Case study: Universal credit scoring for Female-led SMEs in Ethiopia

LenddoEFL collaborated with the World Bank Group to facilitate psychometric assessment for alternative credit scoring as part of the Women Entrepreneurship Development Project (WEDP) launched by the Government of Ethiopia.

The World Bank recently published an extensive and insightful report: “Designing a Credit Facility for Women Entrepreneurs Lessons from the Ethiopia Women Entrepreneurship Development Project (WEDP)”, which delves into different aspects of this project.

To download the full report please visit: https://openknowledge.worldbank.org/bitstream/handle/10986/34013/Designing-a-Credit-Facility-for-Women-Entrepreneurs-Lessons-from-the-Ethiopia-Women-Entrepreneurship-Development-Project.pdf?sequence=4

WEDP was launched in 2012 by the Ethiopian government with the aim of increasing the earnings and employment of growth-oriented micro and small enterprises (MSEs) owned or partly-owned by women entrepreneurs in Ethiopia. LenddoEFL was selected to

Following are selected extracts from the World Bank Report regarding LenddoEFL’s contribution

From Page 11 of the Report:

“WEDP provided a stable anchor from which to innovate, including drawing on financial technology (fintech) as a means to maximize the operational efficiency and effectiveness of lenders, while relaxing collateral constraints for women entrepreneur borrowers. The success of introducing a non-traditional credit assessment methodology to a low-tech and low-literacy environment like Ethiopia stirred enthusiasm and buy-in from the financial sector.

Financial institutions’ traditional lending methodologies often require data on loan applicants, including their tax records, credit history, financial statements, and legal status. MSEs in general, and women-owned MSEs in particular, often lack sufficient credit history, reliable financial statements, and collateralizable assets. This is compounded in emerging markets like Ethiopia, where there is an absence of proper financial sector infrastructure, such as a credit information system, which can help lenders identify credit-worthy borrowers. Faced with such limitations, financial institutions rely on unduly large collateral requirements to minimize their exposure and risk. This results in many women-owned MSEs being excluded from the financial system, while financial institutions miss the opportunity to tap into a pool of potential borrowers.

In recent years, there has been a tide of financial technology, or “fintech”, that has been sweeping across the global financial landscape, which has introduced new tools, systems and business models — allowing financial institutions to accelerate MSE lending in a profitable and cost-effective manner. In early 2014, the WEDP team began investigating different technologies that could address the collateral constraint by closing the information gap among MFIs. Among the promising technologies was one developed by the Lenddo Entrepreneurial Finance Lab (LenddoEFL), whose approach does not rely on traditional financial statements, business plans, high-value physical assets, or borrowing histories. Rather, their value proposition was a universal credit score that was calculated based on a psychometric tool that evaluates the entrepreneur’s personal attributes, including “locus of control, fluid intelligence, impulsiveness, confidence, delayed gratification and conscientiousness.” LenddoEFL’s technology allows for an applicant to complete a 45-minute self-administered test on a tablet computer to determine his or her eligibility for a loan. While this technology had been used in other contexts to help banks improve and/or expand their portfolios, WEDP was among the first initiatives to harness this technology as a substitute for fixed asset collateral. Moreover, for those applicants who already had collateral, the test was designed to allow them to qualify for a larger loan size.

To pilot the psychometric testing, the Amhara Credit and Savings Institution (ACSI) was selected, as it is the largest MFI in the country, with over 1 million active borrowers, 440 branches and individual loans comprising 10 percent of its portfolio. ACSI saw the LenddoEFL technology as an opportunity to improve their ability to screen for individual loans even beyond their WEDP portfolio.

Despite EFL’s great track record in Sub-Saharan Africa, Ethiopia’s context presented a unique challenge. In addition to translating the test into Amharic, LenddoEFL worked to include more visuals and interactive exercises to cater to ACSI’s low-tech and low-literacy clients. Moreover, while ACSI was enthusiastic about the psychometric testing, it was understandably hesitant about relying too much on the technology, given the lack of an evidence base in Ethiopia. As such, EFL focused on testing clients without using the resulting score as the basis for the credit decision – allowing ACSI to observe the accuracy of the test without taking on any credit risk.

In 2015, the psychometric test was pre-piloted in two ACSI branches in Bahir Dar with 420 interested clients, and then piloted across 12 branches with 2,496 clients. As loans matured, WEDP was able to track the progress of the loan repayments. The data revealed a clear trend between psychometric test scores and loan performance. Those borrowers who scored higher on the test were seven times more likely to repay their loans than lower scoring customers. Further results and details of the study are available starting on page 45. 

“Having succeeded with one of Ethiopia’s largest financial institutions, the pilot demonstrated that a psychometrics-based loan screening system could be developed in the country, pushing the frontier of credit access for hundreds of thousands of collateral constrained borrowers. The ACSI experience demonstrated to policymakers and private sector leaders alike that fintech can make a profitable and profound difference to the Ethiopian economy. ”

Based on the proof-of-concept from the ACSI pilot, other MFIs began requesting for the psychometric technology. In 2018, WEDP launched the LenddoEFFL screening system with Wasasa. In 2020, ADCSI followed suit. Around this time, as an added incentive, DBE began providing additional liquidity (named “WEDP X”) to support MFIs who were eager to test out alternative collateral products. Moving forward, WEDP is likely to build on this incentive mechanism to facilitate further crowding in by other microfinance institutions across Ethiopia.”

Source: The World Bank

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Header photo by Stéphane Hermellin on Unsplash

Mondato Feature | Can Personality Predict Loan Performance

LenddoEFL has been featured by leading FinTech consultants, Mondato, in their Insights Series.

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Know Your Customer — often abbreviated as KYC — is such an important part of success in digital finance that it almost deserves to be canonized into KTC: Know Thy Customer. Indeed, creating “bank-legible” forms of identity authentication, streamlining methods of verifying it, and tailoring business strategies around it — all of these entail an enormous range of regulatory and business challenges, from data privacy to algorithmic discrimination. In evaluating the promises of alt-data for banking thin-file customers, this week’s Insight explores the promises and perils of psychometrics as a way of evaluating would-be lendees.

Know Thy Customer

The first maxim adorning the mythical Delphic Temple of Apollo in Ancient Greece, famously, is “Know Thyself.” In business, however — particularly in the business of lending — it is easy to see why the first law may rather be ‘know thy customer.’ In the US, knowing who to lend to was revolutionized in the 1950s when an engineer and a mathematician teamed up in California to generate the first ‘credit score’ — today known as a FICO score — factoring a number of data points around payment history, amounts owed, length of credit history, types of credit used, and more.

The success of this system spread throughout much of the world, and though the precise ways in which each national jurisdiction has developed or regulated credit scoring varies significantly, the art of recouping loans has become much more of a science: the science of quantifying a specific individual’s likelihood to repay a loan under a given set of assumptions or circumstances.

Here, traditional credit bureaus (think EquiFax, Transunion, and Experian in the US) have historically played a major role in the development of retail bank credit. The World Bank deemed the model good enough for export, and has been promoting the development of private credit bureaus in emerging markets since 2001. The record, evaluated by any number of dimensions, is mixed at best; as of 2019, private credit bureaus cover just a third of adults globally, with gaps in coverage unsurprisingly concentrated in lower-income countries.

Indeed, while such forms of credit assessments (for better or for worse) lie at the center of retail finance in formal economies, the paradigm presents serious challenges in emerging markets. Given the paucity of ‘bank-legible’ financial histories in the informal sector, would-be loan applicants in Africa, Asia, or Latin America seeking a loan from a traditional bank might find their hopes and dreams of home-ownership or entrepreneurship at the mercy of a faceless bank bureaucrat judging their ‘worthiness’ on nothing but their gut — or, worse, their biases and stereotypes.

Enter alt-data. The digital era has spawned entirely new forms of understanding people’s behavior through the combination of new forms of data generation and algorithms that can identify hidden correlations between ‘user attributes’ and payment outcomes. In other words, given the appropriate data inputs on an individual and the larger population — as well as judicious interpretation — big data and machine learning can yield actionable, predictable outcomes.

But from whence is this alt-data mined, and is it reliable? Our phones, naturally, can provide a ready trove of information about us, and given their ubiquity even among the world’s poorest, they’re increasingly being leveraged for purposes both benevolent and nefarious. Same goes for satellite data — like all powerful tools, they are double-edged.

Source: UC Berkeley Center for Long-Term Cybersecurity, 2020

Psychometrics, however, are fundamentally different from other alt-data sources in at least two ways: firstly, there are less privacy concerns since psychometric data can only be collected with the potential lendee’s consent — and without the use of labyrinthine terms and conditions agreements that often obscure data mining operations — given that they are administered as a questionnaire. Secondly, while not everyone has a cell phone or uses it extensively, everyone’s got a personality.

Alt-Data Streams of Consciousness

Psychometrics occupy a particularly sensitive — and almost mystical — place among sources of alt-data. This is due, at least partly, to the fact that the entire field of psychology has sustained fundamental challenges in recent years. Against a canonical understanding of “homo economicus” as a utility-maximizing rational actor, the sub-discipline of behavioral economics has been gaining traction as a more rigorous way of understanding, predicting and even influencing human behavior.

Similarly, the past few years have uncovered a systematic bias among swathes of psychology experiments that universalize generalizations drawn principally from studying populations in Western, Educated, Industrial, and Democratic — aka WEIRD — countries.

““Decades of psychological research designed to uncover truths about human psychology may have instead uncovered truths about a thin slice of our species — people who live in Western, educated, industrialized, rich, and democratic (WEIRD) nations.””

— Beyond Western, Educated, Industrial, Rich, and Democratic (WEIRD) Psychology: Measuring and Mapping Scales of Cultural and Psychological Distance, 2020

Meanwhile, pop-psychology theories further invite skepticism, like the infamous “Color Test.” Such tests aim to simplify personality traits into neat, discrete and stable categories, purported to determine romantic, amicable or professional compatibility between individuals. Even popular tests like the famous Myers-Briggs Test, however, mostly fail to stand up to snuff when the empirical rubber meets the road of statistical significance — for most Human Resource departments, the most charitable assessment of such tests has been summarized as “not entirely useless.”

But psychometrics for credit-lending deserve a hard look, if for no other reason than the endurance of LenddoEFL in the marketplace.

LenddoEFL is perhaps the oldest and best known outfit providing psychometric credit scores. The product of a merger between Harvard research-incubated Entrepreneurial Finance Lab and Lenddo, a Singapore-based smartphone data credit specialist, the two companies joined forces in 2017 and claims to have facilitated over two billion dollars in loans across the more than 20 countries in which it has operated. Its proprietary tests are broadly based on the most rigorously evaluated psychometric frameworks in academia: the “Big Five” personality traits of extraversion, conscientiousness, agreeableness, neuroticism and openness to experience.

The case for psychometrics qua credit-scoring, however, has a fairly major bona fide when it comes to evaluating loan-performance: market proof. An independent World Bank evaluation of a LenddoEFL collaboration with Superintendencia de Banca y Seguros (SBS, the fifth largest commercial bank in Peru) using data from June 2011 to April 2014, concluded that psychometric scores were indeed practicable for identifying ‘good lendees’ that traditional assessments would otherwise pass on:

““Banked applicants accepted under the traditional credit scoring method but rejected based on their EFL score are 8.6 percentage points more likely to have been in arrears for more than 90 days during the 12 months after being screened by the EFL tool, compared to 14.5 percent of entrepreneurs who are accepted using both methods … results suggest that the EFL tool can be used to offer loans to unbanked applicants who are rejected under the traditional method without increasing the risk of the loan portfolio.””

— World Bank evaluation report of LenddoEFL pilot in Peru

The evaluation is narrow in its findings, but it lends strong evidence that rigorously developed psychometric tests are able to add a layer of KYC granularity in identifying individuals who are both able to generate enough cash flow to service their debt and who are willing to repay their debt.

All Data is Credit Data

While an increasing number of financial institutions and fintech players are learning to integrate alt-data feeds into their KYC processes, psychometrics remain an edge case. Nonetheless, a handful of psychometric providers have gained traction around the world, like Innovative Assessments based out of Israel (though with a large global footprint), or GFI, focused on the Malay market. A commonality across psychometric providers appears to be founders with a long and established track record in academia and social science research methods. This perhaps explains why there aren’t more psychometric companies out there; amidst the aura of mind-reading in a psychometric business pitch, investors are typically reassured that the product is literally built by a PhD holder. However, these are not necessarily the individuals known for building and scaling companies and products.

James Hume and Jabu Sithole, respectively the Chief Operating Officer and Head of Modelling at LenddoEFL, reflect on this particular challenge in their own company’s history. They note that the secret sauce in creating a successful psychometric-for-lending business is not in understanding or quantifying ‘personality’ per se, but rather in ruthlessly testing correlations within data sets comprised of carefully collected character attributes, and — critically — intelligence on ‘bads,’ or lendees who default on their obligations.

““The key is to ask the right question. Our primary driver is not to understand personality. We are laser focused on correlations and predictability, specifically around repayment.””

— James Hume - COO, LenddoEFL

““When we ‘train the model,’ what we are doing is using historical data to decipher historical patterns and project into the future. But if you lack ‘bads’ in certain segments you examine, then it’s hard to get a sense of who will default. So to begin with, we need sufficient sample size and representativeness, and different characteristics to generate confidence. This can take time — between 6-9 months.””

— Jabu Sithole - Head of Modelling, LenddoEFL

This process necessarily entails a learning curve for each new market — after all, no one is claiming that Nigerians who score the same on questions testing conscientiousness or confidence will behave the same way as Chinese applicants with the same scores. But part of the secret sauce also comes with measuring how people answer, not just what they answer.

Indeed, the time an applicant spends on a question can itself provide an additional data point to feed into the credit-algorithm. Mondato has previously explored how such “autogenic” data processing techniques have proven effective in predicting who will churn in an IFC-Mastercard report on account dormancy last year, and it perhaps bears repeating that when it comes to machine learning for human behavior, human decision-makers often need to relinquish the “need to understand in order to satisfy the need to predict.”

Personality as Product?

So if personality traits can reliably be measured in ways that can help the unbanked gain access to credit, why haven’t such tools become ubiquitous? For starters, there is still a lot of market education to be done. Traditional models are already fairly good at identifying great loan applicants and terrible ones; it’s in the segment of ‘average’ lendees, or those at the margin, that there is the most room for improvement — and most banks don’t even make most of their profits through retail lending in the first place. Incrementally improving their lending models — while improving financial inclusion — is not going to rock their bottom lines, and thus creates significant bottlenecks to uptake.

Secondly, ‘productizing’ alt-data for lending is still a relatively niche use-case. While the idea holds a lot of promise, particularly as digital identities become more and more critical to long-term customer relationships, a profitable business model for offering B2B alt-data credit scoring is yet to be fully cracked. Simply put, developing and incessantly refining behavior-predicting algorithms isn’t free, nor is it cheap.

Subsequently, LenddoEFL recently simplified its pricing model, lowering upfront engagement costs in favor of recurring service charges. The gamble is that the service can provide value to lenders immediately (for example around cross or upselling opportunities) and on an ongoing basis, rather than charge a big lump-sum up-front for a model that only starts to yield fruit in half a year. In this way, it hopes to generate more value to clients and more revenue streams for itself even before the full repayment picture needed to calibrate the model for its primary purpose — identifying ‘invisible good bets’ — is even completely baked.

Nestled at the heart of “alt-data for inclusion” narratives are fundamental ethical questions. As researcher Rob Aitken reminds us, inclusion projects often constitute troubling new kinds of social sorting and segmentation:

““Experiments in alternative credit scoring are, in some essential measure, attempts to know the unbanked – to know unbanked bodies, payment traces, psychological inclinations, online behaviour, social footprints – and to verify the creditworthiness of those bodies in detailed and intimate ways. The body becomes itself a kind of ‘database’ from which some sort of content is extracted or “captured,” then algorithmically encrypted and sorted for retrieval.””

In lightly regulated environments, consumer protections are all the more important, particularly given the ominous implications of racist, sexist or neocolonial artificial intelligence. And yet, hope remains that models will evolve that put people in charge of their own information, and in this sense psychometric evaluations may represent a uniquely powerful modality of respecting unbanked or underbanked individuals’ privacy, dignity and agency. Can we imagine a future where all consumers will be empowered not only to control and protect their data, but perhaps even to monetize it according to their own needs, desires, freedoms or aspirations? Perhaps the first seeds can be found in tools that allow people simply to learn as much about themselves as others are collecting. The Oracle at Delphi, surely, would agree with this virtue.

Photo by The New York Public Library

If you would like more information about the use of psychometric testing for credit scoring, please contact us.

LenddoEFL puede predecir el riesgo, pero ¿les gusta a nuestros clientes? MicroBank evalúa la usabilidad de LenddoEFL y el impacto en NPS

(English version below)

MicroBank, la entidad financiera española líder en microfinanzas en Europa, está evaluando constantemente sus procesos de cara al cliente, respecto a la usabilidad y la aceptación del usuario, una forma de actuar que supone una de sus prioridades. Cuando el banco desarrolla una innovación, se aplica el mismo nivel de escrutinio.

 Entonces, cuando MicroBank decidió usar LenddoEFL para evaluar el perfil crediticio emprendedores para acceder a préstamos, el despliegue estaba condicionado a una experiencia positiva de sus clientes.

 MicroBank empezó a medir la usabilidad del cuestionario de LenddoEFL, su impacto en el Net Promoter Score (NPS) con respecto al uso del microcrédito convenio entidades y cómo la gente se sentía al hacerlo.

 Para nuestro agrado, encontramos que el cuestionario de LenddoEFL es fácil, comprensible y de duración apropiada. Acá se observan algunos puntos relevantes:

• NPS: 84%, superando ampliamente nuestras expectativas

• Satisfacción global:  9.16 de 10

• Idoneidad: 82% encontró el cuestionario adecuado para evaluar a prestatarios del segmento micro. Esto es excelente comparado a las herramientas de la mayoría de los bancos, pero, obviamente, no dejamos de lado al 16% que no encontró el cuestionario adecuado. Nuestro equipo de producto trabaja 24 horas (literalmente, somos un equipo global) para mejorar constantemente nuestra evaluación de crédito – haciendo el contenido más fácil, más divertido, más rápido de completar, más predictivo y conveniente para todos los niveles de alfabetización y manejo de tecnología.

• Duración: Más del 70% encontró que el cuestionario tiene la duración correcta. Esto es bueno, pero queremos mejorar.

• Facilidad de uso: Más del 95% piensa que el cuestionario de LenddoEFL es fácil de completar.

MicroBank es un cliente exigente y este proceso nos ha ayudado a aprender y mejorar. Mientras que las noticias financieras están llenas de fintechs ayudando a bancos, este es un gran ejemplo de un banco mejorando a una fintech. Estamos muy contentos de que los resultados sean mejores de lo esperado, especialmente en un país como España, donde el acceso al crédito es generalmente bueno y la gente espera que el proceso se dé con la mínima fricción. Más aún, apreciamos que MicroBank nos haya desafiado para asegurar que nuestras herramientas superen las expectativas de sus clientes.

Esto nos hace mejores.

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Para descargar el white paper completo por favor ingresa tu dirección de correo electrónico debajo.

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LenddoEFL can predict risk, but do our clients like it? MicroBank evaluates the usability of LenddoEFL and the impact on NPS

MicroBank, the leading Spanish financial institution in microfinance in Europe, is constantly testing its client processes, regarding usability and user acceptance, ensuring these are always top priorities. When the bank launches an innovation, the same level of scrutiny applies.

So, when MicroBank decided to use LenddoEFL to assess the credit profile of entrepreneurs to access loans, the rollout was conditional on a positive customer experience.

MicroBank began to measure the usability of the LenddoEFL questionnaire, its impact on the Net Promoter Score (NPS) regarding the use of entities agreement microcredit, and how people felt about doing it.

MicroBank found the LenddoEFL questionnaire to be easy, understandable, and of appropriate duration. Here are some highlights:

• NPS: 84%, far exceeding our expectations

• Overall satisfaction: 9.16 out of 10

• Adequacy: 82% found the appropriate questionnaire to evaluate micro-segment borrowers. This is excellent compared to the tools of most banks, but obviously we will not leave out the 16% who did not find the questionnaire suitable. Our product team works 24 hours (we are literally a global team) to constantly improve our credit assessment - making content easier, more fun, faster to complete, more predictive and more suitable for all levels of literacy and access to technology.

• Duration: More than 70% found that the questionnaire was the right length. This is good, but we are working to reduce this.

• Ease of use: More than 95% think the LenddoEFL questionnaire is easy to complete.

MicroBank is a demanding customer and this process has helped us learn and improve.

While the financial news is full of FinTechs helping banks, this is a great example of a bank improving a FinTech. We are very happy that the results are better than expected, especially in a country like Spain, where access to credit is generally good and people expect the process to take place with minimal friction. Furthermore, we appreciate that MicroBank has challenged us to ensure that our tools exceed their customers' expectations.

This makes us better.

Mondato Webinar Series: Innovative Approaches to Digital Payments

As many in-person events remain on hold due to COVID-19, industry experts, Mondato have joined forces with the MEF to host a webinar series tackling the discussion of ‘the new normal’ across the payments industry.

LenddoEFL was invited to join a webinar to discuss innovative approaches to commercializing digital payments. The panel also included thought leaders from Mondato and Standard Chartered Bank.

LenddoEFL VP Corporate Development, Camille O’Sullivan joined the panel to discuss how LenddoEFL uses alternative data to link lenders to good borrowers.

As discussed, there are different ways that alternative credit scores can be used. As highlighted by Judah Levine from Mondato, alternative credit scores can even be complementary to traditional scores and there’s a feeling that using alternative data is becoming more and more mainstream.

At LenddoEFL, we work with customers that use alternative credit scores in different ways depending on the market and business case. Alternative Credit Scores can be used either as a proxy in place of a traditional credit score, or in conjunction with traditional methods. Some financial institutions are using alternative data to reassess thin file customers that have been soft rejected using traditional credit scores.

While for lenders that are already using traditional bureau scores, alternative credit scores can be used to lift the predictive power of a traditional credit score. One of the reasons that alternative data can be valuable in conjunction with a traditional bureau score is because of its low correlation.

Watch the full webinar at the link below:

https://www.mondatosummit.com/mondato-webinar

LenddoEFL joins Oxfam webinar for launch of B Ready study

This week LenddoEFL was invited by Oxfam Pilipinas to join a panel for the official launch of their Disaster Risk Financing study. The study is part of the B Ready initiative. 

The B Ready project was launched in 2019 and is the first line of defence for communities in disaster preparedness. 

Located in the Pacific Ocean typhoon belt, the Philippines is hit by up to 20 typhoons each year. While we have no control over these disasters we can help to both protect and prepare people and communities. Each and every one of us can be part of the solutions. 

The B Ready project has two pillars, digital weather forecasting and modelling for early warning, and digital financial technology to allow financial resources to reach those most in need.  

During the webinar, Oxfam explained the importance of credit-risk sharing for communities in disaster-prone areas, particularly those normally excluded from the financial ecosystem. 

Both governments and NGOs are supporting micro-finance institutions and financial service providers that provide loans to these communities by guaranteeing a portion of their loan portfolio. This helps to build the appetite for institutions to lend to these communities.

The FinTech sector is another stakeholder that can provide solutions for communities looking for ways to access credit and prove credit-worthiness. 

LenddoEFL APAC Sales Director Judith Dumapay explained how alternative data can be used to provide an indication of credit-worthiness for those with no or limited access to traditional financial data. Anyone who is online or carries a cell phone shares information whenever they interact with the device. This information can be analysed to understand who they are and their creditworthiness.

Watch the clip of LenddoEFL’s participation below:

Oxfam states that they have greatly relied on the power of collaboration to achieve their goals. LenddoEFL is proud to have partnered with Oxfam several times over the years to support the important work they do in the Philippines and around the world. 

You can view the whole video on Facebook here: https://www.facebook.com/OxfamPilipinas/videos/536358581093393/

Photo by Louie Martinez on Unsplash

LenddoEFL recognised among top finance companies in Singapore

LenddoEFL has been recognised by Welp Magazine as one of the top finance companies in Singapore in 2021 for its use of alternative data to provide credit scores and digital verification.

The list features startups and companies are taking a variety of approaches to innovating the Finance industry, but are all exceptional startups and companies well worth a follow.

To view the list go to: https://welpmagazine.com/these-are-the-top-finance-companies-in-singapore-2021/

Character for Credit in Nigeria

Financial situations change, but your personality will hold steady.

LenddoEFL has shown that credit scores based on behavior and personality traits are continuing to accurately predict default risk, despite the unprecedented economic disruption caused by Covid-19 lockdowns.

LenddoEFL customer, LendMe in Nigeria, has witnessed this new credit-score reality first-hand. They have used LenddoEFL solutions for more than three years to evaluate applicants for Nano-loans. Despite the entire country going into lockdown earlier this year, LenddoEFL’s models have shown strong resilience throughout the crisis and continue to successfully discriminate customers based on their risk level, enabling their lending business to continue at a critical time.

LenddoEFL VP Corporate Development, Camille O’Sullivan, said, “For us, COVID19 has shone a light on the fact that, while your financial situation may change, your core character traits tend to be much more stable. By looking at a customer’s interests (through the apps they download), their reliability, perfectionism or stability traits we are able to provide a more complete profile of an individual.”

Getting credit in Nigeria

Nigeria is an entrepreneurial economy with an estimated 37 million micro, small and medium-sized companies . The World Bank predicts many of these businesses could grow if they had access to finance. However, to access loans, consumers need a credit score. It is estimated that only 40% of adults in Nigeria have a transaction bank account . With no account, these people are ‘invisible’ to banks using traditional credit scoring.

When COVID-19 arrived in Nigeria early this year, the country moved into lockdown restrictions, resulting in millions losing their income. In Nigeria, as around the world, loan default rates have dramatically increased. The Nigerian economy, Africa’s largest, was hit hard. The economy contracted 6.1% in the second quarter of this year and 27% of Nigeria’s labor force (over 21 million Nigerians) are unemployed.

An economic shift of this magnitude results in significant changes in consumer behavior. This has impacted credit scoring models. Predictable behavior has become unpredictable. This makes it difficult for lenders to know who to lend to.

How can you assess the risk of applicants when you are in uncharted waters? The result is less money being lent, at a time when people need it the most. Alternative data decisioning can help financial institutions find a way forward.

Credit through Covid-19: Results at LendMe

While LendMe has seen a slight increase in late payments, especially with recurring customers accessing larger loans, LenddoEFL models continued to accurately predict default risk across the entire portfolio of loans. By combining a tighter credit policy and credit risk models built with a focus on long-term stability in addition to predictive power, LendMe has been able to continue lending to customers needing credit without taking unnecessary risk.

Camille O’Sullivan continues, “We believe that one of the reasons our models continue to hold up is that we only add features that are stable over time and that make business sense. We ensure that the model passes our stability algorithm checks before being selected for implementation.”

LenddoEFL Executive Chairman and CFO, Paul Devine, said, “The results at LendMe are a validation of what we’ve been working on for a decade. We’ve shown that your ability to access financial services shouldn’t only be determined by your bank balance.” “As the effects of the pandemic continue to play out around the world, banks and lenders will have a critical role to play as stabilizers, and they will need to rely on new solutions to do so. Our models are proving that your character is a strong indicator of your likelihood to repay. We’ve already assessed over 7 million people worldwide. And we’re just getting started.”

World Humanitarian Day 2020

It's #WorldHumanitarianDay2020 and we couldn't be prouder to be standing virtual-shoulder-to-shoulder with organisations like Oxfam Pilipinas to say thank you to the #RealLifeHeroes and every person doing their part on this journey.

At LenddoEFL, seeing things differently is central to our mission.

We use technology and science in new ways to reach people in emerging markets around the world who may not have access to financial services. We have developed ways to ‘see’ people who have always been invisible to traditional financial services.

Access to digital financial tools has never been more important than right now. 2020 has forced many people to change the way they work and live and it’s making people consider new ways of solving problems, like financial exclusion.

We have been working on this for a long time, and we are hoping that we can use our skills and solutions to help more people as the global effects of the pandemic continue to play out.

We know that, in the face of a humanitarian crisis, economic resilience is critical to people getting back on their feet. Digital financial technologies also provide a safer and more dignified way to support affected communities, and help jumpstart local economies by increasing people’s access to financial services.

We are proud to be providing our verification solutions to Oxfam to enable identity verification to be carried out more effectively and efficiently to ensure cash can reach the recipient as fast as possible, in a more secure way, and straight to them - can be via a prepaid card or mobile phones.

On behalf of LenddoEFL, our heartfelt thank you to all those on the front lines at Oxfam and in communities around the globe doing everything they can to support people through this challenging year.

We are standing behind you, ready to use our expertise to support you.

The Role of Financial Technology in Disaster Recovery Efforts

Oxfam Pilipinas, together with the Department of Health and other l non-government organizations, visited an evacuation area to assess the immediate needs of those affected by the Taal Volcano eruption in Batangas. (Photo: April Bulanadi/Oxfam)

When Taal Volcano erupted in January 2020, over 70,000 people were forced to take shelter in 300 evacuation centers – the start of a long period of displacement for many. A state of calamity was declared for the entire Calabarzon region. Local authorities expect this to be in effect for the rest of the year.

Elizabeth Embrado had just given birth to her child when Taal Volcano erupted in January. Fearing for their safety - because they lived just a few kilometers away from Taal Lake, in Barangay Nangkaan, in the town of Mataas na Kahoy -she and her family immediately evacuated. Elizabeth's family stayed at a school, which served as the local government's temporary evacuation facility back in January.

Along with displacement is the loss of livelihoods of thousands who rely on agriculture for a living, especially those who are subsistence farmers and fishers. The Department of Agriculture estimated damage to crops to be over $60 million, while local fisheries suffered more than $30 million in damages. This was another burden faced by Elizabeth's family, whose husband works as a fisherman. She said her husband had to stop fishing in the lake because of the eruption. All of this while they had new financial needs with their newborn.

Elizabeth, with her one-month-old baby, in a classroom which serves as a temporary evacuation center in Mataas na Kahoy town, Batangas province. Elizabeth and her baby are among those displaced by the Taal Volcano eruption in January. (Photo: April Bulanadi/Oxfam)

The loss of livelihoods will impact the recovery of affected communities for a long time to come. Humanitarian and development agency Oxfam highlighted early on the need for emergency response plans to anticipate the prolonged displacement of communities within the hazard zone. There was initially an outpouring of support to help displaced families, but there is a critical need to ensure that support continues into the recovery phase.

During Oxfam’s visit to Elizabeth and other displaced families in January, while they expressed gratitude for the relief assistance they received from various groups, they expressed how they would actually much rather receive cash assistance. Indeed, cash support would empower Elizabeth and others to prioritize their needs and increase their sense of self-worth, dignity, and control over their lives. For Elizabeth, her priority needs were essential items for her newborn baby, and livelihood support.

“Our experience in responding to humanitarian emergencies has taught us how economic empowerment is critical to the resilience of Filipinos, particularly women from marginalized communities. This includes access to financial services, access that can be facilitated increasingly through digital platforms. Not only that, digital financial technologies also provide a safer and more dignified way to support affected communities, and help jumpstart local economies by increasing people’s access to financial services,” Oxfam Pilipinas Country Director Lot Felizco said.

Digital financial technology is playing a key role in helping communities in the recovery effort. Oxfam has partnered with Singapore-based FinTech, LenddoEFL, for its digital identity verification solution, known as electronic know your customer (eKYC). This technology allows the user’s identity to be verified faster and more effectively, directly from their mobile device. This enables cash to reach the recipient more efficiently during a humanitarian response. LenddoEFL is providing its services free of charge to support the disbursement of funds to families displaced by the eruption.

“The task of rebuilding requires a considered and tailored approach, guided by those on the frontlines. It is through authentic partnerships, like Oxfam and LenddoEFL, that effective change can be made,” LenddoEFL CEO, Paolo Montessori said.

“We are a mission-driven company, and we are proud to be working with Oxfam at this critical time for the people in the Calabarzon region,” Montessori added.

LenddoEFL first partnered with Oxfam Philippines in 2018 following the devastation wrought by Typhoon Ompong. LenddoEFL’s eKYC solution was deployed to streamline financial assistance to over 1,000 farmers in Cagayan province.

This means the registered farmers were able to access a wide range of financial services, including savings accounts and loans from Philippine financial institutions, in line with regulations of the Bangko Sentral ng Pilipinas (BSP). Regulations in the Philippines have required face-to-face or real-time online interviews to register new-to-card, or new-to bank current account/savings account customers. With this innovation, farmers could be verified faster and more conveniently from their mobile phones.

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About LenddoEFL

LenddoEFL offers software solutions to bridge the gap between lenders and the underserviced. Financial Institutions trust our software solutions to power their financial products, enabling them to reach previously untapped market segments, driving their bottom line. LenddoEFL is built upon over ten years of academic investment purely in risk and decision-making algorithms, having been founded at Harvard. We use AI and advanced analytics to bring together the best sources of digital and behavioral data to help lenders in emerging markets confidently serve underbanked people and small businesses.

About Oxfam

Oxfam is an international confederation of 20 organizations networked together in more than 90 countries, as part of a global movement for change, to build a future free from the injustice of poverty. Oxfam Pilipinas has been working in the country for more than 30 years. Its goal is to contribute to the eradication of poverty by supporting women and other vulnerable groups in saving lives and building livelihoods, enhancing their resilience to crises, and making their voices heard of holding duty-bearers accountable.

Header Photo by Lance Lozano on Unsplash

The looming credit-gap in a post-Covid world

As the economic effects of Covid19 reverberate around the world, it is clear that there will be an impact on credit scores, and that impact will be felt differently in developed and emerging markets.

“LenddoEFL has always, since inception, focussed on emerging economies. Fundamentally, we take alternative data sets and we use them to build credit-risk models for areas of the markets that don’t have traditional credit bureau scores. And we do this in markets where there are no credit bureaus, or where the bureaus only cover 10 - 30% of the market.

In developed markets, credit-bureaus already exist, generating scores for financial institutions which are used to make credit-risk decisions based on historical repayment behaviour. But there is suddenly an unprecedented spike in unemployment - we’re seeing upwards of 20 million people in the US alone and the numbers are climbing - and that’s the same in many countries.

We’re in an interesting dynamic now. Lockdowns are having a real impact on consumer income and we could be in a place where we see a ‘black-hole’ as it relates to credit-scores.

There is a massive change in the market. People’s lives have changed, very unexpectedly. And, sooner or later, we are going to see a spike in defaults. And at a certain point, this unexpected event will damage traditional credit-risk scores.

When the economy does start to restart, and when the governments do start encouraging banks to lend again, they will go to the credit bureau to ask for credit-scores on borrowers, and they are going to get a lot of challenging results.

At LenddoEFL, we do believe that this pandemic will see a lot of financial institutions push towards new digital solutions. Banks have been encouraging their users for some time to embrace digital solutions, online banking. Well now those branches are closed and people are picking up online banking in a way they haven’t before. And that’s a positive thing.

We think there will now be an increased reliance on using new sources of data; such as social data, mobile phone data, psychometric data etc. These data sets are going to be increasingly important in predicting someone's repayment behaviour following this anomaly of significant default that is coming.

In a developed market, someone who had a perfect credit score might soon have a 3 month gap.

Additionally, in these western markets, where governments are providing relief, there is the possibility they are ‘kicking the can down the road’ and consumers are going to be faced with some type of ‘balloon payment’ in the coming months which could be insurmountable.

In an emerging market, we look at people who have no credit score, and LenddoEFL solutions can generate a score for them.

At LenddoEFL, one of the things we do is, we look at behavioural science. We look at the behaviour of the individual at a snapshot in time - now - and use that behavior to predict the repayment of an individual. We look at thousands of data points from different sources to bring out significant information that historical repayment data doesn’t show.

The pandemic is creating a great opportunity for emerging economies to take a step forward. There is going to be capital available to be deployed. At LenddoEFL, we have seen that in emerging markets there is a greater acceptance of these types of new solutions. Emerging markets have the opportunity to push harder and faster to get out of this.”

Photo by Gabe Pierce on Unsplash

How psychometric testing is making sanitation accessible in Ghana

“Would you rather have $1,000 now or $2,000 in 6 months?”  These are the kinds of questions Sama Sama asks when deciding who should receive a payment plan for a new toilet.

LenddoEFL is partnering with iDE Ghana to deliver a mobile-based credit risk model for assessing loan worthiness. The financial survey employs a psychometrics-based predictive model based on research that has shown it is possible to assess credit-worthiness based on a series of questions.

The results of the survey are used by iDE’s Sama Sama Social Enterprise to approve applicants for a line of credit which allows them to purchase a new personal toilet for their household. 

iDE is a global NGO with a mission to create income and livelihood opportunities for poor rural households. They have been working in Ghana since 2010. Sanitation is an ongoing challenge in Ghana. According to Unicef, “As at 2015, only one rural household out of ten were using improved household toilets”

Before partnering with Lenddo EFL, iDE Ghana was using a paper application, which was time-consuming and costly for both the application and processing. By using LenddoEFL’s score instead, iDE reduced it’s turnaround time from 2 weeks to 2 days. This enabled iDE to process more customers and reduce its cost of acquisition and increased it’s loan portfolio significantly as a result - All this while keeping the NPL% at the same level. 

The psychometric testing has been created to meet Ghana-specific market needs. It takes around 30 mins to complete on an Android device. Applicants work their way through a series of questions which assess their credit-worthiness based on factors such as fiscal responsibility, understanding the time value of money, and their internalized norms.

By helping iDE Sama Sama to reduce the acquisition cost and grow their loan portfolio, our partnership has helped to make more affordable toilets available to Ghanians who need them. 

In the words of Sama Sama,

“This will make the unproven market a bit more proven, spur further finance innovation in the development sector, and get more important products and services to the underserved.”

Photo by Virgyl Sowah on Unsplash

LenddoEFL joins the FinTech Fast 101 list

IDC Financial Insights has released the 2020 update of its FinTech Fast 101 research which details a list of fast-growing FinTechs in Asia/Pacific.

LenddoEFL welcomes its inclusion on the list. IDC’s FinTech Fast 101 research refers to fast-growing fintech players based on extensive on-ground analysis of fintech players from China, India, Indonesia, Singapore, Hong Kong, Thailand, Malaysia, the Philippines, Vietnam, South Korea, and Australia. IDC Financial Insights Asia/Pacific applied its Triple U framework – ubiquity, utility, and usability – to determine this year’s FinTech 101 list. The framework evaluates fintech data across the following key metrics: addressable market, customer adoption, investments, alliances and partnerships, innovation, chance of survival, and marketing.

FintechNews.Sg | RCBC Embarks on Digital KYC with LenddoEFL to Onboard Millions of Unbanked Filipinos

Originally posted on fintechnews.sg

PHILIPPINES (Fintechnews) October 22, 2019 – Rizal Commercial Banking Corporation (RCBC) has sealed a partnership with LenddoEFL for faster and more convenient financial account opening for Filipinos through an end-to-end digital verification and authentication solution.  To date, Know Your Customer (KYC) processes have always required a face-to-face or real-time online interview to onboard bank customers.

“With digital KYC, consumers, particularly those who are unbanked, can open deposit accounts, apply for loans online, take out new insurance policies, do money transfers, and pay more than 2,000 billers through RCBC’s DiskarTech virtual bank in less than five minutes, anytime, anywhere. This is simply commoditizing customer convenience in an era when consumers prefer to interact through online channels,” said executive vice president and chief innovation and inclusion officer Lito Villanueva.

Government regulator Bangko Sentral ng Pilipinas (BSP) has been at the forefront in championing inclusive digital finance and digitalization through emerging regulations leveraging on technology. “Overcoming the barriers to digital connectivity will not only promote accessibility to digital financial products, but will allow innovators to improve the design, enhance security features, and drive down the cost of financial services,” in a speech delivered by BSP Governor Benjamin Diokno at the recent 2019 Financial Executives (FINEX) conference.

“This is a game-changer as we continue to adopt alternative digital verification to help push for a more secure, faster and reliable verification process to onboard more unbanked and underserved segments into the financial system, supporting BSP's mission of financial inclusion,” said Judith Dumapay, APAC Sales Director Philippines, LenddoEFL.

Based on the 2017 Financial Inclusion Survey, only 23% of Filipino adults have a formal account. Only 48% of adults save, but 7 in 10 savers keep their savings at home. Of the 22% of Filipino adults who avail loans, 4 in 10 do so through informal sources.

Replicating Psychometric Profiles Through Mobile Phone Data to Assess Credit Risk Abstract

The big mass of financially underserved individuals across the globe is receiving increasingly considerable attention and led to the development of innovative solutions allowing people to use their digital profiles and personality traits to increase their financial options. On one hand, individuals with little to no credit history are empowered to choose if and when to use their own digital data to access the financial services they need. On the other hand, financial institutions across emerging markets are able to predict risk using non-traditional data sources to maximize approvals, reduce risk and, finally, improve access to financial services. However, not all alternative data sources are obtainable for every market, and historical credit repayment information is not always available to facilitate the training or recalibration of credit risk models fed by a particular data source. 

The replication of psychometric profiles through mobile phone data shared by credit applicants enables credit risk assessment through either a psychometric or a mobile profile, alternatively without the constraint of repayment information availability, given the existence of loan performance data collected for any of these data sources for the same market. Using clustering techniques, well defined psychometric profiles are derived for individuals for whom loans were disbursed in Mexico, each associated with different credit risk levels. Afterwards, personality traits associated with these profiles, such as impulsiveness or extroversion, are replicated through phone usage data related to installed mobile applications, calendar events, call logs and phone contacts. Finally, psychometric clusters are rebuilt based on mobile phone traits. Risk sorting power of these traits is validated through loan repayment information available for a different group of credit risk applications in Mexico for whom Android data have been collected. 

In this study, it is shown that psychometric and Android data can be used alternatively to predict risk, based on specific personality traits, extending the value of alternative data for credit risk assessment to market with technological or time information access constraints. The research could open the other to a big set of non-explored solutions to keep improving access to credit reducing process friction and increasing user adoption. 

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South China Morning Post | Technology guides RCBC Bankard’s strategy for new clients

Originally posted on South China Morning.

Country Business Reports interviews and articles by Discovery Reports www.discoveryreports.com

More than an alternative payment method for cash, credit cards today function more as a multi-purpose card as many institutions incorporate incentives such as airline miles, dining credits, discounts and more. Understanding how credit cards need to be more relevant and more integrated to the lifestyles of users, RCBC Bankard is dedicated to developing cards that address their requirements.

Specialising in lending and payments facilitation, RCBC Bankard, the credit card arm of Rizal Commercial Banking Corp (RCBC), is among the fastest-growing credit card brands in the Philippines. It steadily built its technological knowledge and capabilities to rapidly bring to market a curated portfolio of products and services.

The Philippine market is generally underserved. We want to issue five million credit cards in the Philippines in 10 years

Simon Calasanz, president and CEO

Available under major card association brands Visa, Mastercard, JCB and UnionPay, RCBC Bankard offers 11 co-brand credit cards, including tie-ups with AirAsia, MANGO and Phoenix Petroleum, among others.

“We regularly assess the transaction behaviour of customers to customise our offers for them. We tailor everything according to analytics,” says president and CEO Simon Calasanz.

As more consumers increasingly lead digital lifestyles, RCBC Bankard will be launching a mobile app by the end of this year. It also plans to increase customer touch points through text messaging and online messaging support.

To further advance its technological expertise, RCBC Bankard is actively partnering with financial technology firms to enhance and optimise its operations. In the past few years, RCBC Bankard has been working with Singapore-based fintech LenddoEFL, a market leader in alternative credit scoring and Filipino identity verification solutions, to speed up its digital transformation. RCBC Bankard and LenddoEFL effectively allow new-to-bank applicants to use their digital footprints to unlock access to financial services with the use of cloud-based solutions fully aligned with Bangko Sentral ng Pilipinas requirements.

RCBC Bankard is bullish about becoming among the top credit card companies. “The Philippine market is generally underserved. We want to issue five million credit cards in the Philippines in 10 years,” Calasanz says.

www.rcbcbankard.com

How mobile data improve client engagement

For most people, the smartphone is an essential part of daily life. We carry it around wherever we go, and we spend an inordinate amount of time interacting with it throughout the day. As such, it’s no surprise that the smartphone reveals quite a lot about us. Your phone is a proxy for your personality.

In fact, smartphone data has established itself as an effective data sources for credit scoring. This has been especially valuable for the so-called thin-file segment, where applicants have little or no credit history nor other reliable sources of financial information.

However, as useful as smartphone data has been to the credit industry, there are many other use cases for this data source. In this article, we will explore how smartphone data was used to predict an individual’s need for health insurance. The following data was obtained through an engagement with a large insurer in Southeast Asia, who wanted to determine if their mobile app users that would be responsive to a health insurance offer.

Let’s now see theory in action!

Your phone contacts shows your organizational skills.

How contacts are labeled on a smartphone can be quite telling of your personality. When a new contact is added, there are many details you can fill-in. At a minimum, you have to complete the contact’s name and phone number. However, you can also add a number of other details, such as their email, company, address, and birthday. Having more than just names and phone numbers on your contact list indicate a higher degree of perfectionism and organization. Those traits are represented by those with a high level of awareness and attention, who want to have order and control over all the events of their lives. They plan for their future. That means that they are the ideal customer to offer an insurance product which allow them to minimize potential risks.

The chart below shows the percentage of population split by the percentage of completed contact information that they have in their phones and each group propensity  to acquire an insurance product. If it is considered that population with less than 30% of their contacts information completed as the group with lowest probability to buy, it is possible to affirm that people who complete more than 50% of their contacts’ details are more than 1.5 times likely to buy an insurance product compared to those who belong to the first group.

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Your phone calendar determines your daily schedule and priorities.

How you use your smartphone calendar is another good source of insight. For example, we can see how much time you spend in meetings versus how much time you spend in social events. The habit of scheduling upcoming activities is also an indicator of how organized you are and how well you plan. We have seen that people with these traits, as measured by calendar behavior, are in fact more likely to acquire an insurance product. This is most likely driven by their focus on planning for expected (and unexpected) events.

In the chart below, people were grouped according to the number of calendar events they scheduled.  The chart shows that there is a correlation between an individual’s propensity to buy an insurance product and the number of entries in his/ her phone calendar.

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Your mobile apps show personal interests.

Another interesting data category relates to the types of apps that you have installed on your smartphone. This is particularly insightful since your apps directly correspond to your hobbies, tastes, interests, etc. People who are keen on games usually have a lot of gaming apps installed. People who are interested in finance have apps related to banking, investments, and even blockchain. If someone has many apps related to sports, health, and healthy lifestyle, that person is likely to be someone who takes good care of himself and is a good prospect for an insurance product.

Going back to our insurance use case, the plot below shows that people with health apps installed are 30% more likely to respond to the insurance offer compared to someone without health apps.

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Statistics is the data not your personal information.

We should clarify that companies that use smartphone data are just interested in statistics and the insights you can infer from them. They are not interested in knowing the phone numbers of your family and friends nor the details of your mailing address. The focus is on statistics, predictions, and associations, as they are generated by complex machine learning algorithms. 

As a final note, mobile data should be used as a tool to reach more individuals in need of financial services while further enriching insights on clients, to be able to provide the appropriate products. Financial inclusion is lagging behind digital inclusion, where 1.7 billion individuals and SMEs are still unbanked while registered unique mobile subscribers is already at 5.1 billion. LenddoEFL has been working with mobile data as basis of scoring and predictive analytics for ten years. We have proven and deployed multiple models that help financial institutions with their credit and financial decisioning, at the same time allowing thin-file clients to use their mobile data to access life improving financial services.

Reference:

https://cybersecurityventures.com/how-many-internet-users-will-the-world-have-in-2022-and-in-2030/

https://www.statista.com/statistics/570389/philippines-mobile-phone-user-penetration/

https://www.gsma.com/r/mobileeconomy/

PRWeb.com | Oxfam & LenddoEFL Partner to Help Disaster-Hit Communities, Aligned with BSP Initiatives

A partnership between an international organization and FinTech company that aims to improve financial inclusion and digital finance economy in the Philippines.

LenddoEFL CEO Paolo Montessori (left) and Oxfam Philippines Country Director Maria Rosario Felizco (right) during a meeting with BSP Deputy Governor Chuchi Fonacier (center) on June 6, 2019.

MANILA, PHILIPPINES (PRWEB) JUNE 06, 2019

A financial technology innovation will help more people from remote communities affected by disasters get faster and more convenient access to financial services.

The innovation is the result of a partnership between international development organization Oxfam, together with a licensed financial institution, and software company LenddoEFL, which aims to give financial inclusion support “to the poor, underserved, and unbanked” in line with the initiatives of the Bangko Sentral ng Pilipinas (BSP).

Oxfam in the Philippines Country Director Maria Rosario Felizco expressed optimism that this partnership would not only provide more efficient registration disaster-affected populations and ensure financial inclusion, but also help boost local economies by increasing access to financial services such as micro-credit and weather-based insurance.

“We have seen how the innovative use of digital cash technologies has transformed the lives of Filipinos, particularly women from marginalized communities. In contributing to their economic empowerment, we also amplify efforts in fighting poverty and increasing resilience in the face of disasters and conflicts,” Felizco said.

At least 1,000 farmers from Cagayan province who were affected by Typhoon Ompong in 2018 have benefited from the electronic Know Your Customer (eKYC) product, which is an alternative digital verification process to register unbanked and unserved people.

This means the registered farmers may now be able to access a wide-range of financial services, including savings accounts and loans from Philippine financial institutions, in line with regulations of the Bangko Sentral ng Pilipinas (BSP)

At least 1,000 farmers from Cagayan province who were affected by Typhoon Ompong in 2018 have benefited from the electronic Know Your Customer (eKYC) product, which is an alternative digital verification process to register unbanked and unserved people.

This means the registered farmers may now be able to access a wide-range of financial services, including savings accounts and loans from Philippine financial institutions, in line with regulations of the Bangko Sentral ng Pilipinas (BSP).

Currently, Know Your Customer regulations in the Philippine have always required face-to face or real-time online interviews to register new-to-card or new-to bank current account/savings account customers.

With this innovation, farmers will be verified faster and more conveniently from their mobile phone.

Oxfam Philippines Country Director, Maria Rosario Felizco sharing about their work in Cagayan region.

“With our end-to-end fully digital verification solution, we are able to prevent fraud, ensure Oxfam aligns with Bangko Sentral requirements and quickly and efficiently onboard beneficiaries at scale” said Paolo Montessori, CEO of LenddoEFL.

He added, “We are proud to partner with Oxfam and help Filipino communities that need urgent financial support. Providing a solution to help disaster-stricken Filipino communities get access to financial services at a lower cost, faster and more conveniently is a step further to LenddoEFL’s mission of financial inclusion.”

Data from BSP’s latest Financial Inclusion Survey show that 52.8 million, or 77.4 percent of adult Filipinos, remain unbanked. Of these, 60 percent cited not having enough money as a reason, while 18-percent of the respondents said they do not have the documents required to open an account.

The innovation will also aim to support communities frequented by typhoons in Eastern Samar, and those displaced by the armed conflict in Maguindanao, where Oxfam and its local partners currently implement humanitarian responses.

The initiative builds on the lessons learned from previous humanitarian cash transfer programs during Super Typhoon Yolanda and the Marawi crisis, which pioneered affordable digital financial services for poor communities in the Philippines.

Originally posted on PRWeb.com

Lendit.com | LenddoEFL one of Lendit Fintech Industry Award Finalist 2019

LenddoEFL is one of the finalists of Lendit Fintech 2019’s Excellence in Financial Inclusion award.

To see the complete list, go to Lendit website.

FintechNews.SG | 12 Companies Score SG$1.2 Mil at The Singapore Fintech Awards 2018

The Monetary Authority of Singapore (MAS) and The Association of Banks in Singapore (ABS) today awarded 12 FinTech companies a total of SG$1.2 million divided for 12 different companies at the Fintech Awards, which took place at the third Singapore FinTech Festival.

This time around, the awards featured a greater ASEAN representation, with a focus on financial inclusion,  spanning different business areas like credit-scoring, mobile security, anti-money laundering, and digital investment. The Fintech Awards, supported by PwC, recognises innovative FinTech solutions that have been implemented by FinTech companies, financial institutions and technology companies.

This year, 40 finalists were shortlisted from more than 280 global submissions including the companies who participated in the ASEAN PitchFest6. The winners were selected by a panel of 17 judges who represent a cross-section of international and local experts from the private and public sectors. The entries were evaluated based on four criteria: impact, practicality, interoperability, and uniqueness and creativity.

The panel of judges includes representatives from Accenture Technology, Allianz, AMTD Group, Credit Ease, DBS, Deloitte, GIC, Grammen Foundation India, HSBC, Insignia Venture Partners, Jungle Ventures, Mastercard, The Boston Consulting Group, The Disruptive Group, True Global Ventures, UOB and Vertex Ventures.

ASEAN Open Award

Top 3

First Place: LenddoEFL (Philippines)

The company wants to provide people access to powerful financial products without exorbitant costs, quickly and more conveniently by using AI and advanced analytics to bring together digital and behavioural data. This helps lenders serve the underbanked. LenddoEFL has provided credit scoring, verification and insights to 50+ financial institutions, serving over 7 million people.

To continue reading, click here.

MAS.gov.sg | Twelve innovative FinTech solutions recognised at the 2018 FinTech Awards

Singapore, 14 November 2018… The Monetary Authority of Singapore (MAS) and The Association of Banks in Singapore (ABS) today awarded 12 FinTech companies a total of S$1.2 million at the FinTech Awards, which took place at the third Singapore FinTech Festival.

ASEAN Open Award

1st place – LenddoEFL (Philippines)

2nd place – SQREEM Technologies (Singapore) 

3rd place – Finantix Asia Pacific (Singapore) 

ASEAN SME Award

1st place – FinAccel Teknologi (Indonesia)

2nd place – Katipult (Thailand)

3rd place – MoneyMatch Transfer (Malaysia)

Singapore Founder Award

1st place – CCRManager

2nd place – Cynopsis Solutions

3rd place – Thin Margin

Global Award

1st place – Everspin (South Korea) 

2nd place – Naffa Innovations (India)

3rd place – Keychain (Japan)