Managed Chaos: Keeping Track of Agents
In the past few weeks, my colleagues have blogged about our study of agent networks in India. You can see our overall analysis of agents (called CSPs or Customer Service Points in India). The India research was one part of a three-country study (along with Brazil and Kenya) that highlights the critical role agents play as the key interface between branchless banking providers and customers.
In this post, we look closely at FINO. FINO has 10,000 agents, distributed across 25 different initiatives with nearly 40 financial institutions, with more than 13 million registered users accessing a range of products from no frills saving accounts to NREGA government benefits to microloans and insurance.
FINO started life as a firm focused on banking technology, but necessity has forced FINO to become skilled in agent network management as well. By some measures, FINO is the world’s largest agent manager. FINO is putting together some tools we’ve not seen in Brazil and Kenya, countries which get a lot more attention in branchless banking.
FINO’s solution starts with something deceptively simple. Every field staff member sends a SMS to headquarters when they leave home and head for the field each morning: almost like taking attendance. FINO then melds this with transaction data showing when and where field staff meet agents, and the transaction details of agents and customers, yielding a massively data-rich mash up which FINO color-coordinates, uses to generate scores for every staff member, and makes sortable. The end result converts tens of thousands of data points into an easily absorbed visual interface. And this is all online, easily accessible to FINO staff.
When I saw it, it comes across as a system designed to provide not perfect information, but “good enough.” For instance, a dishonest staff member could send a text from bed saying he was in the field. But as FINO’s Jatinder Handoo puts it, “You cannot lie forever.” Absences will appear. Other data will show that staff person’s agents do not perform as well, that clients don’t transact as often.
The key is pattern recognition. That’s where the color coding, scoring and sortability of FINO’s system comes into play. The worst performers slide to the bottom, and two staff in headquarters in Mumbai are able to follow up over the phone, typically on the same day. FINO can also single out the best agents to examine more closely. In the long run, this should provide a goldmine of data helping FINO improve its agent networks, and ultimately the quality of financial services it delivers for its partners.