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.

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.

image2.jpg

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.

image1.jpg

 

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

The Economist | Mobile financial services are cornering the market

Mobile money means more nimble financial services

20180505_SRD003_4.jpg

KAUSAR PARVEEN, of Chakwal district in the north of Pakistan’s Punjab province, is a star beneficiary of the work of Karandaaz, a Pakistani financial-inclusion charity. The owner of just one buffalo, she borrowed 75,000 rupees (about $650) to buy another one and started selling milk. The business has done so well she now has four buffaloes and an assistant, and has taken out another loan to install a biogas plant, saving on firewood and sparing her family the woodsmoke.

This was how microcredit, as promoted by Muhammad Yunus, a Nobel-prizewinning entrepreneur from Bangladesh who launched his Grameen bank in 1983, was supposed to work: credit would allow the poor to establish microbusinesses and improve their lives. The idea has spread across the developing world. Sadly, in many places it has not worked out that way. A big expansion of microcredit in India’s Andhra Pradesh province caused a crisis in 2010 when the lenders were blamed for an increase in suicides by farmers. A World Bank paper last November, written by Robert Cull of the bank and Jonathan Morduch of New York University, considered evidence showing that microcredit has had “only modest average impacts on customers”. It has often been used to cover the normal ups and downs of household spending, which is helpful but not transformative. Read full article.

MICROCAPITAL | Traditional Credit Bureau Ctos Tapping LenddoEFL to Add Digital, Behavioral Data to Scoring Models to Boost Financial Inclusion in Malaysia

Malaysian credit scoring firm Ctos recently partnered with LenddoEFL, an alternative credit scoring firm with offices in Singapore and the US, to increase the number of people and small businesses for which it can supply credit evaluations. The usage of alternative data can also improve the credit scores of some loan applicants.

LenddoEFL, which was created in 2017 by the merger of Singapore-based Lenddo and US-based Entrepreneurial Finance Lab (EFL), bases its evaluations on “social media activities, browsing behaviour, geolocation and other smartphone data.”

As of late 2017, the organizations had completed a total of 5 million credit evaluations facilitating USD 2 billion in lending by 50 banks, microfinance institutions, insurers, retailers and telephone companies in 20 emerging markets.

Read full article

Lodex Blog | LodexSecurity, Privacy and Social Data - Insights from LenddoEFL

Social data empowers millions of people around the world through their transactions with financial services providers. We wanted to bring this technology to Australia and have teamed up with LenddoEFL to do this.

We spoke with Audrey Banares Reamon, Quality and Compliance Manager, and Howard Lince III, Director of Engineering, from LenddoEFL, and asked them some of the questions you have been asking to help give you a greater insight into the power behind Social Scoring and using non-traditional data. Enjoy.

See full interview

Forbes | Could Personality Tests One Day Replace Credit Scores?

forbes article 042018.jpg

If someone gave you an unexpected $100, what would you do with it? Give it to charity? Save it? Splurge on something fun?

We see questions like this in personality quizzes online, and sometimes even when applying for jobs. Your answers are supposed to help others predict your behavior using what’s called psychometrics.

And companies looking to avoid hiring potential problem employees aren’t the only institutions interested in psychometrics. The financial industry might get in on it, too.

What if, instead of a lender checking your credit score, they gave you a personality test?

Read full article.

Spore Magazine | Réduire les risques : Des systèmes innovants d’évaluation du crédit pour aider les agriculteurs

Screen Shot 2018-04-26 at 6.07.32 PM.png

La difficulté d’emprunter, pour de nombreux petits agriculteurs ne disposant ni de garanties ni d’antécédents de crédit, a fait apparaître de nouveaux systèmes pilotes d’évaluation du crédit pour aider les banques à apprécier les risques que présentent réellement les emprunteurs et tirer parti de ce secteur potentiellement lucratif.

L’évaluation psychométrique

Pour augmenter les taux d’acceptation et réduire les délais de traitement des prêts aux agriculteurs, Juhudi Kilimo, prestataire de solutions financières pour les petits agriculteurs d’Afrique de l’Est, teste la méthode d’EFL Global, une entreprise privée qui utilise l’évaluation psychométrique pour créer les profils de risque d’emprunteurs africains, asiatiques, européens et latino-américains. Cette méthode pilote – financée par la Fondation Mastercard – mobilise les représentants de six agences kényanes de Juhudi qui visitent et incitent les demandeurs de prêts à passer des tests psychométriques sur tablette. Ces tests permettent, selon EFL, de définir leur personnalité, y compris leur self-control en matière de dépenses et budgétisation. Sur cette base, une cote de crédit à trois caractères est alors attribuée aux demandeurs. À partir de son évaluation initiale d’environ 6 000 clients réalisée à l’aide de l’outil d’EFL, Juhudi a constaté que 6 % des personnes classées dans le quintile le plus bas avaient au moins une fois des arriérés de remboursement de 60 jours pour un prêt type d’un an, contre 1,5 % dans le quintile le mieux noté.

Read full article.

Bitcoin | 8 empresas da América Latina interrompendo finanças locais paypal bitcoin

"O que define Lenddo além de tradicionais financiadores são os critérios é usa para estabelecer os empréstimos, uma vez que depende de conexões sociais para determinar a solvabilidade. Por uma questão de fato, o seu alvo principal são os mutuários acesso bancário que são excluídos do circuito de crédito tradicional e estão acima do limiar de micro-finanças."

Read full article.

Medici | What Happens at the Convergence of Machine Intelligence and Online Lending

Credit scoring and approval rates changed substantially with the arrival of alternative lenders, mainly due to the adoption of new practices in collecting and analyzing potential borrower data. Alternative data has played its role in expanding horizons for financial institutions and for creating an opportunity to enter the financial sector fir technology startups and data-rich international companies.

While social media, for example, as a source of data for creditworthiness assessment is still at a nascent stage, certain startups are already claiming to have incorporated information from social networks into their frameworks. In the quest to reinvent the way to assess consumer-related risk (as well as extend credit to unscored and questionable), startups were found more imaginative than traditional institutions.

Alternative data requires alternative approach to data analytics, which wide adoption of machine learning and artificial intelligence brought.

Read full article

Medici | How BigTech Challenges Banks

The evolution of bank-FinTech narrative brought us to a logical point, when FinTech is no longer perceived to be a threat to traditional banking, but rather as an instrument in re-establishing their position in the financial services industry. The narrative, however, doesn’t end there. As Citi emphasized in its March 2018 Bank of the Future: The ABCs of Digital Disruption in Financereport, traditional banking is being challenged not by small FinTech startups, but by established tech giants because of:

Big data customer insights

"Social media has been recognized by Wharton as an important data source for credit scoringback in 2014, although the practice of judging a stranger based on his/her social environment is not really new. One of the core ideas is that “who you know matters.” Companies like LenddoFriendlyScore, and ModernLend use non-traditional data to provide credit scoring and verification along with basic financial services. Those companies are creating alternative ways to indicate creditworthiness. The information contained about a person in social networks can provide some sort of verification that the person exists at all and who that person is."

Read full article

 

PRSync | The Future of Artificial Intelligence in Banking

 

"The Future of Artificial Intelligence in Banking", report examines the most significant uses of AI in retail banking, in both front-office and back-office implementations.

Companies Mentioned:
Admiral
Amazon
Atom Bank
Bank of America
DataVisor
Ernest
EyeVerify
Facebook
Google
IDnow
Kasisto
Lenddo
Moneyhub Enterprise
Olivia
PayPal
Personetics
Plum
POSB
Starling Bank
USAA
TrustingSocial
Wells Fargo
ZestFinance
Inquire for Report at http://www.reportsweb.com/inquiry&RW0001866700/buying

Read full article

Microfinance Gateway | Malaysia: Fintech Heavyweight CTOS Expands Services for A Better Financial Inclusion

CTOS has been Malaysia’s largest in terms of credit reporting, just announced a partnership with LenddoEFL to achieve a joint vision of financial inclusion for the people who had difficulties securing loans in Malaysia due to the lack of credit history. 

Read article in MicroFinance Gateway website: https://www.microfinancegateway.org/announcement/malaysia-fintech-heavyweight-ctos-expands-services-better-financial-inclusion

Financial Express | Credit bureau veteran Darshan Shah joins LenddoEFL as Managing Director

“Having worked across geographies and being well-versed with the problem of credit coverage, I look forward to leveraging my experiences to work on the challenge of financial inclusion in India. The need is massive with less than 45% of Indian adults included in the credit bureau and less than 10% borrowing from a financial institution in the last year, as per the World Bank.” said Darshan Shah.

Read full article in Financial Express

Enanyang MY |【独家】申请银行贷款被拒 CTOS接纳无信贷记录者

(吉隆坡12日讯)许多早前因传统信贷风险而无法获得贷款机构服务的人士,现今将可享有更包容性的金融服务。 马来西亚信贷情报服务私人有限公司(CTOS)今天与LenddoEFL...

统信贷风险而无法获得贷款机构服务的人士,现今将可享有更包容性的金融服务。 马来西亚信贷情报服务私人有限公司(CTOS)今天与LenddoEFL 达成合作伙伴关系协议,携手为甚少或几乎没有信贷记录的大马消费者,实现普惠金融的CTOS信贷记录有限评分

Read full article.

IT Sideways | Fintech Heavyweight CTOS Expands Services for A Better Financial Inclusion

CTOS has been Malaysia’s largest in terms of credit reporting, just announced a partnership with LenddoEFL to achieve a joint vision of financial inclusion for the people who had difficulties securing loans in Malaysia due to the lack of credit history. 

Under the partnership, CTOS and LenddoEFL will launch a universal credit decisioning platform capable of accessing credit-worthiness of those who lack credit history, providing financial institutions with expanded service coverage. Read full article.

Malaysian Business Online | CTOS and LenddoEFL partner up to boost Financial Inclusion in Malaysia

CTOS Data Systems Sdn Bhd, Malaysia’s largest credit reporting agency, has entered into a partnership with LenddoEFL.

CTOS Data Systems Sdn Bhd, Malaysia’s largest credit reporting agency, has entered into a partnership with LenddoEFL.

AstroWani | CTOS, LenddoEFL extends financial inclusion in Malaysia

30% of Malaysians with good potential is still denied access to loans. This is because they lack or directly have no credit history. In order to curb this issue, Malaysia's Largest Credit Reporting agency, CTOS Data Systems Limited, partne…

30% of Malaysians with good potential is still denied access to loans. This is because they lack or directly have no credit history. In order to curb this issue, Malaysia's Largest Credit Reporting agency, CTOS Data Systems Limited, partnered with Fintech LenddoEFL company and emerged with a new solution.

Karangkraf | Beri peluang rakyat akses perkhidmatan kewangan

AGENSI pelaporan kredit terbesar Malaysia, CTOS Data Systems Sdn Bhd (CTOS), menjalin kerjasama dengan LenddoEFL bagi memperluaskan perangkuman kewangan pengguna Malaysia yang kurang atau tidak mempunyai sejarah kredit melalui ‘CTOS Non-Traditional Data Score’.

Ketua Pegawai Eksekutif Kumpulan CTOS Holdings Sdn Bhd, Dennis Martin berkata, walaupun markah kredit ramalan tentang tingkah laku pembayaran telah meningkat tahun demi tahun, namun sekumpulan besar peminjam yang berpotensi baik ketika ini dinafikan akses kepada kredit disebabkan kurangnya sejarah kredit.

“Disebabkan pemberian pinjaman pengguna lazimnya bergantung kepada skor kredit, individu ini mendapati diri mereka terpinggir daripada ekosistem kredit dan juga sukar menambah baik markah kredit mereka.

“Dengan memanfaatkan sepenuhnya data tingkah laku dan data digital yang diizinkan penggunaannya oleh pengguna, CTOS dan  LenddoEFL akan melancarkan platform keputusan kredit universal yang mampu menaksir kebolehpercayaan kredit mana-mana rakyat Malaysia, baik yang ada sejarah kredit mahupun kurang sejarah kredit,” katanya dalam kenyataan media.

Menurut Dennis, kini banyak individu yang dahulunya kurang dilayan oleh institusi kredit atas alasan risiko kredit tradisional mereka, akan menikmati peluang untuk akses kredit. 

Read full article.

Finance Digital Africa | Can big data shape financial services in East Africa?

Psychometric big data—including online quizzes to judge character or personality traits and analysis of Facebook “likes”—is garnering increased attention. Suppliers of psychometric data or psychometric tools, such as EFL, believe not only that their data and analytics are predictive but also that they have a key advantage in their applicability to everyone, even clients with limited credit history (“thin-file” clients), as a starting point. When layered with other big and traditional data sources (e.g., social media, mobile phone, bureau data, bank historical data), proponents expect psychometrics to become even more powerful. Indeed, Equity Bank conducted an experiment with EFL’s psychometric scoring model and found it both predictive and useful; they plan to integrate it into applicable models across their regional subsidiaries.

 

 Moreover, Juhudi Kilimo decided to partner with EFL in order to evaluate character as part of their risk assessment. This was previously carried out by loan officers, but they believed the EFL approach would be more objective.

Read full article.

World Bank | Using a PhD in development economics outside of academia: interviews with Alan de Brauw and Bailey Klinger

Today's interviews are with Alan de Brauw, a Senior Research Fellow in the Markets, Trade, and Institutions Division at the International Food Policy Research Institute; and Bailey Klinger, the founder and (until recently) CEO of the Entrepreneurial Finance Lab

Read full interview with Bailey Klinger.