he 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.
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
1st place – Everspin (South Korea)
2nd place – Naffa Innovations (India)
3rd place – Keychain (Japan)
Written by Rodrigo Sanabria, Director Partner Success, Latin America
On a prior post by Carlos del Carpio (“The Economics of Credit Scoring”), we discussed the business considerations to assess the merit of a risk model. In this post, I will address how a good origination model impacts the bottom line of a company’s P&L.
These principles may be adapted to look into other types of models used at later stages of a loan life, but on this post we will only address loan origination.
From a business point of view, an origination model is a tool that helps us aim at the “sweet spot”: where we maximize profits. A simple way to think about it is as a trade-off between the cost of acquisition (per loan disbursed) and cost of defaults (provisions, write-offs): The higher the approval rate, the lower the cost of acquisition, but the number of defaults go up.
How do we go about finding the sweet spot? I’ll try to explain it below.
A good model has a good Gini. A “USEFUL” model creates a steep probability of default (also known as PD) curve – we usually refer to it as a “risk split”.
Figure 1 shows the performance of a model based on psychometric information used by an MFI. The Gini (not shown in the graphic) is pretty good (0.28). The risk split is great: the people in the lower 20% of the score ranking are about 9 times more likely to default than those in the top 20%.
Knowing the probability of default for a given group, we may set a credit policy. Basically, we need to answer: “what would the default look like given an acceptance rate?”
We have re-plotted the same data in Figure 2, but now we express the probability of default in accumulated terms. Basically, the graph shows that if we were to accept 80% of this population sample, we would have a 4.5% PD, but if we were to accept 40%, the PD would go down 2 points to 2.5%.
Now, from a business point of view, we still do not have enough information to decide. Do we?
Where would the profit be maximized?
The total cost of customer acquisition is mainly fixed. Whatever we spend on marketing and sales to attract this population, will not change if we reject more or fewer applicants. So, the cost per loan disbursed would grow as we reduce the acceptance rate.
Of course, the higher the acceptance rate, the larger the portfolio, and the more interest revenue we get. BUT, the higher the provisions and write-offs. The combination of these 2 variables (cost of acquisition and net interest income) produces an inverted U-shaped curve that uncovers the “sweet spot”
The current credit policy is yielding a profit at 100% acceptance rate (see Figure 3) because the sample being analyzed corresponds to all the customers that were accepted (i.e. we have repayment data about them). So, the portfolio is profitable.
But the sweet spot seems to be shy of 60% acceptance rate. If this FI were to cut down its approval rate to that level, profits would increase by about a third, and its return on portfolio value would almost double. Of course, there are other considerations around market share and capital adequacy that may play a role in such a strategic decision, but the opportunity is clearly uncovered by the model.
In my experience, the sweet spot usually lies within 30%-70% acceptance rates, driven by marketing expenditures, interest rates, cost of capital, sales channels, and regulation.
What if the shape of the curve shows a continuous positive growth? The sweet spot is at a 100% acceptance rate! – have we reached risk karma? – Most likely, the answer is no (but almost!).
Most likely, we are leaving money on the table. Some business rule may be filtering people before they are scored. I have experienced this situation while working with lenders. For example, a traditional bank was filtering out all SMEs that had been operating for less than X years. This bias in the population was creating a great portfolio from a PD point of view, but there was clearly an opportunity to include younger businesses. As you can see in Figure 4, the maximum return on the portfolio was achieved at 60% approval rate, but they could increase profits by approving beyond the current acceptance rate. Depending on their cost of capital, it may be a good idea to expand the portfolio by approving more people.
In summary, think of your origination model as a business tool. Don’t stop at looking at Gini to assess a model’s merit. Understand how your profitability would be impacted by changes in your acceptance rate. If the PD curve is steep enough, you may capture quite a lot of value by applying the model to either reduce or increase your acceptance rate.
Originally posted on Lodex website.
Technology and data advancement is rapidly providing us with tools for greater and data-driven insights. We are looking at new ways to solve old, longstanding problems.
LenddoEFL is a fantastic example. Through data and tech, LenddoEFL provide financial service providers, all around the world, an alternative tool to help measure a consumer's creditworthiness.
We know that blockchain technology walks hand in hand with disruption and innovation, therefore, we wanted to hear what the pioneers at LenddoEFL's thought on this hot-topic.
We had a chat with Jeff Stewart, LenddoEFL's Co-Founder & Chairman, who shared some of his insights into the use of blockchain for companies and how it can impact consumers. Check it out!
"The new innovations are opening up the possibility of consumers having more control over who sees what information when and being able to track who has seen it."
1. How do you see Blockchain Technology supporting LenddoEFL’s business?
At LenddoEFL, we are convinced that blockchain is one of the most innovative technologies since the public internet. We are also convinced it opens up opportunities for further providing access to financial services, cheaper and more conveniently. Since we started LenddoEFL in 2011, we have been continually innovating, anticipating the future and exploring new and upcoming technology solutions, and blockchain is one of these.
We have already successfully deployed our solution in the Ethereum blockchain ecosystem, where we are able to seamlessly provide our services and automate decisioning in smart contracts. As distributed ledger technology is further developed to reduce friction across the customer lifecycle, we believe we can further help lenders make better decisions and extend financial services to the unbanked. Blockchains, smart contracts and new cryptographic distributed architectures will allow us to do this faster and with less friction.
2. Will Blockchain be helpful or a hindrance for consumers owning their own data? How do you see the help or hindrance affecting the consumer?
It is too early to say for sure, but the technology is evolving very quickly. The new innovations are opening up the possibility of consumers having more control over who sees what information when and being able to track who has seen it.
One critical part to remember is that although the Zero Knowledge Proof offers exciting opportunities, consumers face similar challenges that exist today with regard to understanding what data is being put on the blockchain. If a third party uses the blockchain thoughtfully, they will not include any personally identifiable information (PII), but rather just identifiers. This means that the consumer still has the right to be forgotten, and maintains the ability to control and delete their data.
On the other hand, if a third party puts your data or your PII directly on the blockchain, it is permanent and unalterable and potentially accessible to anyone. This is absolutely unacceptable in our view, and problematic for consumers.
With the rise of GDPR protecting European consumers’ data, the Facebook scandal, and at the same time PSD2 putting the consumer in charge of their financial data and allowing it to be shared, it will be interesting to see how the blockchain can facilitate better control and ability to share when so desired.
Jeff Stewart, LenddoEFL's Co-Founder & Chairman
3. Are there any projects that you are working on in the blockchain space that you can share?
We have been researching the blockchain for over 3 years and our team is actively working on a number of exciting projects. It’s too early to share the details but we are keenly interested to be part of the development in the blockchain space and will have more to share in the coming months.
4. How do you see BLOCKLOAN supporting your business in the future?
BLOCKLOAN is a new Banking-as-a-Platform using blockchain technology with a lot of potential for empowering customers with increased financial flexibility. We are excited to help grow the platform through new functions and features linked to identity verification and credit scoring.
By Satoko Omata | 10 July, 2018
TODAY, customers expect more from their banks – who are slow to deliver new products, services, and experiences as a result of their legacy systems and archaic processes.
However, those that truly want to meet and exceed expectations (and snatch up a bigger share of the market), there are a few lessons they can learn from fintechs.
By partnering with fintechs, banks would have access to new services that help deliver better offerings to customers, at cheaper rates.
At the Wild Digital conference on Wednesday, panelists at a discussion observed that of all the industries, those dealing with money-based investments have been the least changed by technology.
The panel featured Richard Eldridge, Co-founder and CEO of Lenddo EFL; Ashley Koh, Senior Vice President and General Manager of Send, Matchmove; Michele Ferrario, Co-Founder and CEO of StashAway; and Gan Pooi Chan (PC), Country Director GoBear.
SINGAPORE (PRWEB) JULY 11, 2018
LenddoEFL, a fintech offering alternative credit scoring and verification solutions in emerging markets, welcomed Jefri Sormin as its new Indonesia Country Director.
“I’m joining LenddoEFL to help give more people access to credit and banking services, and to drive growth in Indonesia,” said Jefri Sormin, Indonesia Country Director, LenddoEFL. “Indonesia is home to 260 million people and the Financial Services Authority (OJK) has aggressive financial inclusion targets. Our solutions can help Indonesia achieve those goals, while helping banks serve more underbanked people with less risk.”
Jefri has over 15 years of experience in banking, including Citibank, General Electric, Sewatama and Orica. As Country Director for Indonesia at LenddoEFL, Jefri will be responsible for bringing the company’s credit scoring, verification and insights products to financial institutions in the country actively helping them to successfully achieve digital transformation.
“Indonesia is poised for continued growth in financial access and services,” said Mark Mackenzie, APAC Managing Director, LenddoEFL. “We are already seeing strong demand from Indonesian financial institutions for innovative ways to responsibly serve more people. I’m confident that Jefri’s leadership and brand-building skills will help us meet the demand in Indonesia.”
LenddoEFL’s mission is to provide 1 billion people access to powerful financial products at a lower cost, faster and more conveniently. 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. To date, LenddoEFL has provided credit scoring, verification and insights products to 50+ financial institutions, serving over 7 million people. Find more information at https://include1billion.com/.
We started LenddoEFL to solve the problem of access to credit in emerging markets, where people find themselves unable to get a loan, and unable to build their credit. This excludes good people from financial services, limiting opportunity for individual livelihoods and economic growth.
We realized that even though people may have limited financial data in a credit bureau, they have plenty of unique data that can be accessed to better understand who they are. For example, we found that analyzing the digital footprint of an individual (with full consent) helps us to get to know them and understand certain traits that relate to creditworthiness and credit risk.
Now, we are working with banks and lenders across 20+ countries to use non-traditional forms data - digital footprint, mobile behavior and psychometric to predict risk, and unlock access.
When we think about financial inclusion, there are really 3 levels, each necessary to get to the next one.
Access comes first: Can you get a credit card or open a savings account? 1.7 billion adults around the world lack an account at a financial institution according to the 2017 Global Findex. Enabling these people to take that first step towards opportunity is foundational.
Price: Often where access is scarce, the first loan can come from a payday lender or other institution at an unbearably high price/interest rate. So the next step to financial inclusion is bringing the price of a loan down to reasonable rates even without historical credit data.
Convenience: Once you have access to credit at a fair price, the third step to financial inclusion is making it convenient to get. Historically, inclusive lending such as microfinance could involve arduous, time consuming processes with multiple in-person visits and copious document collection. We want to make borrowing easier and faster for people while maintaining safety. The beauty of moving from analog loan officer-based processes to machine learning and big data-driven processes like ours is that it becomes faster and easier.
We believe that financial inclusion isn't simply about access to financial products, but about access to fast, affordable, and convenient financial products. Join us on our mission to #Include1Billion people around the world. We are hiring!
KUALA LUMPUR: CTOS Data Systems Sdn Bhd (CTOS), Malaysia’s largest credit reporting agency, has entered into a partnership with LenddoEFL to enable access to financing for Malaysian consumers with little to no credit history.
Both CTOS and LenddoEFL have aided banks, lending instit…
Attempts to calculate the creditworthiness of individuals by AI (artificial intelligence) and to finance using it are expanding. This is called "AI score lending".
The meaning of AI doing loan screening, which is one of the most important tasks of banks, is quite large.
However, the question is whether Japanese financial institutions can handle big data. If it can not do it, it will repeat the failure of the past score lending.
Singapore's Lenddo is a service in emerging countries such as India, Vietnam, Indonesia, which have never had a history of credit.
Read full article
Bangladeshi banker and Nobel laureate Muhammad Yunus (Muhammad Yunus) the promotion of microfinance , is the poor through microcredit loans , so there is money to do a small business to support themselves, and thus get rid of poverty. However, due to the time-consuming and laborious credit evaluation of lenders, the large-scale application of microfinance is difficult to achieve once.
Nowadays, mobile banking comes. It can collect data to help people who have little formal financial records in the traditional sense to broaden their services. Labor costs are also greatly reduced. For example, Kenyan mobile telecommunications operator Safaricom and African Commercial Bank jointly launched the M-Shwari business in 2012, which can determine customers’ credit scores based on Safaricom’s user information and the trading history of its M-PESA mobile money business. Loan amount.
In addition to payment data, mobile phones (especially smart phones) can also provide more types of information for credit evaluation by borrowers . For example, a person's geographic location data can reflect whether he has a stable job and fixed residence; shopping records can even reveal whether the borrower is pregnant ; and the richness of information obtained by social media is not Yu.
The fintech start-up company Lenddo EFL also uses the Internet to conduct psychological tests on potential borrowers. The question concerns the concept of money (for example, choosing to pay $10,000 at a time, or $20,000 for six months), where your money is spent. , Evaluation of living communities, etc., to determine the reliability of testers loan repayment. To date, the company has completed more than 7 million credit assessments, helping consumers with a lack of traditional credit records to borrow 2 billion U.S. dollars from 50 financial institutions of varying sizes.
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
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.
KUALA LUMPUR: CTOS Data Systems Sdn Bhd (CTOS), Malaysia’s largest credit reporting agency, has entered into a partnership with LenddoEFL to enable access to financing for Malaysian consumers with little to no credit history.
Both CTOS and LenddoEFL have aided banks, lending institutions, utility and credit card companies to reduce risk, increase portfolio size, improve customer service and accurately verify applicants. Read full article.
KUALA LUMPUR, Malaysia, and SINGAPORE, CTOS Data Systems Sdn Bhd (CTOS), Malaysia's largest credit reporting agency, has entered into a partnership with LenddoEFL to achieve a joint vision of financial inclusion for Malaysian consumers with little to no credit history. Both fintech leaders have aided banks, lending institutions, utility and credit card companies to reduce risk, increase portfolio size, improve customer service and accurately verify applicants. Read full article.
"The exponential rise in the use of smartphones, mobile wallets and e-payment systems has given birth to a new technology that uses big data to determine credit scores. The technology has been lauded for helping the underbanked gain access to credit, representing the first step towards financial inclusion.
The use of non-traditional data to churn out credit scores is now expanding beyond the underbanked and unbanked to reach even well-banked individuals who already have a credit score. This pool of data, which is used to discover patterns of users’ repayment behaviour based on their mobile phone and social media usage, is playing an increasingly important role in Asia alongside traditional credit scores." Read the full article.
"Microfinance is described by the Financial Times Lexicon as a service where financial institutions will back small start-ups and would-be entrepreneurs with small loans, in the poorest parts of the world. In Southeast Asia, the biggest microfinance players currently include Asia Pacific-based LenddoEFL, Singapore's CredoLab and the Philippines’ Lendr, for example..." Read full article.