credit scoring

the string analytics

credit scoring engine

String Analytics develops custom credit scoring engines that can create credit scores based on a set of underlying data provided by different institutions and different data sources.

The scoring engine runs the credit scoring on a real- time / daily / monthly basis depending on the frequency of receipt of the underlying data. The models deployed are based on Machine Learning algorithms

data processing

The platform is able to process large datasets from multiple data sources
Alternative datasets.
  • Msisdn
  • Topup amounts
  • Topup frequencies
  • Device types
  • SIM activation dates
  • Location data
  • Minutes of use (Onnet & Offnet)
  • Spend on network (sms,airtime,data,bundles)
  • Last revenue generated event.
  • Agricultural input data
Transactional datasets.
  • Loan history
  • Average repayment time
  • Credit score
  • Repayment amounts
  • No of successful repayments
Conventional datasets.
  • Cash deposit/withdrawal amounts
  • Cash deposit /withdrawal frequencies
  • Bill payment info
  • Registration details on mobile wallet/ Bank account
  • Wallet to wallet (account to account) transferdetails
  • Salary details
  • Demographic info
  • Employment info