No, Alternative Data Is Not Evil & Other Such Myths Busted
Data science, data analytics, data mining, data privacy- the ever-expanding list of terms with ‘data’ in them are becoming increasingly common in our daily vocabulary and rightfully so. With a vast majority of modern-day problems being resolved by modern applications of various types of data, the advent of technology has radically altered traditional operating models across fundamental commercial domains such as manufacturing, retail and banking- to name a few.
Yet, an increasingly commercialized society has also witnessed a rise in the number of people unable to afford the products offered by these domains and this is especially prevalent in the banking sector. With developing countries having vast majorities of unbanked people, limited access to formal credit and a lack of financial inclusion, governments have introduced various schemes to assist this demographic. This is good but alternative data is what can make it better.
For people with poor credit scores but in dire need of loans, alternative credit scoring has been bridging the gap between the needs of people and hindrances holding them back. While many understand the obvious benefits this approach can have in the long run, some common misconceptions linger around and here is a brief deep dive into the veracity of these claims.
1.Alternative credit data is unreliable and untrustworthy
Reports from Experian have pointed out that ~65% of lenders in the banking industry believe and have been using sources of data apart from the traditional format of credit data that has been utilized for decades to carry out lending.
The sum of parts is greater than the whole and this is especially true in the case of lending data as traditional data combined with alternative data gathered by analyzing behavioral aspects of customers can provide an enhanced portfolio. This allows the expansion of financial scope for merchants as lenders can not only provide them personalized offers but also introduce them to new options.
2. Alternative consumer data is only used for financial activities catering to individuals
The utilization of alternative data has many applications and they have been a boon for small businesses to secure collateral-free loans. Such businesses do not have a traditionally strong credit score, which when coupled with financial woes and economic trends paint a dreary picture. Thus, data from POS terminals, phone pings and surrogate sources of data such as tax returns and various bills help lenders cater to the needs of the business owners, and chalk out suitable loan plans.
3. Alternative data is a violation of customer privacy
With strict rules and regulations being implemented in legislative frameworks worldwide, access to an expansive database has long tweaked curiosity in people about privacy concerns. However, all the data acquired through third parties or directly from the customers is consensual.
Furthermore, a survey from Experia found that 70% of customers are willing to share necessary data to avail better offers and financial services. Smartphones have metadata that allows customers to know about the type of data to be outsourced and can make their independent decisions regarding access.
4. A major chunk of alternative data is social media data
From smartphone metadata to payment pings at POS terminals, lenders do not rely solely on social media data to predict behavioral patterns regarding payments. Tax returns and timely bill payments coupled with traditional financial parameters can be compiled into an AI-powered scoring model to provide a more holistic credit score to assess the levels of delinquency and creditworthiness of the customer.
Millions in India still lack proper credit access despite the increasing rate of smartphone penetration. This is where alternative data can make all the difference and help them access a democratized channel of credit and other financial services.