IFC Partnership for Financial Inclusion Field Note: Changing change management

27 Nov 2018
Mastercard Foundation
Picture

The changes involved when a financial institution ‘goes digital’ touches all levels of the business and may even challenge the established business model or institutional identity. The successful implementation of a digital channel thus requires a sound change management plan. Many digital projects that failed or struggled have done so because they did not adequately address change factors such as staff expectations and resistance to change.


IFC's latest Field Note, Changing change management: adapting internal and external culture in times of digital transformation, focuses on the ‘soft’ or interpersonal aspects of digital transformation in the financial sector. It is based on the collective experiences of nine financial institutions over four years and across seven African markets, and presents some concrete advise on how to get change management right to ensure the successful implementation of digital financial services for greater financial inclusion. 

READ MORE

Proving the business case of smallholder finance: 
How sustainable business models can unlock capital for smallholders
26 Nov 2018
Learning Lab, IDH
IDH Trade
Authorship: Clara Colina, Program Manager, Mastercard Foundation RAF Learning Lab; Iris van der Velden, IDH, the Sustainable Trade Initiative

Two-thirds of the world’s 450 million smallholder farmers live on less than USD 2 a day and remain stuck in cycles of poverty. But this pattern doesn’t need to be the norm. Smallholder farmers produce 70% of the worlds food, and economic growth in agriculture is up to 11 times as effective at reducing poverty compared to other sectors. With better access to financial services – such as credit, insurance, and savings – smallholders can invest in the critical inputs, technology and services they need to increase their productivity and ultimately improve their livelihoods to rise out of poverty.

To ensure smallholders have access to finance, and to close the USD 150 billion smallholder finance gap, financial institutions at all levels have a critical role to play.

READ MORE

Learning brief 5: Big data could mean big opportunity: Why we should stay excited for data analytics in smallholder finance
26 Sep 2018
Learning Lab, Dalberg Advisors
Numbers

The fifth Learning Brief in the Lab’s research series, this brief aims to provide a high level understanding of how data analytics is used for smallholder farmers, introduce a new framework to understand the economics of data analytic investments, and highlight key innovators in the space.

DOWNLOAD THE FULL BRIEF

With a USD 150 billion smallholder finance gap, the use of data analytics could be the game change we need to serve smallholders profitably and at scale. And while early signs are promising, there is still a lot of work to be done. To bring data analytics to the next level, it will require a concerted effort from all players. Financial service providers and digital service providers will need to work together on a commercial scale to prove the business case and develop blueprints of success. Meanwhile, donors and investors will need to continue funding more and better innovative solutions to increase the possibility of innovation.

To learn more about the opportunities for data analytics in smallholder finance, download the full brief below.

To understand the return on investment (ROI) on data analytic investments, download the excel tool below. 

...
READ MORE

Featured Posts

Farmland aerial

A global smallholder weather update: Shocks guaranteed, losses optional

Spotlight: The twelfth blog in in the Pulse series offer readers a sector update on the state of smallholder agricultural insurance and the opportunities for elevating those solutions.

Five key insights to consider if you’re thinking about investing in data analytics

Analysis: In early December, the Lab pulled together key stakeholders from across the rural and agricultural finance community to learn more about the opportunity for data analytics (DA).