Collections Target Setting
Only collectible AR is considered for determining collection goals
Disputed AR is taken inconsideration when defining despite resolution targets
A holistic portfolio approach is employed taking customer parent child relationship in
consideration
Collection targets are set based on “Top-down and bottom-up approach ensuring SMART
(Specific, Measurable, Achievable, Relevant and Timely) performance goals
Cumulative daily cash receipts tracked relative to collection goals ensure timely
modification of collection targets and strategies
Dispute Management
Dispute management process can be considered to be continuous improvement in the finance
value chain
Through customer contact barriers to payment are identified. These barriers are errors
that can occur anywhere in the order to cash and forecast to fulfill value chains
Error types, frequency of occurrence, transactional volumes and processing cycle times
are captured to provide valuable insight into process and systems deficiencies
Root cause analysis and reporting is enabling implementation of corrective action
Success of corrective actions implemented is continually monitored and evaluated through
the PDCA loop
Receivables Portfolio Segmentation
Machine learning technology implemented in the collections platform is used to segment
the portfolio automatically and consistently
Inclusion of external data such as geography, demographics, risk profile, etc. enriches
the data and improves the classification accuracy
Collection strategies are configured and assigned to customer segments
Collection campaign deployment and management service is used to execute customer
contact campaigns using methods such as: text messaging, e-mail campaigns, automated phone contact,
predictive dialer managed calls, collector initiated contact, etc.
Performance Measurement
Multiple sources of information are integrated into a data warehouse representing a
single source of truth
Data is at the finest granularity level allowing for drill-downs, drill-ups and
aggregation at any level desired
Combination of disparate data sources provides unparalleled inference into collections
performance, customer behavior, causality of errors, real time cash flow performance and requirements,
and much more
Performance targets and KPIs are implemented at the lowest level of granularity which
enables aggregation at any desired level – collector, department, business unit, country, etc.