Over the last few years, governments, NGOs and to a lower extent, the private sector, have all invested huge efforts and capital to help the unbanked population in emerging markets access the formal financial system. The common belief is that financial inclusion will enable governments to remit funds to their citizens in a safer manner, thereby reducing corruption and fraud. In addition to financial inclusion, the migration to digital payments will also enable individuals and businesses to transact in a manner that is both cheaper and safer, thereby promoting entrepreneurship and growth.

The growth in digital payments for the unbanked over the last 10 years has been phenomenal due to different mechanisms such as mobile money in Sub-Saharan Africa or government-initiated projects in India such as Adhar, digital India and payment banks.

 Payment banks are a new model of banks conceptualized by the Reserve Bank of India . Payment banks can operate current and savings accounts, they can issue ATM cards and debit cards as well as provide net-banking and mobile-banking. These banks can only accept restricted deposits and are not allowed to issue loans or credit cards.

However, a large portion of the population has moved from being unbanked altogether to being underbanked (i.e., they can now transact digitally but the majority of people are still unable to easily obtain access to credit and additional banking products that are considered critical for true financial inclusion).


Providing access to credit to the underbanked is very challenging. In the traditional lending process, the applicant is required to physically visit a branch or an agent to fill out a credit application form. The lender then assesses the application following a manual process that usually takes several days Traditional lenders rely on the applicant's credit history, collateral such as property or deposits or a steady, documented income such as a salary. However, most of the underbanked lack these three key assets: they have never obtained credit before and therefore they have no credit history, in many cases they have no assets that can be used as collateral, and most of them don't work in the formal economy, thereby lacking a steady job or a formal salary slip.

Making things even more challenging, the underbanked typically need relatively small loans since that is all  they are able to repay  whereas granting small loans is unprofitable for formal financial institutions such as the MFI or banks with traditional lending processes that are labor intensive and carry fixed operational costs.

Many tier one banks have already transformed many of their credit processes from traditional to digital lending. Obtaining a loan digitally requires the customer to fill out a credit application form digitally for which a decision is immediately made. Validation and disbursement typically occur within 24 hours. While digital lending streamlines the lending process by making it more efficient and cheaper, it focuses on customers that already have some recorded credit history, either with the financial institution or with a centralized credit bureau. Therefore, traditional digital lending doesn't effectively grant the underbanked access to credit.


We believe the next evolution in credit is Collaborative Lending. Under the Collaborative Lending model, an existing lender partners with a non-lending partner. Whereby the partner provides detailed data on each existing customer that has specific credit needs. The lender funds the credit and uses its underwriting know-how as well as its regulatory framework and lending license.

This collaboration enables a very efficient and inexpensive process, because the partner supplies the credit lead, thereby yielding a very low cost of customer acquisition for the lender. The lender receives validated customer data from the partner, making the operational costs very low. The lender disburses the funds immediately and directly through the partner, thereby reducing fraud risk.


We believe Collaborative Lending could be relevant for all unsecured loans:

  • When an unbanked individual uses his or her mobile money application and does not have enough balance to pay.
  • When an individual purchases a home appliance such as a refrigerator, and the merchant offers that purchaser a bank loan to finance the purchase.
  • When a small business wants to buy from his or her current supplier.

Collaborative lending benefits all parties:

  • Customers save time and effort, getting credit when and where it is needed and at a lower price.
  • The partners reduce customer churn and increase their customer value through additional income related to credit.
  • Lenders enjoy access to a new target market of potential borrowers that can be very efficient and deliver a higher ROE than the one currently delivered by their existing digital or traditional lending.

Lenders, primarily banks, could partner with MNOs, Utilities or large retailers to serve personal customers or industry aggregators that sell or buy products from a large pool of micro-entrepreneurs.

A common collaboration use case is for a lender to join forces with a payment bank and access its customer data in order to grant credit.

Payment banks have a large customer base of the underbanked segments of the population with a unique data history that includes:

  • KYC information.
  • Transactions.
  • CDRs.
  • Location history.


Collaborative Lending provides great value for all the parties involved but also poses some interesting challenges:

1.     Regulatory - can data collected for one purpose be used for another business purpose?

2.     Data Privacy- What data do payment banks need to share with the lenders in order to enable a reasonable risk decision without compromising data privacy?

3.     Technological - Can Collaborative Lending deliver a secure, simple and fast lending process?

4.     Analytical - is there a way in which the vast amount of new data available through Collaborative Lending could be effectively analyzed?

We believe lessons learned in other markets such as the collaboration between Banks and MNOs are very relevant for both the Indian payment and commercial banks.

6 Reasons Your Bank Needs Digitalized Lending

6 Reasons Your Bank Needs Digitalized Lending

Most banks have already integrated a mobile banking offering into their services. Allowing for fund transfer or cash withdrawals without human interaction is not new.

The next step for banks is mobile lending: allowing customers to apply for, receive and access loaned funds instantly and automatically, using only their mobile device. This kind of offering has many benefits, including cutting loan origination costs, lowering risk, reducing loan turnaround times, enabling more customized product offerings and allowing your bank to gain a competitive advantage.

In the Mobile Money Competition, Mobile Lending is King

In the Mobile Money Competition, Mobile Lending is King

Mobile lending holds tremendous promise for mobile money providers throughout the developing world. Mobile money providers have the opportunity to be the market leader in many segments, providing real value to customers in the form of readily available credit. 

Nigeria: Ready for Mobile Lending

Who and where will be the next big success story in lending technology?  Nigeria is the next hot spot for mobile lending—despite the failure of mobile money in the country, and even, perhaps, because of it.

There are three main factors at play: 1) governmental initiatives to improve access to financial services and broadband internet, 2) the rate of growth in both of those fields independent of the government, and 3) the fact that only around 30 percent of people currently have access to retail credit. Taken together, these factors will result in a population using cell phones to access financial services for the first time.

Among the most exciting results of this revolution will be accessible, mobile loans for consumers. A strong desire for credit provides opportunity for a bank to emerge as the leader of Nigerian mobile lending—offering a service no one else can match to a customer base no other bank has tapped.

Using Predictive Analytics to Address the Challenges faced by Growing Online Lenders

Online lenders face a unique challenge. In addition to building an online lending operation that competes with established lenders such as banks and microfinance institutions, these online lenders also need to build an entire credit-related set of analytics tools completely from scratch, relating to credit scoring, credit pricing, credit fraud and portfolio-level analytics.

Paretix is a solution which is ideally positioned to assist bringing these online lenders to market quickly using a combination of an agile cloud-based environment, know-how related to industry best-practices and a platform which helps expedite the process of defining, deploying and enhancing these credit-related analytics.

Mobile and online lending - a threat and an opportunity for traditional lenders

In recent years, alternative lenders have emerged and are now extending credit to unserved or under served market segments such as SMEs, the unbanked or "thin file" borrowers, competing with traditional lenders such as banks, credit unions and microfinance institutions. These alternative lenders utilize state-of-the-art lending platforms coupled with advanced algorithms to extend credit at a lower cost (to the lender) and with very fast turnaround times. This blog post describes the practical steps that traditional financial institutions should take to effectively compete with these alternative lenders.

KCB M-Pesa's Game Changer: What Does Your Bank Need to Do?

With more than one million customers in its first month, the KCB M-Pesa partnership is a clear sign that mobile lending is the future of banking. Banks that do not adjust to this new paradigm risk falling behind and losing market share. What are the implications of this deal for other banks in Kenya, Africa, and around the world? In this piece, we’ll explore: Details of the New KCB M-Pesa Account; What Does This Mean for Banks?; How to Move Forward?

Demystify credit risk modelling for Small and Medium Enterprises (SMEs)

Modelling the credit risk of SMEs is typically challenging. A common mistake when modelling their credit risk is trying to fit SMEs either into retail or into corporate credit risk methodologies whereas the SME segment deserves a unique approach, which is different from these two segments. This blog post describes a recommended approach to modelling their credit risk while taking into account the unique characteristics to small and medium enterprises.