80% or greater loan repayment rate, and developing better datasets on loan repayment to enhance our ability to predict the leverage one-dollar in loan guarantees creates.

We are working toward meeting these short-term objectives by onboarding users through partner organizations that are extending loan guarantees, and deploying a user experience researcher to get regular feedback from Giving Credit users. A benefit of being lean is we can quickly deploy changes to the application and get immediate feedback through transactional data on the platform.

Over the five-year time horizon we are focused on eradicating the need for high-interest predatory debt. We will measure our progress by collecting data on how users would have met their financial needs in the absence of Giving Credit. Eradicating the need for high-interest loans will have a substantive, transformative impact on the financial lives of people living with low-incomes.

More broadly, we believe that access to financial services is central to well-being and human dignity. We envision a future where people have access to the resources they need, where communities are recognized for the solutions they innovate. Financial citizenship is about more than low-cost credit. True financial citizenship is about agency over one's life, including the opportunity to co-create loan terms.

We envision a future where informal banking practices have the same data transparency as mainstream credit and banking services. Where people access loans from lenders who prioritize impact over interest. In this future state, informal loan repayment is recognized by mainstream finance, qualifying informal borrowers for high-quality, low-interest, wealth building mainstream credit products like mortgages and business loans. 

A future where community finance is recognized and supported is a future where the need for predatory services declines and financial well-being increases for everyone.

Giving Credit has been designed from the ground up with an ability to track meaningful social impact indicators. I have deep expertise in the field of impact evaluation, specifically evaluating the efficacy of financial interventions on people living with low-incomes. While CTO of a national nonprofit called UpTogether I helped launch four randomized control trials evaluating the effectiveness of unconditional cash transfers.

Giving Credit tracks specific impact and process metrics. Those metrics are listed below.

Impact metrics

• High-interest debt utilization - We survey our users to understand if, when, and how much high-interest debt they accumulate. We also ask people who take out loans on the platform how they would have met their financial need if they didn't have access to Giving Credit.

• Sense of financial well-being - We periodically survey users to quantify their sense of financial well-being. We use a qualitative measure purposely as a sense of financial-well being is not only a function of material wealth but also the extent to which one feels stress about their financial position. Our hypothesis is that Giving Credit both materially and psychologically affects people’s sense of financial well-being.

Process metrics

• Social-credit extended - Giving Credit is fundamentally a social credit network. In order to add value to users we need to map the network by having users extend credit to others (that is, make clear how much they would lend to others if they need a loan). We track the number and amount of social credit relationships, with a target for each user to extend credit to two other people on average.

• Loan number, amount, and use - We track the number of loans, loan amounts, and loan uses. This is an important process metric to ensure people are using the application to make and repay loans.

Loan default rate - We track the loan default rates, contextualized against loan use (for example, do certain types of loan uses result in higher/lower defaults). We consider loan default a process instead of outcome metric as the platform should be optimizing over social impact. Default is important to meeting our mission, but our mission is not to myopically focus on loan default as we believe this obsession is part of how microfinance lost its way.

Giving Credit’s theory of change is divided into two parts; our impact on individuals and our impact on systems.

Impact on individuals

Giving Credit increases the financial well-being of users and decreases reliance on predatory debt through the following causal pathways.

• Social credit line transparency - People on the Giving Credit platform gain transparency into their social credit networks, allowing them to know how much they can borrow from their networks. Knowing how much one can borrow from their network lowers the cognitive effect of financial scarcity (known as the bandwidth tax). Additionally, people become less likely to borrow from high-interest debt sources given the increased visibility into their social credit network.

• Loan guarantees - Partner nonprofit and credit unions extend loan guarantees to select users on the Giving Credit platform. The loan guarantees improve the financial well-being of borrowers by insuring them against loan loss and increase the availability of credit in social credit networks, decreasing reliance on high-interest debt products.

Additionally, financial well-being is increased as people’s loan repayment data on Giving Credit is reported to credit bureaus, building mainstream credit.

Impact on systems

Giving Credit surfaces data and publishes reports highlighting the effectiveness of informal peer-to-peer lending. We partner with Credit Unions and other mainstream financial institutions to co-create financial products that bridge the gap between informal community finance and formal, mainstream finance. We also advocate for regulatory changes that recognize and value the social outcomes people living with low-incomes create.

While our impact on individuals is important, we know that no one organization can affect change on its own. Instead, we are intentional in publishing research and promoting a narrative that helps mainstream finance and public policy better understand and support the power of informal community finance.

Giving Credit is a mobile-optimized web-application. The web-application is built in Python using the Django framework with a PostgreSQL database. We have some light front-end Javascript using AlpineJS. This summer we will build out our analytics backend infrastructure, including a robust ETL process utilizing DBT for transformations. We will stand up both a business intelligence layer as well as building out the capability to deploy production machine-learning models to handle tasks like default prediction, prioritizing specific social credit networks for loan guarantees, etc.

There are broadly two-ways a technology needs to work; first it needs to do the thing it is supposed to do, second it needs to solve the problem it’s intended to solve. We answer the question in both parts.

We make sure the software does what it’s designed to do through robust unit and integration testing. Before moving code into a production environment we first deploy and test in a staging environment. We use continuous integration to automate our test suite. If a test fails in the staging environment the push is rejected. When we promote code from staging to production the continuous integration system again applies the automated tests and rejects a deployment if any test fails.

The more interesting (and tougher) question is whether Giving Credit solves the problem we intended to solve. The short answer is we don’t know yet, we are currently in the pilot stage. Giving Credit is a behaviorally informed solution and is built on tremendous amounts of domain knowledge, academic research, and lived experience. 

However, it would be dishonest for us to say we empirically know Giving Credit has exactly the impact we intend. We don't know that. But we do know how to find out, and how to interpret the data and adjust the product to get the desired impact.

I have lived experience with this issue as described earlier in this application. One of Giving Credit’s enumerated core values is to be intentionally anti-racist in our work. We know that racial disparities in financial outcomes are the result of historical (and present) corporate and public policies. We center equity in everything we do and are building a diverse team of advisors who keep us accountable to our stated value of equity and inclusion.

Most importantly, we know that the best solutions originate from communities themselves. As such we have frequent and type feedback loops with our target users. In order to best listen to our users, we need a team of consultants, interns, staff, advisors, etc. that resemble the communities in which we operate. We take equity seriously not only because it’s the right thing to do, but because it is critical to our success.

Giving Credit serves both people living with low-incomes and partner organizations that extend loan guarantees to their constituents. Both segments are discussed below.

People living with low-incomes

People join Giving Credit to gain visibility into their social credit networks, track informal loans they give and receive, and to have their loan repayment reported to credit bureaus. The value for these users is reducing reliance on predatory loans by gaining visibility into their social credit networks and building mainstream credit through their informal lending.

For select individuals, an additional benefit is access to loan guarantees provided by partner organizations. The loan guarantees insure their lenders against loan loss.

Partner organizations

Nonprofit organizations and Credit Unions use Giving Credit to extend loan guarantees to their constituents. The value proposition for these organizations is to improve the financial well-being of their constituents by leveraging capital already existing in these communities. Giving Credit surfaces aggregate level insights that partner organizations can use to better understand the intricacy of the social credit networks their constituents are engaged in. The analytics also highlights the social impact of the partner organization’s loan guarantees.

We are exploring different monetization opportunities. Even if we incorporate as a nonprofit organization we will certainly have an earned income component. Below are some revenue models we are exploring:

• Alternative underwriting data - As we build out the social credit network and collect data on informal loan repayment, there might be opportunities to monetize the data if it is predictive of mainstream credit reliability. We have had early conversations with a major US credit scoring company about this possibility.

• Mainstream financial product recommendations - There may be an opportunity to provide recommendations for high-quality mainstream bank products. We have been talking to Credit Unions to better understand what opportunities might exist in this space.

• Tipping - We might provide a mechanism for end-users to fund Giving Credit (or each other) directly. For example, one model might ask loan recipients to provide a tip for their lender after a loan is repaid. We could then give the lender the option of keeping the funds or contributing a portion of the tip back to the Giving Credit community.

This list is not exhaustive but rather illustrative of the type of early thinking we are doing. This is one of many places we could use Solve’s help!

I am an inaugural fellow in the Princeton University's Sugarman Practitioner in Residence program. The fellowship has provided me the time and space to research informal community finance and develop Giving Credit into its current state (started in March 2022 and ends June 2023). I have recently been awarded a $100,000 investment from Unorthodox Philanthropy to pilot Giving Credit and build it into an independent organization.

Additionally, I was awarded a $15,000 fellowship from the Federal Reserve Bank of Boston to author a research paper on approaches to measuring peer-to-peer household indebtedness. The paper is directly tied to my work at Giving Credit and helps further legitimate the problem space Giving Credit is in.