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.

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.

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?

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.