Banking on the Data Revolution

The data democratization

India is the highest consumer of mobile internet in the world. Internet access has allowed people to explore products, services, opportunities, and content from across the world.

Source: Ericsson Mobility Report 2018

This change is already forcing enterprises to take their businesses online and have a presence in the online space. Online retail sales has increased by over 250% from $19.7bn in 2015 to $50bn in 2018. Out of all the queries for digital commerce, 82% were made through mobile device in 2017.

Smartphone penetration

While PCs and tablets are expensive and beyond the budget of the masses, with 4G enabled smartphones costing roughly $7 in the country, affordability is no more a constraint leading to around 500% increase in the number of 4G enabled smartphones from 47 million in 2015 to 218 million in 2017. The number of mobile internet users is expected to rise sharply by roughly 21% CAGR from 240 million in 2016 to 520 million in 2020.

Increase in average data consumption

With the launch of 4G, the high-speed internet has been made available to the masses for the first time. Drop in data prices by 93%, from $3.7 per GB to $0.26 per GB has changed the behavior of customers significantly and has gotten them hooked to the internet, with an average Indian user spending roughly 3 hours a day on their smartphones.

Digital footprint

Increased geographical reach and improved speed, coupled with the huge numbers of first-time 4G-enabled smartphone users, has made India a huge source of customers’ digital footprint.The data democratization of masses can translate into the data revolution for the industries. Using this data to improve the scale and scope of business operations is being thought about by every industry and these changes can have huge social, economic and technological ramifications. Data revolution for improved efficiencies of retail lenders is one such expected ramification.

Digital footprint for efficient lending?

Image: Enhanced Net Interest Margin(NIM) due to better risk management and operational costs

The digital footprint of the customer is one pristine data source, self-generated by the customer. That’s why this digital footprint has proven to be a great tool for profiling the customer and hence is being used to identify the customer’s behavior and preferences. Indian retail lenders are already realizing the value from customers’ digital footprint by either strategic partnerships with technology services like ICICI has partnered with Paytm to offer instant short-term credit digitally, or by acquiring technology service providers, like Capital Float recently acquired Walnut, a personal finance management app, for $30 million.

The patterns in preferences and behavior can enable lenders to effectively underwrite customers with no or thin bureau records. The models including digital footprint and alternative data as additional inputs have continuously proved their mettle across the world and have consistently outperformed the traditional credit bureau models as highlighted in a FICO research shows that alternate data adds predictive value on margin to credit risk models, data stemming from transactions, utilities, social media, etc., contribute to the overall predictive power of the models.

The collection, preparing, and analyzing customer’s digital footprint will facilitate financial inclusion over a series of levels as highlighted below.

Level 1: Bringing more people under the ambit of underwriting

More than 300 million Indians are smartphone users and this number is expected to grow to 530 million by the end of 2018. More than 225 million Indians are registered with social networks and it is expected that this number will increase to 371 million.

The increasing digital presence of Indians will allow more people to seek credit. This view was supported by other professionals claiming that the idea of incorporating alternative data in credit risk assessment will benefit a majority of erstwhile unscorable and unlendable customers. According to a PERC study, including alternative data improved the credit score of 64% of thin-file customers, while reducing the scores for just 1% of the sample.

Level 2: Reduced per-unit cost

Digital lenders have lower operating cost compared to traditional lending institutions. Private lenders in India are partnering with FinTechs to improve their underwriting quality and lower the underwriting cost. Operating expense as a percentage of outstanding loans run at approximately 6% at banks that use traditional processes, compared to less than 2% at the non-bank alternative lenders. Incorporating alternative data in credit decisioning could further reduce costs for lenders allowing the lenders to enhance profitability.

Level 3: Profitability of small-ticket size loans

Incorporating alternative data in credit risk assessment reduces the costs of underwriting and will enable a larger pool to seek institutional credit. This will result in higher profitability of small-ticket size loans.

Experts note that for lenders, the primary benefit of incorporating alternative data is the ability to increase the number of profitable loans while having a consistent risk appetite. Additionally, alternative data will enable lenders to have a more complete picture of the prospective borrower, enabling them to offer competitive interest rates, which many lenders consider as a challenge today.

With increased profitability, retail lenders will be incentivized to get aggressive in this segment.


The value of alternative data for retail lenders was also emphasized by the Reserve Bank of India(RBI), as it highlighted that incorporating alternative data would provide lenders with pointers to assess the borrowers’ financial situation and enable lenders to make an informed credit decision.

The regulatory impetus and the socio-economic need for lenders to adopt alternative data has resulted in mushrooming of multiple artificial intelligence and data science startups providing insights from alternative data to make the operations of lenders more efficient.

Incorporating alternative data in the mainstream will be facilitated by these startups and fulfilling the aspiration of Viral Acharya, Deputy Governor, RBI, to make available tailored credit products for the immediate credit needs of every borrower in the country.

Just like in the Fast-moving Consumer Goods(FMCG) sector, banking and access to credit too will be‘sachetized’ to make it more accessible and affordable for the masses. We want that even a small tea shop vendor should be able to take a 500 rupee loan at fair rates, say, for only a week. - Viral Acharya, Deputy Governor, RBI

Click here to access MEDICI’s latest report on Big Data Analytics

In their endeavor to use data analytics as an enabling force, banks are facing a number of challenges, both at the strategic and operational levels. The aim of this report is to help banks arrive at an effective Data Analytics strategy by identifying the problems and suggesting practical solutions. It looks at the challenges in a bank’s journey in achieving actionable insights from an ingrained analytics process and suggests strategic and operational best practices to create and execute an implementable vision.