Protect People From Themselves: Reducing Default Risks in P2P Lending

I think there's some connection between absolute discipline and absolute freedom. Alan Rickman (1946-2016)English actor and director ‘Freedom’ has been the slogan of the fintech boom witnessed over the recent decades. Many fintech advocates regarded the traditional financial system as too rigid, over-regulated, excessively conservative, and too old anyway. From cryptocurrencies and crowdfunding to alternative payment channels and peer-to-peer (P2P) loans, this bright new financial world seemed to pave the way to self-regulation (who said anarchy?), where people could prosper by making their own conscious decisions. Well, the reality turned out to be a bit tougher for me as I became the Founder of Lendsbay, a P2P lending platform. This article is a real-life case study of dealing with default risks. To put things short, many people all too often tend to rush into ill-considered financial decisions. Leaving things just as they are leads to catastrophic results both for the clients and the platform. A framework of rules should be built in order to protect people from their own hasty behavior. So, this story could alternatively be named “How I started with promoting absolute freedom but ended up becoming a regulator myself.” Wherever Reckless People Congregate Exploring the subject of P2P lending is particularly intriguing because it involves more than just being an expert at a company, such as a bank, where you choose how to invest money (loans) and how to attract money (deposits). You rely on your experience, analysis, and loads of data to devise your business strategies. Some of them work, some do not, but your success depends primarily on your own judgment. But P2P is different: you build a platform where you bring together various types of participants and watch them interact with each other. When we started Lendsbay, my ultimate dream was to create an ideal market where investors and borrowers would meet in an efficient and easy manner, considering the information we provide them with. We would then receive fair commissions from successful deals, and the enterprise would be more profitable than a conventional bank. Or so we hoped… Any P2P lending platform has two major functions. First, it is a place where borrowers and lenders meet. Second, it has to make this environment as transparent as possible. First of all, there are the KYC procedures. We conducted thorough checks on borrowers, including their passports and other paperwork, we checked if they were on the terrorist watch lists, and obtained their full credit history. Based on the collected data borrowers were assigned with ratings (from best A to poorest F) so that lenders could make informed investment decisions. And, of course, loans were disbursed only to the borrowers’ card accounts, no physical cash lending was allowed. However, as the system was launched, we saw to our horror that many investors just kept choosing the most profitable and risky loans for their investment, regardless of the risk we indicated for them using our A-F scale. The investors’ behavior resembled that of casino gamblers. Their logic (as we saw it) was that since there is a default risk anyway, no matter how high or low, it is always better to choose loans with the highest interest rates to increase the likelihood of earning. Needless to say, this led to numerous defaults, as even loans of blatantly poor quality were readily taken up by investors. The problem was exacerbated by low-risk borrowers with poor credit histories often requesting loans of small amounts, making it easier for investors to grant small loans than larger ones. How Bad Is Your Default Rate What should be considered a high default rate is a matter of debate. It depends on the country, the economic conditions, and, of course, the borrowers’ quality. Numerous research suggests that a growing economy, indicated by rising GDP and increasing stock market indices, generally reduces P2P lending default rates. On the contrary, higher inflation and interest rates, as well as turmoil and uncertainty associated with pandemics and conflicts tend to worsen the default statistics. A report by Zopa, a P2P lending pioneer based in the UK, sets the expected average annual default rates between less than 0,5% for the best borrowers and as much as 15% for the worst: Borrower rating A A1 A2 B C1 D E Share in portfolio 49% 7% 13% 10% 16% 4% 2% Expected annual default rate <0.5% 0.5-2.5% 0.5-2.5% 3-8% 3-8% 8-15% 10-15% Source: P2P Lending and Regulation Data from another industry pioneer and arguably the best-known P2P lending platform, the Lending Club from the U.S., suggests a different picture. Lending Club’s publicly released datasets served as a classical source of empirical information and were used in numerous research papers dedicated to the P2P lending market. One of them states that the actual default rates vary from 5.2% to 43.4% averaging at 17.4%: Borrower grade A B C D E F G Total Share in portfolio 15% 29% 28% 17% 8% 3% 1% 100% Actual default rate 5.2% 10.9% 18.8% 25.7% 33.4% 37.4% 43.4% 17.4% Source: Predictive Analysis of Default Risk in Peer-to-Peer Lending Platforms: Empirical Evidence from LendingClub (based on 358,518 actual loans) Well, our initial default rate at Lendsbay was very, very high. It reached 50+% annually for low-rated loans, exceeding the worst rates of Lending Club’s G-rated borrowers. The Third and Fourth Elements This is when we saw that an efficient and successful P2P lending platform needs two more essential functions: rules and education. Rules affect the way and the result of interactions between borrowing and lending clients and, at the end of the day, it is them that define whether these interactions bring profit to your clients and the platform itself. We realized that we needed to guide investors and implement risk mitigation measures. Here is what we did: First, we divided all loans into tranches, allowing investors to invest any amount starting from an equivalent of 10 euros instead of the entire loan amount. Second, we restricted access for novice investors to low-rated loans; they simply didn't see these loans until they had invested in 10 loans with good ratings. Third, we began calculating and showing investors their potential returns after risk. Whereas previously they only saw the contract rate and rating, they now saw the expected return with the expected default rate taken into account. Fourth, we developed a separate portfolio window to evaluate the quality of an investor's portfolio, providing recommendations such as investing more in well-rated loans, investing smaller sums in a larger number of loans, reducing the share of the largest loan in the portfolio, etc. Fifth, we created a separate channel where we posted information about the most interesting loans according to our own calculations. Sixth, we introduced mandatory sorting by rating, ensuring that less risky loan applications always appeared at the top. All these principles significantly helped reduce default levels in investors' portfolios, increased their satisfaction with the platform, and improved returns. The average default rate was reduced to 20%, which is quite close to the average Lending Club’s default rate. It was still a long way from Zopa’s performance, but note the difference in the borrower portfolio composition. As you see from the tables above, Zopa focused on top-notch borrowers with a pure A rating so that they made up almost half of their entire portfolio. Lending Club distributed the portfolio more evenly mainly between borrowers with average and above-average ratings (A-D). At the time, interest rates in the US and the UK hovered around their historical lows, which meant that platforms like Zopa or Lending Club simply could not afford to shift their focus to more risky borrowers. At a higher default rate, their business would have generated losses instead of profits. So this factor perfectly explains their portfolio composition. Things were different for Lendsbay: in Eastern Europe interest rates were significantly higher, which meant that we could venture into the riskier (but more profitable) borrower segments. Considering this, bringing our overall default rate to a level similar to that of the Lending Club, a platform with a much less risky portfolio, was a truly big achievement. This meant we could offer our investors a higher profitability after risk deduction than similar Western companies. All in all, this has been a very good lesson about people’s behavior that is probably not limited just to finance. In a new environment, many people tend to behave recklessly preferring to gamble rather than take informed and conscious decisions. Responsible P2P lending platform management inevitably means combining educational measures with restrictive ones. If you study once again the list of six major steps we took to improve our situation at Lendsbay, you will see that half of the measures (three out of six) were educational and the other half were restrictive. Knowledge does not come on its own. In the world of finance, you have to put a lot of effort and time into educating people so that their choices become truly informed and truly conscious. Until a certain level of knowledge is reached, you will have to rely on restrictions in order to protect people not just from their peers, but mostly from themselves. However, it is important to remember that you have to gradually lift some (if not most) of those restrictions as the educational process advances for each individual investor. After all, fintech is all about freedom and this is what I still stand for after learning my Lendsbay lesson. I think there's some connection between absolute discipline and absolute freedom. Alan Rickman (1946-2016) English actor and director I think there's some connection between I think there's some connection between I think there's some connection between absolute discipline and absolute freedom. absolute discipline and absolute freedom. absolute discipline and absolute freedom. Alan Rickman (1946-2016) Alan Rickman (1946-2016) English actor and director English actor and director ‘Freedom’ has been the slogan of the fintech boom witnessed over the recent decades. Many fintech advocates regarded the traditional financial system as too rigid, over-regulated, excessively conservative, and too old anyway. From cryptocurrencies and crowdfunding to alternative payment channels and peer-to-peer (P2P) loans, this bright new financial world seemed to pave the way to self-regulation (who said anarchy?), where people could prosper by making their own conscious decisions. ‘Freedom’ has been the slogan of the fintech boom witnessed over the recent decades. Many fintech advocates regarded the traditional financial system as too rigid, over-regulated, excessively conservative, and too old anyway. From cryptocurrencies and crowdfunding to alternative payment channels and peer-to-peer (P2P) loans, this bright new financial world seemed to pave the way to self-regulation (who said anarchy?), where people could prosper by making their own conscious decisions. Well, the reality turned out to be a bit tougher for me as I became the Founder of Lendsbay, a P2P lending platform. This article is a real-life case study of dealing with default risks. To put things short, many people all too often tend to rush into ill-considered financial decisions. Leaving things just as they are leads to catastrophic results both for the clients and the platform. Well, the reality turned out to be a bit tougher for me as I became the Founder of Lendsbay, a P2P lending platform. This article is a real-life case study of dealing with default risks. To put things short, many people all too often tend to rush into ill-considered financial decisions. Leaving things just as they are leads to catastrophic results both for the clients and the platform. A framework of rules should be built in order to protect people from their own hasty behavior. So, this story could alternatively be named “How I started with promoting absolute freedom but ended up becoming a regulator myself.” A framework of rules should be built in order to protect people from their own hasty behavior. So, this story could alternatively be named “How I started with promoting absolute freedom but ended up becoming a regulator myself.” Wherever Reckless People Congregate Wherever Reckless People Congregate Exploring the subject of P2P lending is particularly intriguing because it involves more than just being an expert at a company, such as a bank, where you choose how to invest money (loans) and how to attract money (deposits). You rely on your experience, analysis, and loads of data to devise your business strategies. Some of them work, some do not, but your success depends primarily on your own judgment. But P2P is different: you build a platform where you bring together various types of participants and watch them interact with each other. When we started Lendsbay, my ultimate dream was to create an ideal market where investors and borrowers would meet in an efficient and easy manner, considering the information we provide them with. We would then receive fair commissions from successful deals, and the enterprise would be more profitable than a conventional bank. Or so we hoped… Any P2P lending platform has two major functions. First, it is a place where borrowers and lenders meet. Second, it has to make this environment as transparent as possible. First of all, there are the KYC procedures. We conducted thorough checks on borrowers, including their passports and other paperwork, we checked if they were on the terrorist watch lists, and obtained their full credit history. Based on the collected data borrowers were assigned with ratings (from best A to poorest F) so that lenders could make informed investment decisions. And, of course, loans were disbursed only to the borrowers’ card accounts, no physical cash lending was allowed. However, as the system was launched, we saw to our horror that many investors just kept choosing the most profitable and risky loans for their investment, regardless of the risk we indicated for them using our A-F scale. The investors’ behavior resembled that of casino gamblers. Their logic (as we saw it) was that since there is a default risk anyway, no matter how high or low, it is always better to choose loans with the highest interest rates to increase the likelihood of earning. Needless to say, this led to numerous defaults, as even loans of blatantly poor quality were readily taken up by investors. The problem was exacerbated by low-risk borrowers with poor credit histories often requesting loans of small amounts, making it easier for investors to grant small loans than larger ones. How Bad Is Your Default Rate How Bad Is Your Default Rate What should be considered a high default rate is a matter of debate. It depends on the country, the economic conditions, and, of course, the borrowers’ quality. Numerous research suggests that a growing economy, indicated by rising GDP and increasing stock market indices, generally reduces P2P lending default rates. reduces reduces On the contrary, higher inflation and interest rates, as well as turmoil and uncertainty associated with pandemics and conflicts tend to worsen the default statistics. worsen worsen A report by Zopa, a P2P lending pioneer based in the UK, sets the expected average annual default rates between less than 0,5% for the best borrowers and as much as 15% for the worst: Borrower rating A A1 A2 B C1 D E Share in portfolio 49% 7% 13% 10% 16% 4% 2% Expected annual default rate <0.5% 0.5-2.5% 0.5-2.5% 3-8% 3-8% 8-15% 10-15% Borrower rating A A1 A2 B C1 D E Share in portfolio 49% 7% 13% 10% 16% 4% 2% Expected annual default rate <0.5% 0.5-2.5% 0.5-2.5% 3-8% 3-8% 8-15% 10-15% Borrower rating A A1 A2 B C1 D E Borrower rating Borrower rating Borrower rating A A A A1 A1 A1 A2 A2 A2 B B B C1 C1 C1 D D D E E E Share in portfolio 49% 7% 13% 10% 16% 4% 2% Share in portfolio Share in portfolio Share in portfolio 49% 49% 49% 7% 7% 7% 13% 13% 13% 10% 10% 10% 16% 16% 16% 4% 4% 4% 2% 2% 2% Expected annual default rate <0.5% 0.5-2.5% 0.5-2.5% 3-8% 3-8% 8-15% 10-15% Expected annual default rate Expected annual default rate Expected annual default rate <0.5% <0.5% <0.5% 0.5-2.5% 0.5-2.5% 0.5-2.5% 0.5-2.5% 0.5-2.5% 0.5-2.5% 3-8% 3-8% 3-8% 3-8% 3-8% 3-8% 8-15% 8-15% 8-15% 10-15% 10-15% 10-15% Source: P2P Lending and Regulation P2P Lending and Regulation P2P Lending and Regulation Data from another industry pioneer and arguably the best-known P2P lending platform, the Lending Club from the U.S., suggests a different picture. Lending Club’s publicly released datasets served as a classical source of empirical information and were used in numerous research papers dedicated to the P2P lending market. One of them states that the actual default rates vary from 5.2% to 43.4% averaging at 17.4%: Borrower grade A B C D E F G Total Share in portfolio 15% 29% 28% 17% 8% 3% 1% 100% Actual default rate 5.2% 10.9% 18.8% 25.7% 33.4% 37.4% 43.4% 17.4% Borrower grade A B C D E F G Total Share in portfolio 15% 29% 28% 17% 8% 3% 1% 100% Actual default rate 5.2% 10.9% 18.8% 25.7% 33.4% 37.4% 43.4% 17.4% Borrower grade A B C D E F G Total Borrower grade Borrower grade Borrower grade A A A B B B C C C D D D E E E F F F G G G Total Total Total Share in portfolio 15% 29% 28% 17% 8% 3% 1% 100% Share in portfolio Share in portfolio Share in portfolio 15% 15% 15% 29% 29% 29% 28% 28% 28% 17% 17% 17% 8% 8% 8% 3% 3% 3% 1% 1% 1% 100% 100% 100% Actual default rate 5.2% 10.9% 18.8% 25.7% 33.4% 37.4% 43.4% 17.4% Actual default rate Actual default rate Actual default rate 5.2% 5.2% 5.2% 10.9% 10.9% 10.9% 18.8% 18.8% 18.8% 25.7% 25.7% 25.7% 33.4% 33.4% 33.4% 37.4% 37.4% 37.4% 43.4% 43.4% 43.4% 17.4% 17.4% 17.4% Source: Predictive Analysis of Default Risk in Peer-to-Peer Lending Platforms: Empirical Evidence from LendingClub (based on 358,518 actual loans) Predictive Analysis of Default Risk in Peer-to-Peer Lending Platforms: Empirical Evidence from LendingClub Predictive Analysis of Default Risk in Peer-to-Peer Lending Platforms: Empirical Evidence from LendingClub Well, our initial default rate at Lendsbay was very, very high. It reached 50+% annually for low-rated loans, exceeding the worst rates of Lending Club’s G-rated borrowers. The Third and Fourth Elements This is when we saw that an efficient and successful P2P lending platform needs two more essential functions: rules and education. Rules affect the way and the result of interactions between borrowing and lending clients and, at the end of the day, it is them that define whether these interactions bring profit to your clients and the platform itself. We realized that we needed to guide investors and implement risk mitigation measures. Here is what we did: First, we divided all loans into tranches, allowing investors to invest any amount starting from an equivalent of 10 euros instead of the entire loan amount. First, we divided all loans into tranches , allowing investors to invest any amount starting from an equivalent of 10 euros instead of the entire loan amount. we divided all loans into tranches Second, we restricted access for novice investors to low-rated loans; they simply didn't see these loans until they had invested in 10 loans with good ratings. Second, we restricted access for novice investors to low-rated loans ; they simply didn't see these loans until they had invested in 10 loans with good ratings. we restricted access for novice investors to low-rated loans Third, we began calculating and showing investors their potential returns after risk. Whereas previously they only saw the contract rate and rating, they now saw the expected return with the expected default rate taken into account. Third, we began calculating and showing investors their potential returns after risk . Whereas previously they only saw the contract rate and rating, they now saw the expected return with the expected default rate taken into account. calculating and showing investors their potential returns after risk Fourth, we developed a separate portfolio window to evaluate the quality of an investor's portfolio, providing recommendations such as investing more in well-rated loans, investing smaller sums in a larger number of loans, reducing the share of the largest loan in the portfolio, etc. Fourth, we developed a separate portfolio window to evaluate the quality of an investor's portfolio, providing recommendations such as investing more in well-rated loans, investing smaller sums in a larger number of loans, reducing the share of the largest loan in the portfolio, etc. evaluate the quality of an investor's portfolio, providing recommendations Fifth, we created a separate channel where we posted information about the most interesting loans according to our own calculations. Fifth, we created a separate channel where we posted information about the most interesting loans according to our own calculations . posted information about the most interesting loans according to our own calculations Sixth, we introduced mandatory sorting by rating, ensuring that less risky loan applications always appeared at the top. Sixth, we introduced mandatory sorting by rating , ensuring that less risky loan applications always appeared at the top. mandatory sorting by rating All these principles significantly helped reduce default levels in investors' portfolios, increased their satisfaction with the platform, and improved returns. The average default rate was reduced to 20%, which is quite close to the average Lending Club’s default rate. It was still a long way from Zopa’s performance, but note the difference in the borrower portfolio composition. As you see from the tables above, Zopa focused on top-notch borrowers with a pure A rating so that they made up almost half of their entire portfolio. Lending Club distributed the portfolio more evenly mainly between borrowers with average and above-average ratings (A-D). At the time, interest rates in the US and the UK hovered around their historical lows, which meant that platforms like Zopa or Lending Club simply could not afford to shift their focus to more risky borrowers. At a higher default rate, their business would have generated losses instead of profits. So this factor perfectly explains their portfolio composition. Things were different for Lendsbay: in Eastern Europe interest rates were significantly higher, which meant that we could venture into the riskier (but more profitable) borrower segments. Considering this, bringing our overall default rate to a level similar to that of the Lending Club, a platform with a much less risky portfolio, was a truly big achievement. This meant we could offer our investors a higher profitability after risk deduction than similar Western companies. All in all, this has been a very good lesson about people’s behavior that is probably not limited just to finance. In a new environment, many people tend to behave recklessly preferring to gamble rather than take informed and conscious decisions. Responsible P2P lending platform management inevitably means combining educational measures with restrictive ones. If you study once again the list of six major steps we took to improve our situation at Lendsbay, you will see that half of the measures (three out of six) were educational and the other half were restrictive. Knowledge does not come on its own. In the world of finance, you have to put a lot of effort and time into educating people so that their choices become truly informed and truly conscious. Until a certain level of knowledge is reached, you will have to rely on restrictions in order to protect people not just from their peers, but mostly from themselves. However, it is important to remember that you have to gradually lift some (if not most) of those restrictions as the educational process advances for each individual investor. After all, fintech is all about freedom and this is what I still stand for after learning my Lendsbay lesson.