Significance Of Psychometrics And Biometrics For Underwriting To Reduce NPA Burden For Lenders
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India has nearly 190 million unbanked adults, which makes it the second developing country after China in the number of residents who don't have bank accounts or participate in the formal financial sector, as identified by the World Bank. Traditional banks and lending companies consider them credit `unworthy' because of their absence of any banking transaction data to establish earning, which helps in determining their capacity to repay. Moreover, such individuals do not have a credit history to calculate credit scores (eg. CIBIL score), which in turn helps in establishing the intention and ability to repay. The use of financial behaviour using banking transactions and credit history are effective underwriting tools for lending.
Credit availability is essential for the economic success of individuals, corporations and nations. Access to credit can help significantly in poverty alleviation. As individuals become more prosperous and richer, they can contribute more towards the growth of the country as well as the world. Thus, it is essential for the financial institutions to create mechanisms for underwriting excluded individuals rather than focussing only on the financially established population. While it may sound difficult, there are many ways to underwrite such excluded individuals using alternative data and techniques.
The Global Findex Report 2017 revealed that in India, more than 50 percent of the unbanked population and 66 percent of inactive account holders carry a mobile phone. The increasing use of mobile phones and digital technology can be an effective way to reach and understand the financially excluded individuals. Many organisations are extracting data about the users from their mobile phones to understand more about them. The data basically is derived from social media posts, messaging, contact lists, applications used, etc. While such type of data does help understand individuals, applications or social media are not used extensively by many on their mobile devices. This calls for the need for an effective method of collecting data about specific users that can be sufficient to establish their ability and intent towards repayment.
The use of Psychometrics and Biometrics are two effective ways of determining intention. Both the techniques go beyond financial behaviours to build a holistic profile of an individual based on their behaviours. This might sound familiar to the days when loans were approved by banks on the basis of interviews and intuition of bank managers. While the concept is almost the same, the use of digital media and artificial intelligence-driven algorithms make the approach faster, reliable and effective, thereby eventually helping reduce the risk of NPAs.
Using Psychometrics Data To Identify Financial Behaviour
To establish financial behaviour of an individual, Psychometrics data promises very good accuracy by identifying personality traits that have a direct correlation to financial behaviour. While there are several ways to do it, a situation judgment test is the most prominent method where users are presented with hypothetical situations to determine their personality. An example may be asking a friend to lend you some money and they agree to lend you half of what you need. How does one react in such a scenario? Show gratitude, show happiness, be disappointed or angry. The response selected by the applicant can determine their personality. The effectiveness of Psychometrics is well established in personality determination. Various researches have been established that show a correlation between personality and financial behaviour. By bringing these techniques into the mainstream and making the experience user friendly through digital media, financially excluded individuals can be underwritten in a very effective manner.
Using Biometrics To Establish Financial Behaviour
Biometrics isn't a new concept. It is already being used for several purposes to establish authenticity. For instance, mobile devices using face matching or thumb impression to unlock them are a way of using biometrics. Meanwhile, using thumb impression to provide consent for use of Aadhar data is yet another example of biometrics. Several digital lending applications are also using videos and face matching to ensure authentic identification. However, to underwrite loans to the unbanked individuals a lot more needs to be done.
Recall a lie detector or a polygraph test that uses pulse rate, blood pressure and even body temperature fluctuation to determine a person's honesty. Latest research shows that pupil dilation and eye blinking can also establish honesty. Such tests can be used to underwrite loans. Imagine individuals answering simple questions on their phone like the purpose of their loan application, the duration, information about themselves and their families etc. While answering such questions, a mobile device can capture their eye and pupil movement, check their pulse rate and body temperature. Since this is done on a mobile device, the user will have complete control of what, when and where they are giving out the information. Such data can help understand a person's honesty and intention and accordingly algorithms can be developed to establish clear correlation between the data collected and financial behaviour.
While there are several other approaches apart from the aforementioned that can also be adopted, financial institutions need to prioritise investment and research either organically or through partnerships. This will open up the gates of opportunities for financially excluded individuals and for the financial institutions as well by amplifying their customer base and portfolio. Even though the approaches we have discussed so far may seem intrusive but with proper privacy, consent and data securities, both these techniques can solve broader problems that can economically boost millions of people in the country.
India has nearly 190 million unbanked adults, which makes it the second developing country after China in the number of residents who don't have bank accounts or participate in the formal financial sector, as identified by the World Bank. Traditional banks and lending companies consider them credit `unworthy' because of their absence of any banking transaction data to establish earning, which helps in determining their capacity to repay. Moreover, such individuals do not have a credit history to calculate credit scores (eg. CIBIL score), which in turn helps in establishing the intention and ability to repay. The use of financial behaviour using banking transactions and credit history are effective underwriting tools for lending.
Credit availability is essential for the economic success of individuals, corporations and nations. Access to credit can help significantly in poverty alleviation. As individuals become more prosperous and richer, they can contribute more towards the growth of the country as well as the world. Thus, it is essential for the financial institutions to create mechanisms for underwriting excluded individuals rather than focussing only on the financially established population. While it may sound difficult, there are many ways to underwrite such excluded individuals using alternative data and techniques.
While there are several ways to do it, a situation judgment test is the most prominent method where users are presented with hypothetical situations to determine their personality
The Global Findex Report 2017 revealed that in India, more than 50 percent of the unbanked population and 66 percent of inactive account holders carry a mobile phone. The increasing use of mobile phones and digital technology can be an effective way to reach and understand the financially excluded individuals. Many organisations are extracting data about the users from their mobile phones to understand more about them. The data basically is derived from social media posts, messaging, contact lists, applications used, etc. While such type of data does help understand individuals, applications or social media are not used extensively by many on their mobile devices. This calls for the need for an effective method of collecting data about specific users that can be sufficient to establish their ability and intent towards repayment.
The use of Psychometrics and Biometrics are two effective ways of determining intention. Both the techniques go beyond financial behaviours to build a holistic profile of an individual based on their behaviours. This might sound familiar to the days when loans were approved by banks on the basis of interviews and intuition of bank managers. While the concept is almost the same, the use of digital media and artificial intelligence-driven algorithms make the approach faster, reliable and effective, thereby eventually helping reduce the risk of NPAs.
Using Psychometrics Data To Identify Financial Behaviour
To establish financial behaviour of an individual, Psychometrics data promises very good accuracy by identifying personality traits that have a direct correlation to financial behaviour. While there are several ways to do it, a situation judgment test is the most prominent method where users are presented with hypothetical situations to determine their personality. An example may be asking a friend to lend you some money and they agree to lend you half of what you need. How does one react in such a scenario? Show gratitude, show happiness, be disappointed or angry. The response selected by the applicant can determine their personality. The effectiveness of Psychometrics is well established in personality determination. Various researches have been established that show a correlation between personality and financial behaviour. By bringing these techniques into the mainstream and making the experience user friendly through digital media, financially excluded individuals can be underwritten in a very effective manner.
Using Biometrics To Establish Financial Behaviour
Biometrics isn't a new concept. It is already being used for several purposes to establish authenticity. For instance, mobile devices using face matching or thumb impression to unlock them are a way of using biometrics. Meanwhile, using thumb impression to provide consent for use of Aadhar data is yet another example of biometrics. Several digital lending applications are also using videos and face matching to ensure authentic identification. However, to underwrite loans to the unbanked individuals a lot more needs to be done.
Recall a lie detector or a polygraph test that uses pulse rate, blood pressure and even body temperature fluctuation to determine a person's honesty. Latest research shows that pupil dilation and eye blinking can also establish honesty. Such tests can be used to underwrite loans. Imagine individuals answering simple questions on their phone like the purpose of their loan application, the duration, information about themselves and their families etc. While answering such questions, a mobile device can capture their eye and pupil movement, check their pulse rate and body temperature. Since this is done on a mobile device, the user will have complete control of what, when and where they are giving out the information. Such data can help understand a person's honesty and intention and accordingly algorithms can be developed to establish clear correlation between the data collected and financial behaviour.
While there are several other approaches apart from the aforementioned that can also be adopted, financial institutions need to prioritise investment and research either organically or through partnerships. This will open up the gates of opportunities for financially excluded individuals and for the financial institutions as well by amplifying their customer base and portfolio. Even though the approaches we have discussed so far may seem intrusive but with proper privacy, consent and data securities, both these techniques can solve broader problems that can economically boost millions of people in the country.
