Blog | Lessons from the field: How we created new group psychometrics to increase financial inclusion in Mexico

While Jonathan takes notes, Gerardo helps an applicant navigate our psychometric assessment on a mobile device. An essential component of our field work was to get direct usability feedback from applicants as they completed new psychometric content.

By Jonathan Winkle, Behavioral Sciences R&D Manager, LenddoEFL

An experimental psychologist by training, I am relatively new to the world of financial technology. Since joining LenddoEFL, I have embraced terms like information asymmetry, alternative data credit scoring, and financial inclusion. Yet it was only during a recent trip to the field that I was able to meet the people behind the FinTech jargon we use in our day-to-day, the small business owners whose lives we help improve in our mission to #include1billion.

In April of this year, I traveled with colleagues to Veracruz, Mexico to test new psychometric content for one of the top 3 microfinance institutions (MFI) in the country. Their group loan product extends a line of credit to a collection of business owners, but liability for payments is joint: if one person misses a payment, the group must still make that payment in full. Since many of those applying for these loans lack traditional credit histories, this MFI asked LenddoEFL to develop psychometric exercises that could quickly and reliably assess group traits that predict creditworthiness.  

There are traits that define a strong social group which are nonexistent for individual borrowers. A successful group has strong internal relationships that ensure they will help each other in times of need. A tenacious group can generate creative ideas to solve problems that arise when life presents hardships, as it is wont to do. And a cohesive group exhibits decision making abilities that allow it to act deliberately and with confidence. We designed new psychometric exercises to measure these core traits, and tested them in the field with groups of small business owners applying for loans.

Hiding from the Veracruz heat underneath a family’s palapa, Gerardo leads a collection of applicants through our group psychometric exercises while Jonathan makes observations about their behavior.

Measuring interpersonal relationships through social pressure
To measure the strength of a group’s interpersonal relationships, we examined the social pressure that exists among group members. Do individuals feel that they can answer sensitive questions honestly? Or do they feel pressure to conform to the opinions of the group majority? While the group was sitting together in one room, we asked them to raise their hands if they agreed with statements about the trustworthiness, fairness, and helpfulness of their local communities. We then asked individuals to answer these questions privately. The discrepancy between how the questions were answered in each setting could reveal how much social pressure exists, and thus how comfortable group members are being honest with each other. We expect that less social conformity means the group’s interpersonal relationships are stronger, an important factor for predicting whether the group will cover individuals who may miss payments throughout the loan cycle.

Measuring creativity through brainstorming
To measure a group’s creativity, we created a set of generative exercises. For both an easy and a hard problem, we had groups brainstorm as many solutions as they could in 60 seconds. The number of solutions generated was recorded as a creativity metric, and, as predicted, groups generated many fewer ideas for the harder exercise. We were also interested in the group’s dynamic as they performed these tasks. Were they apathetic or engaged? Was there a dominant member of the group? Ultimately, when a loan payment is due and some individuals are short on money, can the group come up with ideas for how to get the extra money? We hope that these generative exercises will shed light on this critical group trait.

Gerardo snags a picture with one of the applicants we met and her business, a stand selling eggs, candy, and other sundries. The small scale of some businesses we encountered, such as the one pictured above, reinforces their need for access to financial products. This woman’s entrepreneurial endeavors are only limited by the capital she can acquire.

Measuring decision making abilities through consensus
To measure a group’s decision making abilities, we created a time-to-consensus task. This exercise asks the group to solve a problem where all members must agree on the answer they provide. While we asked the groups to estimate the population of the state they live in, we actually don’t care how accurate their answer is! What’s more important in this exercise is how the group reaches consensus. Are they indifferent and accept the first estimate suggested? Or do they take their time and argue intensely while deliberating over possible solutions? What kind of strategies did they use to reach their estimate? Importantly, this task provides loan officers with a window into the group dynamic that might not otherwise be seen if the assessment merely collected static information such as sociodemographics and business revenues.

Financial inclusion is the mission of LenddoEFL, but working directly with the people we want to include allowed me to better understand how our assessments must be tailored to their cultures and experiences. The better we can measure group dynamics that predict creditworthiness, the more successfully we can extend financial services to those in need. As we continue to expand our credit scoring offerings across the world, looking past the business jargon we use and maintaining empathy for the humans we touch is essential on our path to #include1billion.

Welcoming our New Behavioral Science Manager

In this photo, Jonathan demonstrates cultural differences in height during a field visit with loan applicants in Veracruz, Mexico.

Since our merger, we have welcomed a number of incredible new colleagues onto the LenddoEFL team. Jonathan Winkle joins us in our Boston office as our new Behavioral Science Manager. We cornered him to learn more.

Tell us about your background?

In undergrad I majored in psychology, where I developed a passion for researching the brain and behavior. To gain more experience after college, I worked in a systems neuroscience lab at MIT studying visual attention. Eventually I found my way to Duke where I earned my PhD in cognitive neuroscience. My dissertation focused on the behavioral economics of dietary choice, investigating how the mind is affected by “nudges” that can bias people towards healthy (or unhealthy) eating habits.

What brought you to LenddoEFL?

Studying behavior has always excited me because it is the ultimate endgame of our brains’ hard work, yet academic research on the topic can often be too disconnected from real-world problems. I found myself wanting to make more of an impact on society, and in this role I can leverage my experience to quickly and directly improve people’s lives around the world. As the Behavioral Science Manager for LenddoEFL, I can test a new hypothesis and apply that knowledge globally in a matter of weeks. And the better I do my job, the more people I can help get access to life-changing financial services.

What are your plans as Behavioral Science Manager?

My primary goal is to drive feature engineering. Features are the observations we collect about individuals to predict credit risk, and feature engineering is the process of discovering and creating new features to make our algorithms work better. For example, how honest a person is might be predictive of loan default, but we first need to quantify honesty as a feature to use it in a predictive model. As new features make our models more predictive and more powerful, our financial institution clients all over the world will gain a better understanding of their under-banked loan applicants.

If I am successful, we will be better at predicting if someone will repay their loans, thereby allowing our clients to make the best, most informed decisions possible. No pressure.

Across data sources, we look for ways to profile a person’s character, trying to understand how traits like honesty or conscientiousness relate to credit risk. This is a hard, but extremely important challenge.

LenddoEFL deals with both psychometric/behavioral and digital data sources. How do those differ and how do you think about each?

On the psychometric side, we engineer the form our data will take from the outset, then extract it by inserting new content (e.g., survey questions or psychometric games) into our simple, interactive assessment. We can be more hypothesis-driven when it comes to designing features in this realm.

On the digital side, we work with large, unstructured data sources where we necessarily have to be more exploratory and let the data do the talking.

Will you be working with our research advisors?

Absolutely! I am looking forward to working with leading researchers like Peter Belmi to push the envelope of our own research while also sharing the insights gained from our unique dataset with those in the field of behavioral economics. We will also be inviting more researchers to collaborate on our work.

Enough about work, what do you do for fun?

I like to rock climb, play Go, hang out with my dog Clementine (pic below), and try out new recipes in the kitchen.

What’s a fun fact about you?

I have a tattoo of Phineas Gage, a famous figure in the history of psychology and neuroscience. Gage was a railroad worker in 1848 that lost the left pre-frontal cortex of his brain when an accidental explosion sent a 3 foot iron rod rocketing through his head. Miraculously, he survived and was even able to walk himself to a doctor despite the 11⁄4 inch hole running behind his left cheek and out the top of his skull. He lived for 11 years after this event, but experienced marked changes in his personality that have been studied ever since. The story in itself is fascinating, and of particular interest to me is how Gage’s misfortune shaped theories of the mind for more than a century after the accident.

Look out for a future post from Jonathan about his field work in Mexico and learnings about group dynamics.

Media Telecom | Orange Bank comienza a ofrecer micropréstamos personales

Micropréstamos: un negocio en aumento

La posibilidad de ofrecer micropréstamos a los usuarios tienta cada vez más a la industria. No solo a la banca digital. El año pasado, Telefónica de España presentó Movistar Money. Se trata un servicio de préstamos al consumo. Asimismo, una de sus principales características es que son preconcedidos a los clientes de la operadora.

En Latinoamérica esta tendencia es todavía más importante. Así, en México, Lenddo y Entrepreneurial Finance Lab (EFL) se fusionaron para brindar productos financieros para el sector no bancarizado. Read full article.