The Creditinfo Chronicle
In these troubled times, credit providers are searching for actions to take to protect themselves from the worst of the economic storm. Many different options are available however what is often overlooked is the critical need for having accurate and timely visibility on your loan portfolio. This can be the difference between a defaulted credit contract or a recovery.
The unique situation the world faces is a significant reduction in economic activity occurring at the same time globally. The economic effects of the pandemic likely be severe and it is not an exaggeration to suggest that the Financial Sector faces its greatest challenge perhaps ever, if not then certainly since the 2008 financial crisis.
Credit providers face the twin challenges of worsening repayment performance on existing credits and greater risk in issuing new credit. With unemployment rising and many businesses facing severe financial difficulties, it is to be expected that there will be an imminent and severe impact on the NPLs of lenders.
In large sections of the global economy financial difficulties are already being faced by consumers, entrepreneurs, MSME and Corporates alike. A wave of layoffs is underway in the areas worst affected by the outbreak. As no country is completely working in isolation, the effects are already being felt on a global scale. Creditinfo has already observed in most markets that the number of loans disbursed are decreasing rapidly coupled with a rise in missed due payment, a clear early warning of a forthcoming rise in default levels.
In these troubled times, credit providers are searching for actions to take to protect themselves from the worst of the economic storm. With the enforced closure of bank branches, the movement towards online and application-based banking will undoubtedly be given a boost in the medium to long term. However, the most valuable step that lenders can take immediately is to increase their visibility on the performance of their portfolios.
- Informed decisions on credit risk policies adjustments
- Informed decisions on collections strategies adjustments
- Targeted actions to take place making sure lenders resources are focused in on where it matters most.
- Lenders to receive advanced warnings on changes to their portfolio
Having accurate and timely visibility and can be the difference between a defaulted credit contract or a recovery.
Gaining visibility of your internal credit portfolio performance is relatively straightforward. All successful lenders will have implemented systems to measure and monitor their loan book performance.
However, this can only logically provide part of the overall picture. The part of their client’s overall credit history provided by that lender. What is missing and what is crucial in times of economic stress is the ability to view all market activity of your clients. For if a client is suffering financial distress elsewhere in the market then there is a high probability they will soon exhibit distress with you.
This is where Creditinfo is able to assist you through our Monitoring and Alert solution. A straightforward tool for proactively providing notifications whenever one of your clients records a significant event on their credit file. So, for example, you will learn when your client:
- Misses a repayment elsewhere
- Has overdue amounts throughout the market over a certain level
- Reaches a certain level of credit exposure in the market
- Enquiries for credit elsewhere
- Takes out credit elsewhere
The Monitoring tool can be activated within minutes and will ensure a stream of alerts is sent to your risk team as and when they are generated. Armed with this information lenders can ensure early engagement for at-risk customers and help teams rapidly focus their pre-delinquency efforts. Efforts such as fast-tracking collections actions, preparing payment plans or reducing exposures to that client. With knowledge comes options and the ability to make better decisions.
The mantra saying that “knowledge is power” has never been more true as it enables you to effectively monitor your clients’ performance across the market. This should be the very first step in preparing and defending yourself against the economic downturn.
Ben Riley, Global Consultant at Creditinfo Group
András Horvath, Head of Product Management at Creditinfo Group
Never Has There Been Stronger Evidence for Mobile Loans in West African Economic and Monetary Union region
With many countries in the West African Economic and Monetary Union (WAEMU) region in lockdown, bank branches empty and movement constrained; the case for a true, robust mobile lending ecosystem is stronger than ever. In global markets where mobile lending is nascent or inexistent, and the credit market is relegated to physical interaction between underwriter and customer, physical confinement and countrywide lockdowns are the equivalent of death sentences. Credit markets are frozen because critical communication is impossible. On the other hand, where digital wallets and e-money are common, no such barriers exist.
In the WAEMU region, many initiatives are already in place. MoMo Kash, a mobile money solution by MTN in Côte d’Ivoire has over 5.000.000 subscribers and specifically targets ‘financially vulnerable’ segments of the population. It has a similar structure in Benin. Orange Bank will launch in Côte d’Ivoire this year. Other solutions such as Moov show that the seeds have been planted and are ready to grow. Growth has been incentivized by ‘healthy’ competition and a well-designed regulatory environment. In addition to mobile lending, successes such as Creditinfo Kenya underscore the importance of having a strong and functioning Credit Bureau platform to prevent over lending from responsible lenders, as well as its complementarity with a vibrant e-money ecosystem. While Côte d’Ivoire leads the way, it is high time for the rest of West Africa to embrace such transformative solutions.
Nevertheless, while there are many positives, there are still key steps to be taken. One fundamental obstacle that needs to be removed is the difficulty of obtaining customer consent digitally or online. Comprehensive digital onboarding is important in normal times but critical in a crisis. It enables rural communities far from bank branches to take advantage of access to finance. It also prevents overcrowding at bank branches for small, short term loans that would otherwise be financially unviable for banks. It reduces the costs, errors, and subjectivity that were once structural components of human underwriting. In a crisis like this, with people stuck at home, digital onboarding and disbursement can be completed in a few clicks, pumping ‘real’ money into the economy, keeping families afloat, and allowing bills to be paid. None of this is possible if a sole trader must physically sign a form at a bank branch far from his home. Therefore, digital consent is the crucial next step in transforming the lending industry. This must be coupled with a mandatory bureau inquiry for mobile loans, to avoid the phenomenon of high default rates observed so far. To this end, Creditinfo have planned to launch a mobile score which will be ideally suited for risk analysis. The technology and infrastructure are not only a commercial, but an economic imperative as well, and there is a need for a revolution in the region.
Global Consultant at Creditinfo Group
With the stock markets falling and unemployment increasing as a likely outcome of the current virus-led situation, it is important for credit providers to start thinking about management of their portfolios. List of areas to review ranges from collections management, payment holidays to anti-fraud policies. The immediate focus should be on C.A.L.M (Cut-off Analysis and Limit Management). This article provides initial guidelines for those wanting to STAY C.A.L.M.
Rank Ordering and Probability of Default Calibration
When reviewing evidence from last recession (in line with what was shown in previous recessions such as UK mortgage crisis in 1990), it is clear that to a large extent, credit scorecards retained their ability to rank order credit risk. This means that scorecards continued to rank from the highest risk at the lowest scores to the lowest risk at the highest scores. This is because many scores are dynamic and they adjust as typical risk profile changes. Credit Bureau scorecards built on payment data and enquires are a prime example of this, as average Credit Bureau score slumps during a recession due to a worsening of Credit Bureau data.
Well-thought-out scorecards continue to rank ordering risk during a crisis or recession. What does change is a calibration between scores and the probability of default (PD). Evidence from past recessions suggests that at each score, observed bad rates (BR) tended to surpass initially predicted PD. As an example, let’s imagine that a cut-off is set at a certain score, let’s say, 610 and we expect PD to be equal to 13% at the cut-off point. However, during a recession observed BR will increase to a higher value, perhaps 15% depending on the depth of the crisis.
It is, therefore, necessary to change the cut-off to a higher value to retain the quality of the portfolio. Further analysis and modelling can help to produce a detailed estimate of the impact of key economic factors on levels of default to safeguard the portfolio from significant losses.
RECOMMENDATION: REVIEW YOUR CUT-OFF SCORE
Loss Given Default and Reducing Exposure
We all hope that the impact of the virus crisis will be relatively short-lived and then expect a return to normality. One of the major learning points from the previous sub-prime mortgage crisis was that both PD and Loss Given Default (LGD) estimates were impacted in a recession. The deterioration of LGD was overlooked, as there was a repeated belief that sub-prime mortgages carried a low risk due to a high value of a housing asset even despite potentially high PD. This falsehood was laid bare when asset prices tumbled in line with rising defaults.
Reviewing how limits are assigned is an important step. This will have a dual benefit of making payments more manageable in an environment where incomes are vulnerable to reductions, and secondarily to reduce losses if defaults increase.The considered strategy of risk-driven exposure reduction will minimize any spikes in losses from the current portfolio and any new loans in the coming weeks and months.
RECOMMENDATION: REVIEW YOUR LIMIT MANAGEMENT
Creditinfo will be using their data resources in each country to monitor the situation and identify any trends which will support the management of credit portfolios in each country. Each lender needs to continue to review portfolios and assess what changes are needed to best manage through this difficult period.
More questions? Get in touch: firstname.lastname@example.org
Íslandsbanki – one of Iceland’s three largest banks – launches new self-service affordability calculator and loan application system developed in collaboration with Creditinfo.
Íslandsbanki is a leader in financial services in Iceland. A universal bank with roots tracing back to 1875. The Bank offers comprehensive financial services to households, corporations, and professional investors in Iceland. It has a strong market share across all domestic franchise areas (Retail Banking, Corporate Banking, Capital Markets, and Wealth Management) and a 25% – 50% market share across all local industry segments.
With a team of 800 employees and a vision of being #1 for service, Íslandsbanki prides itself on being ranked first among banks in the Icelandic Customer Satisfaction Index for six out of seven years. The Bank was voted ‘Best Bank in Iceland’ by Euromoney four years in a row (2013- 2016) by the anker (2014, 2016 & 2017) and ‘Best Investment Bank in Iceland’ by Euromoney (2014).
Íslandsbanki customers can now apply for a mortgage, complete the affordability calculations and application process online, and get results from the affordability calculations in real-time. If followed up with a loan application, they also get confirmation within the day. This very same process would take up to two to three weeks before.
The affordability calculator works for multiple loan types (mortgage, car leasing, and other consumer lending). There is also a new feature for up to three unrelated individuals to apply for a mortgage together. This feature will make it easier for friends, unmarried/unregistered couples, parents, and their children to buy together and thus serves to simplify the buying process for first time buyers.
Creditinfo’s role in the process has been to develop the affordability calculations in collaboration with Íslandsbanki. The Bank connects to Creditinfo’s API but developed the front-end and user interface themselves. Creditinfo data sources used in the calculations can be seen below:
“This is an important step in our strategic partnership with Íslandsbanki. The implementation has been very successful, and we look forward to contributing to their clients improved journey,” says Dagný Dögg Franklínsdóttir, Head of Sales at Creditinfo Iceland.
“This process has so far been more or less manual so there has been a lot of waiting around for our customers, but now we have a fully automatic payment assessment,” says Linda Lyngmo, Project manager of digital solutions at Íslandsbanki. “Now everyone can apply for a credit assessment for mortgages, car loans or other loans on the Íslandsbanki website and get an answer about their payment capacity right away.”
Retail lending in Kenya has taken a unique path. It has skipped some stages typical for developed markets and climbed to heights that can be admired and envied. Ironically, this happened not due to economical advantages but rather due to certain historical deficiencies. As it happens in many developing markets at some point lots of people move from rural areas to big cities seeking better-payed jobs. These people as they earned money needed some way to transfer it to their families, often left in the villages. Most of these people didn’t have a banking account as banks were avoiding such customers, viewing them as high risk/low profit. In such circumstances a person wishing to transfer money to his family would have to find a bus driver, going to his home village, and ask him to carry cash to his family. Not the most fast, convenient and secure way to commit a financial transaction.
In 2007 Safaricom, a Kenyan telecom company addressed this problem by launching MPESA – mobile wallet linked to user’s phone number. A user could send money to another person over network who could then withdraw funds from the system through an agent. The agents were either Safaricom’s employees or shopkeepers who partnered with Safaricom besides of doing their primary business. With 93% of population coverage by mobile (Safaricom’s Annual Report 2019) and ubiquitous agents network the problem of money transfers was solved. People started to use MPESA to transact with each other, and also with businesses and government agencies. Since 2007 mobile money has rapidly proliferated in the developing world and today there are more than 500 MLN users in at least 90 countries (GSMA 2016a).
Besides solving money transfer problem MPESA has propelled the development of retail lending. Millions of people that hadn’t had access to finance suddenly entered the financial system. They sent money to each other, payed bills and purchased goods through mobile wallet. Whereas many people in Kenya are not officially employed (according to the National Bureau of Statistics informal sector represents 82,7% of employment) this data is the only reliable footprint of their financial activity.
Mobile lending has become a critical growth driver of lending market. A typical mobile lender is a financial institution partnering with mobile operator (e.g. Commercial Bank of Africa partnered with Safaricom and launched their M-Shwari product in 2012). A credit application is submitted through mobile phone (app or USSD interface) and remotely processed by Lender. In case of positive decision money are funded on person’s mobile wallet. Mobile wallet is also used to make regular loan payments. Such purely digital approach has obvious benefits. Since loan is disbursed remotely Lender doesn’t have to extend sales network, keeping operational costs low. The disbursement is made immediately without need to visit bank’s office which improved customer experience and boosted growth. The weak sides of such approach are limited KYC (which is basically delegated to a telecom company) and weak collection (in most cases customers are out of physical reach of Lender). This results in higher than usual NPL rate which is compensated by higher interest rate (or service charge).
At the dawn of mobile lending credit limits were relatively small, starting from 500 KSH (5 USD). Now, banks are ready to provide 50,000 KSH (500 USD) and even higher amounts which is on par with traditional unsecured loan. This has become possible due to building up of good customer base and advanced scoring mechanisms that rely on a vast array of data, both traditional (e.g. credit bureau) and non-traditional (e.g. phone meta-data, mobile wallet). Non-traditional data proved to be useful for assessing customers without previous credit history (64% according to The World Bank). Data sources include calls journal, installed apps, sms and other. Most of such data is not linked to credit behavior but some subtle items matter a lot. For example, Creditinfo has conducted research that showed that customers who have installed UBER app are more reliable than those without. Gambling apps on the other hand indicate higher risk. Another research showed that people who have certain government agencies in their phone book are less risky than the rest.
In the domain of non-traditional data mobile wallet proved to be the most powerful resource. Data on financial transactions is used to estimate customer’s income and to assign credit limit. A person that is regularly paying 5,000 KSH bill is likely to have enough income to serve 10,000 KSH loan given for three months. Of course, different people have different financial behavior so designing limit assignment system is not a straightforward exercise and requires solid analytical work. The advanced approach recommended by Creditinfo’s consultants combines specific MPESA variables with an internal/CRB score breaking down population by customer segments (e.g. Prime/Sub-prime). Higher limits are provided to low risk/high income customers which leads to increased profitability and reduces risk exposure. A good limit assignment system will also consider length of relation with customer and his borrowing activity. New customers will typically get smaller amounts than those who have already repaid several loans. This strengthens customer relations and helps building up good customer base. Implementation of such advanced approach requires besides of heavy analytical work availability of proper automation tools that support not only scorecard calculations but also complicated decision matrices varying by customer segments. Furthermore, as every analytical model limit assignment model requires regular reviews and fine-tuning. We need to monitor stability of financial behavior patterns and alignment of limit size with level of risk. It becomes possible only if historical decision data is properly stored and maintained, and can be easily linked to customer’s payment behavior.
We are yet to observe what will happen to lending market in Kenya. Recently the growth has slowed down which might indicate a tipping point in the credit cycle, followed by a decline and growth of NPL. Still the lessons learned are insightful and can be utilized in other developing markets.
National Commercial Bank of Jamaica veteran joins Creditinfo team to help credit providers embrace digitalisation and boost financial inclusion.
Creditinfo Group, the leading global credit information and decision analytics solutions provider, today announced that it has appointed John Matthew Sinclair as the CEO of its Jamaican credit bureau. In this role, Sinclair will continue the significant work conducted by Creditinfo in the country, with the vision of helping credit providers to embrace technology and unlock access to more financial services for citizens and businesses.
Sinclair joined the Creditinfo Jamaica team in January 2020, following senior positions held at the Bank of Jamaica, and, more recently, the National Commercial Bank of Jamaica, where he was responsible for digital transformation across the organisation. His broad and unique experience in financial services, working for one of the most forward-looking banks and also experience on the regulatory part of banking, will play a crucial role in his new remit as CEO of Creditinfo Jamaica.
This strategic hire by Creditinfo will see Sinclair responsible for leading the charge in educating the Jamaican market on the importance of intelligent business solutions; broadening the usage of financial and non-financial data as instruments for credit providers; and providing best-in-breed risk management consultancy and automation solutions that help the industry make better financial decisions. Sinclair will lean on his experience driving and executing on digital transformation projects to support regulators in the country with the digitalisation of financial services.
Claudia Garcia, Regional Manager, LATAM & Caribbean, Creditinfo commented on the appointment: “John Matthew brings positive energy, openness, enthusiasm and in-demand skills to the role of CEO of Creditinfo Jamaica. This credit bureau is the oldest entity of our three points of presence in the Caribbean market, but we see huge untapped potential in the country. We’re excited to have John Matthew on board. His digital transformation experience will prove vital in helping to educate on the importance of digitalisation in financial services.”
John Matthew Sinclair, CEO of Creditinfo Jamaica added: “I’ve watched Creditinfo Jamaica from afar, and have been impressed with the way the bureau has built such a secure financial infrastructure in the region, with automation and digitalisation at the heart. As I join the Creditinfo team – a team that has been a key player in financial services innovation – I look forward to being at the forefront of such significant industry change in both Jamaica, and in the Caribbean more widely.”
Sinclair replaces former Creditinfo Jamaica CEO Craig Stephen, who after successfully driving the business through 3 consecutive years of growth will now take the position of COO.
By Dmitry Borodin, Head of Risk Analytics at Creditinfo Group
In societies of Digital Nomads, working from home Millennials, global migrations and emerging economies, lenders are often facing a shortage of relevant data to score and assess a big pool of population. Consequently, lenders are often unable to make decisions on so called ‘thin files’ due to a lack data. Thin file customers then remain excluded from formal finance.
Can Lenders under such circumstances, rely on alternative data such as Psychometrics, payment behavior on previous small loans, Telecom and utility data to gather initial insights on customers and their financial credibility?
Thanks to its global footprint Credintinfo have been able to gather enough data to suggest that Telecom and other alternative data sources, MFI and IL channel can help lenders predict future credit risks of thin file applicants for formal credit.
To an extent we can say that alternative data and the experience with small loans results predictive in the long term. This study presents a number of predictive characteristics from alternative data sources and their impact is evaluated across several Creditinfo markets. Particular attention is paid to Kenya, which has seen an unprecedented growth in mobile money and mobile borrowing.
Findings of Creditinfo suggest that lenders are able to convert short terms loans to traditional credit products, boost decision quality by utilizing alternative data, help customer retentions and facilitate access to banking loans for unbanked thin file individual applicants and small business owners.
Creditinfo Group, the leading global credit information and fintech services provider has today announced that it has signed a long-term strategic partnership agreement with PT PEFINDO Biro Kredit (PBK) to further support financial and non-financial institutions in Indonesia. Using Creditinfo’s knowledge and experience, PBK will enhance its consultancy and analytical services to provide customers with additional value-added risk management solutions and support.
As a global supplier of credit bureaus and credit risk solutions, Creditinfo has been active in Indonesia since 2014, in a partnership with PBK. Established in 2014, PBK is the leading Private Credit Bureau in Indonesia today, serving numerous traditional financial institutions, fintech companies, and other non-traditional institutions. Since becoming operational, PBK has enriched its data coverage, improved its services and is now playing an important role in the operation of its members. The new agreement secures a further five years of collaboration between the two businesses and will focus on the delivery of services to improve financial inclusion in the region.
“We are very excited about our new, strengthened partnership with PBK. Together we have a significant opportunity to increase the level of financial inclusion in Indonesia, a country where the economy is driven by microbusinesses and SMEs,” commented Samuel White, Regional Director, Creditinfo Asia. “In close collaboration with PBK, and supported by its stakeholders, we will introduce new products and services that will help financial institutions to better assess their customers, enhance risk management capabilities and provide better services to the Indonesian market.”
This announcement marks another significant milestone for Creditinfo, which is a world leader in providing intelligent information in mature and emerging markets. Backed by international know-how and local market support, Creditinfo solutions set a high bar wherever they are implemented.
By Stefano Stoppani – CEO, Creditinfo Group
Last month, consumer champions Which? revealed the findings of research into the state of the UK banking sector – with a somewhat bleak conclusion. The top line of the study? A third of all UK bank and building society branches have closed over the last four and half years. Of those that remain on our high streets, opening times have narrowed.
To some, this news might not be so surprising. We’ve already seen the so-called ‘death of the high street’ claim retail victims from all corners of the UK. Mass closures of this kind – whether in retail or banking – are arguably the result of the widespread digitalisation of services. We’ve all been bitten by the convenience bug. As time-poor consumers, we crave access to services and products in the easiest and cheapest way possible – and if this means managing our finances via an app from the comfort of our own homes, rather than brave queues in town centres, then so be it.
Fintech unicorns such as Revolut and Monzo have clearly upped the ante from a banking perspective – these businesses are agile, novel and attractive propositions, particularly to younger generations, in today’s digital age. With no bank branches and a lean infrastructure, the alternative they provide to traditional banks leans into a more digitally-savvy generation who is driving how we consume products and services today. Revolut’s recent partnership news with Visa will also enable the firm to expand to even more countries than it currently serves.
However, with opportunity comes risk. A lack of physical bank branches means that more vulnerable citizens, such as the less digitally- or financially-savvy, and the elderly are without access to crucial financial services. And so, this brings us to the financial inclusion conundrum in developed economies, which continues to be an issue today.
As my colleague Paul Randall outlined in an article for Global Banking and Finance Review last year, according to stats from the World Bank, a whopping 1.7 billion adults across the globe remain ‘unbanked,’ with no bank accounts and no access to formal finance. Most of the unbanked admittedly live in the developing world, in countries such as China, India or Africa. But developed economies are also still struggling to close the gap between banked and unbanked citizens.
While the UK has a good level of financial inclusion, one in four British families is now classed as low-income. What’s more, 13 million of the lowest-income individuals in the UK are financially excluded by mainstream banks and lenders. So how can we close the gap? In the first instance, traditional and established banks need to work alongside fintech ‘disruptors’ to ensure that services are accessible to all in society. This includes facilitating change in the credit lending industry, by helping banks to tap into and use new sources of data that can unlock access to services for the wider unbanked population.
At Creditinfo, we’re doing just that – using our innovative psychometric testing methods to measure the risk of potential customers who may have been overlooked for formal finance in the past, by assessing their core personality. Just like credit bureau data, where millions of raw variables are split into segments such as default, early stage and revolving arrears, or credit card performance, so personality data is split into segments in a similar way. By uniting psychological models with traditional risk analytics, lenders can reduce risk with existing customers and start new relationships with prospective customers, thereby increasing affordable access to financial services products.
Government also has a role to play in supporting more vulnerable citizens in accessing services that are arguably a basic human right today.
In March of this year, the HM Treasury and Department for Work and Pensions released a financial inclusion report that outlined its commitment ‘to building an economy where everyone, regardless of their background or income, can access the financial services and products they need.’ This involves a programme of initiatives, such as the new Single Financial Guidance Body (SFGB), which will ‘develop a long-term national strategy to improve people’s understanding of money, pensions and their ability to manage debt.’
While this is an encouraging step in the right direction, the proof of these initiatives will be in the progress we make together, in closing the financial inclusion gap for the improvement of all citizens’ lives and eradicating poverty as best we can.
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By David Kaufer (Senior research psychologist at Coremetrix)
I used to live in a small town where everyone knew everyone. I don’t live there anymore – not even in the same country or continent. I grew up and moved on, but deep inside I still have a sweet spot for this town because of the memories; memories of the countryside, my primary school, my family, neighbours, playmates, teachers and local merchants.
I used to go to the local grocery shop and take anything – be it an ice-lolly or some shampoo – without needing to pay for it immediately. I would smile at the shop owner and show him what I took. I didn’t even sign his notebook where he registered the items I took. He trusted me (especially my parents) to pay him at the end of the week. In return, they trusted him to accurately record the purchased items. We were very loyal to our local merchants and even when new and bigger shops opened, we kept going to the same shops. We knew each other, trusted each other and want to help each other. There was a special unwritten bond between us.
Many things have changed since then. The town has become a city, I have lost my hair along with the need for shampoo and many of the smaller stores have lost their battle against bigger and stronger retailers that can offer more for less money. Sometimes, it makes me sad to think of the sweet memories from the past, but at other times I enjoy the immense offering that this modern economy has brought. What hasn’t changed since then is the need for mutual trust. Trust from the side of retailers, and service and credit providers to be paid for their offerings and from the side of the customers to get these services and goods at a fair price and interest. From a business perspective, this trust can obviously be translated into income. More good customers, loyal customers, customers who will recommend products to their friends or customers that will buy other products from the same company, just as we did 30 years ago.
We don’t always have the luxury of getting to know each and every customer personally in order to build mutual trust. How can we, as a business, develop and maintain trust when we deal with hundreds of thousands of customers? How can we ensure that our customers feel unique? How can we better understand customer needs and motivations?
Coremetrix’s psychometric profiles are the solution for large-scale companies who really want to understand their customers and recreate this business-to-customer bond. Coremetrix can now help businesses segment their entire portfolio based on personality traits that underlie their customer behaviour and motivation. When intelligently and respectfully used, this knowledge will translate to actions impacting higher retention rates, acquisition of new profitable customers, and creation of effective communication channels and development of new products.
Contact us at: email@example.com
The key to success (my humble opinion): Any lessons from credit-vibrant Iceland to small population countries?
By Reynir Finndal Grétarsson – Founder, Creditinfo Group
In 2010 I decided to go back to University and learn Anthropology. This is the discipline that deals with human behavior in wide and holistic manner. Why do humans behave as they do? After graduating in 2014 with a bachelor’s degree, my understanding of the complex organism that is the modern human being increased just a little bit. The most important thing I learnt was that different behavior of different groups of people could be explained by what we call culture.
This is not saying much. Culture has been defined countless of time. It is a subjective term, but in short it is about what people does and how. Behind that are the motives, knowledge, values, beliefs, etc. I believe that the most important thing for companies, which are one form of groups of people, is its culture. You might point at some of the greatest companies in the world and say that they came about because of great ideas. I would say that the initial ideas were rarely novel, but elaboration (or even plagiarism) of someone else’s ideas. Why did those groups of people succeed and not other groups with similar ideas? Sure, luck plays a role. But luck is also about being prepared when opportunity arrives. Most important is the mindset of the founders and their team in creating a culture of success. And then to add to the team people who fit into that culture.
We started a small company in Iceland in 1997. In 2002 we started expanding to other mainly smaller markets, focusing on those with high growth potential in the long term. We now have offices in 25 countries (last count). Iceland is still the most important part of the company, contributing more in revenues and profits than any other country, yet it is the smallest in population. Why?
It is firstly the culture of the country. Icelanders like new things. To start internet-based service in Iceland in 1997 was easier than in some other European countries many years later. Icelanders are usually in hurry and very demanding. They want things now. Call me biased, but to open a bank account or register a company, as examples, is easier that anywhere else, at least for locals. Iceland has the highest proportion of payments being made electronically. Cash is disappearing. Secondly, the company culture, at the heart of which lies respect and appreciation towards one’s colleagues. You don’t just give orders and expect people top follow; you explain them and are prepared to listen to reasons why things should be done differently. Of course, the boss is the boss, but he/she must be reasonable. This has the effect of improving decision-making. I have often been guided towards a better approach by my colleagues. And knowing that you will be questioned, you avoid asking for things that serve limited purpose. In short, you won’t get away with nonsense. What you ask the people to do has to serve a purpose that is in line with the overall goals of the company.
I recently read the autobiography of General Georgi Zhukov, he mentions officers who do not respect their common soldiers. He says that they are stupid as this results in the soldiers not being ready to fight as hard as they can for their officer.
I think that the reason for the tremendous success of Creditinfo Iceland is the fact that we have been fortunate in finding the right people. Not only good professionals, but also good people who respect their colleagues and in that way are in line with the most important part of the company culture.
We can say that Iceland success can be seen as the result of business intuition & social listening with perfect timing & great professionals blended together.
Last but not least: luck. Iceland was prepared for our services and you never really know beforehand if this is the case. Luck is always a factor in business, although by our professional team adapting our services to meet the changing environment, we have stayed lucky for over 20 years!
Artificial Intelligence (AI) is currently growing at a fast rate, and is becoming a hot subject in the industry globally. Individuals and organizations alike, are now moving towards that direction in order to increase efficiency and maximize on profits while lowering costs for themselves and their businesses.
Creditinfo has worked on an automated machine learning (ML) model generation platform, which delivers impressive levels of automation, and user-friendliness to apply state of the art artificial intelligence algorithms to the finance sector data.
Our pipeline will enable analysts to securely build and deploy highly accurate adaptive machine learning models with very limited human intervention making it a great tool for credit bureaus and financial institutions.
Our ML pipeline requires four easy steps:
– Drag and drop your dataset.
– Choose target variable.
– Build state of the art models; visualize weights of the main predictors.
– Deploy the best model.
The pipeline uses a wide spectrum of algorithms such as logistic regression, K-nearest neighbor, random forests, naive Bayes, stochastic gradient decent, linear SVC, decision trees and gradient boosted trees. The platform mainly focuses on deep learning algorithms and allows to effortlessly deploy them.
For more information on our ML model, please contact Dmitry Borodin (firstname.lastname@example.org)
Afghan Credit Guarantee Foundation partner on first-of-its-kind Credit Risk Scorecard for Afghan SMEs
LONDON, UK, 26th June 2019 – Creditinfo Group, the leading global credit information and fintech services provider, today announced that it has entered into a strategic partnership with ACGF – Afghan Credit Guarantee Foundation to develop a Credit Risk Scorecard aimed at small-to-medium enterprises (SMEs) in Afghanistan. As the first SME credit scorecard to be developed for the Afghan market, the joint solution will not only increase profitable lending to the market, but also provide a host of societal benefits such as great wealth generation and increased employment, as a result of opening up affordable, formal credit to SMEs in the country.
As a global supplier of credit bureaus and credit risk solutions, Creditinfo has been active in Afghanistan since 2013, in partnership with the Central Bank of Afghanistan. ACGF was established in 2014, following a decade of a successful performance by its institutional predecessor Credit Guarantee Facility for Afghanistan. ACGF operates in Afghanistan with the aim of boosting financial inclusion in the Afghan market by providing credit guarantees and Technical Assistance (TA) to financial institutions with the ultimate objective of facilitating SME lending.
ACGF has been at the forefront of driving the Afghan credit industry forward for 15 years. In the challenging economic and political environment of Afghanistan, the organisation utilises its funds effectively to create wide-reaching developmental impact. Since inception ACGF has cumulatively guaranteed USD 219m of loans, supporting 5,500 SMEs. Furthermore, as per the end of 2018 estimations, 45% of all business loans in Afghanistan have been guaranteed by ACGF.
The partnership between Creditinfo and ACGF will see the development of a cutting-edge technique for assessing the credit risk of SMEs granting credit. It will also enable credit providers to extend credit to SMEs who are currently unable to access credit. The solution will be used at the point of application by SMEs for credit, and will enable lenders to make more informed decisions, and extend more credit than is currently possible.
Creditinfo brings its industry-leading Credit Risk Analytics knowledge and experience to the table, alongside its intimate knowledge of available data in Afghanistan from its work running credit bureaus in the region. ACGF will bring its vast experience dealing with several leading local credit providers to the partnership, which includes a goldmine of data, knowledge and, ultimately, end users for this product.
Mr Benjamin Riley, Senior Global Consultant, Creditinfo, commented on the partnership: “Our unique insight into the Afghan credit market, combined with our previous work with the Central Bank of Afghanistan, will help in creating a robust and reliable measure of SME credit worthiness in the country. This will have a significant positive impact on the national economy, by opening up access to more affordable and stable credit to SMEs. Creditinfo is delighted to be given the opportunity to work alongside ACGF to help the country deliver these much-needed changes.”
Mr Bernd Leidner, Chairman of Management Board, ACGF added: “Globally, SMEs are the driving force behind economic growth, generating employment opportunities and wealth. However, access to affordable and stable credit is a key factor in the success of the sector. Afghanistan is no different in this respect. For years, we have been dedicated to opening up financial access to Afghan businesses. Our next initiative, alongside our trusted partner Creditinfo, will ensure we’re providing the local market with the required tools, consultancy and advice to not just survive, but thrive.”
Established in 1997 and headquartered in Reykjavík, Iceland, Creditinfo is a provider of credit information and risk management solutions worldwide. As one of the fastest growing companies in its field, Creditinfo facilitates access to finance, through intelligent information, software and analytics solutions.
With more than 33 credit bureaus running today, Creditinfo has the largest global presence in the field of credit risk management, with a significantly greater footprint than competitors. For decades it has provided business information, risk management and credit bureau solutions to some of the largest, lenders, governments and central banks globally – all with the aim of increasing financial inclusion and generating economic growth by allowing credit access for SMEs and individuals.
For more information, please visit www.creditinfo.com
About ACGF – Afghan Credit Guarantee Foundation
ACGF – Afghan Credit Guarantee Foundation is a charitable foundation based in Cologne, Germany. ACGF’s mission is to improve access to finance for Small and Medium Enterprises (SMEs) in Afghanistan by providing credit guarantees and technical assistance to Partner Institutions (PIs) – banks, micro-finance and micro-deposit institutions. ACGF is closely supported by its local subsidiary – SME Client Support Afghanistan (SCSA) with offices in Kabul and Mazar-i-Sharif.
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Translated version of the interview with Sidimohamed Abouchikhi, CEO of Creditinfo Morocco.
Image credit: Finance News.
Interview by Momar Diao
At the global level, Credit offices are open to any kind of information to assess the risk of a customer. Which is not the case yet for the Morocco. Elsewhere, data telecom operators, water and electricity suppliers give financial institutions the opportunity to better understand their customers.
Finance News weekly: How did Creditinfo Morocco perform during the first quarter of 2019? And what are your projections for the year 2019?
Sidi Abouchikhi: As we already announced previously, the number of consultations by the Credit Bureau has surpassed 2.5 million in 2018 and this upward trend continued for the first quarter of the year 2019 in alignment with our forecast.
Regarding value-added services, we recorded a high demand on our services of Monitoring, Alerting and Scoring. This trend is a reflection of the actions carried out by the financial sector to “air out” its portfolio of credits for more of risk management and to comply with regulatory, increasingly strict prerogatives with the IFRS 9 standard which came into application recently.
In terms of strategy, we note that institutions implement transformation programs in the areas of Risk management, which is likely to increase their appetites for the use of the ‘Big data’. Rightly, Creditinfo continues to support the financial system through innovative services and solutions of digitalization able to support these transformations.
F.N.H.: In Morocco, credit bureau activities are open to the water, electricity sector and the Telecom and insurance sectors. What does this mean concretely?
S.A.: The integration of this kind of so-called alternative data fits into the process of natural evolution to a Credit Bureau. At the global level, Credits offices are open to any kind of information to assess the risk of a customer. This is the case for Creditinfo that manages this data in its Credit offices in Europe, the Middle East and Africa.
For example, in West Africa, data telecom operators and suppliers of water and electricity give financial institutions the opportunity to better locate their clients in a more relevant manner, regardless of the timing .i.e: at the beginning of the granting credit or during its collection.
In Morocco, the integration of such data is a real opportunity to develop a new generation of financial products and services and, consequently, to increase financial inclusion to a large section of the population that accesses, or in a very limited way, to financing, without forgetting the TPE which are today at the heart of all policies public development and require, too, a fundraising effort on the part of the financial system by more suitable products.
F.N.H.: Is Creditinfo, today, equipped and endowed with the necessary expertise to accompany the above sectors?
S.A: As a global leader in the sector, we manage the data in 20 of our Credit offices worldwide. This kind of data is considered to be classic, despite its novelty in some countries. Creditinfo has tech solutions and proven expertise to manage data of Telecom operators and water and electricity suppliers as well as data from financial systems.
In other markets, Creditinfo uses a new generation mobile data as the metadata for mobile phones. The idea is to capture the maximum possible information to enable the creation of models with more power and predictive algorithms, paving the way for a more automated process of granting credit, cost reduction for promotion of financial inclusion.
F.N.H.: Finally, how do you manage customer risk at the level of banks and micro-credit associations?
S.A.: The culture of risk management is well established in the Moroccan banking system. Thanks to devices that control risk, the banking system is backed by rating agencies, demonstrating its resilience and ability to adapt to changes imposed by the transformation in digitization and regulation. The risk trend remains stable without significant deterioration throughout the first quarter of the year 2019. For micro-credit associations, the overall trend of risk has improved following the adoption of the report of solvency and scores provided by Creditinfo.
However, the increase in the threshold of 150.000 DH funding is to push microcredit associations to transform and equip themselves with solutions that enable a better knowledge and assessment of the customer and better management of the cycle life of the credit.
Paul Randall was recently at the Kafalah SME Financing Conference in Riyadh, Saudi Arabia, and he tackled these 2 questions during the panel discussion.
What are the specific challenges of assessing credit risk of SMEs as compared to larger firms and how can fintech can help lenders address those?
“There are 3 main areas of a difference and I could summarise this by talking about the “3 P’s”: Pertinent data, Profitability and Pride. The availability of formal data in regard to the pertinent data, the profitability the cost of gathering data and pride relates to the different skill set.
For Pertinent data we can consider for large corporates that balance sheets, profit and loss financial ratios cash-flow provide a huge amount of data. When it comes to small businesses this formal information is often not available. However in the future we will see the use of open banking data, mobile wallet data, credit bureau and invoice information data like for example, Amazon who through their invoice information, are likely to be one of the biggest global lenders to SME in the future.
When we look at the Profitability for small business lending historically, we see that it has been low because of the cost of data and the relatively low volumes compared to retail. When the information is a gathered automatically and decisions are made digitally then the cost reduces and a profitability increases.
The final point perhaps I was a little bit harsh using the word “Pride” with my “3 P’s”. What I mean here is that the skill set for underwriting corporate loans is very different to that of underwriting small businesses especially when an automated process is used, so it has been important to separate the departments of corporate lending and small business lending to really be effective in this area”.
What are some of the key innovations that are seen in credit reporting and credit scoring today that have the potential to transform the SME finance space and reduce the credit gap?
“The core concept that fintech credit bureaus are supporting is data fusion. This is the process of gathering data from multiple sources and bring it together.
So where does this new data come from for SME decisions? We have data from mobile wallets so the transaction data that is made in mobile wallets in different markets can be data from open banking sources – so transactional data in the banking environment. From there we can then identify data on the internet or from mobile scraping so to bring together the information on activity that the companies are undertaking such as making news articles and traffic on their websites. At Creditinfo for example, we are working with a number of lenders and use the mobile wallet data to support SME lending in Africa.
We have information from credit bureaus that describe many aspects of SMEs. Many credit bureaus will hold information on the payment histories also the credit activity of businesses furthermore they will hold information on any collateral or guarantors or information on the directors or owners”.