Artificial Intelligence To turn data into Intelligence Brian Morgan FCICM Business Growth & Partner Director
We exist to simplify the complex Software that finance people love
Challenges Rigid Unintelligent Difficult to Performance Reporting change process Management Cash Flow Not Real Reactive, Visibility of Customer Forecasting Time not Proactive Cash Activity Relationships
Typical Cash Allocation Process Receive & File 30% of Manual Effort Remittances & Cheques File Remittances in Order Value Matching 40% of Manual Effort Bank Statement/File Purge Unmatched Remittances 30% Keying Unmatched receipts to customer account or Phone: +44 (0) 1527 872 123 of Manual Effort suspense enquiries@rimilia.com | www.rimilia.com
Typical Cash Allocation Process Receive & Scan 30% of Manual Effort (not all remits require scanning) Cheques & remits scanned and Remittances & Cheques data extracted 10% Matching of Manual Effort (automated matching) Electronic Bank Statement Data Automated Matching Software 0% Keying File Uploaded to Sales of Manual Effort Ledger Phone: +44 (0) 1527 872 123 (Auto upload) enquiries@rimilia.com | www.rimilia.com
Industry-leading utilization of AI for faster, quicker, better decision-making
What is the impact of implementing Collect?
Collections is a complex process, a balance between managing debt effectively and handling customers sensitively External Internal Economic Conditions Cost Containment The unsettled economic climate is leading to increased Utilising scarce resources to produce the best financial stress on SME Businesses . outcome for all in the collections process. Customer Experience Maximize recoveries Customers expect personalised & relevant digital Increasing the amount of cash collected by creating journeys. Consumers and Businesses now look to nurture more effective processes and treatment strategies. their own credit score. Identify the non-compliant customers from the vulnerable segments Increased Competition Customer Insight Open Water has enabled customers to easily switch Use data to develop more personalised interactions providers increasing the importance of your brand. and billing cycles influencing behaviors to improve results. Regulatory Compliance Greater focus on the fair treatment of Consumers and Businesses with a holistic view of ALL customers.
Multiple data items – One location. Data Assets Standalone Scorecards Affordability Fraud Companies Adverse Scores Indicators House Data Data Risk Vulnerability Scores CATO Data Voters Roll Scores Improved Customer Insight Regulatory Compliance Enhanced Strategies Advanced Reporting
Impact of Predictability DEBTOR PREDICTABILITY Preditable Unpredictable 41% 59% How does this impact on your collections?
With some rules and some automation you can predict With utilisation of AI and ML, you can predict at least Only 4% of debtors with 70% Accuracy or more 48% - %50 of debtors with 70% Accuracy or more Rimilia AI Engine
Defining Automated Treatment Paths Customers who pay on receipt No reminder until unpaid trigger of bill statement date Customers who pay on receipt Reminder letter with X days of reminder Customers who pay on verbal No reminder letter – Outbound contact call Customers who always pay on No reminder until unpaid trigger the same date date Outbound DD conversion campaign
Information never changed anything Application brings transformation
Turning Information into Intelligence into Wisdom
Our Customers Finance pioneers who want to make a significant difference because they know “we have always done it this way” is the wrong answer
Extract from South Staffs Water PR19 “ Our openness to innovation has continued with our new debt management system. We have carried out an extensive review of the systems currently available because we wanted something that truly broke new ground. So, in another first for the sector, we are currently implementing a debt management solution that embeds artificial intelligence (AI) to create highly-tailored, individual customer journeys for debt management. More importantly, the AI will identify early changes in customer behaviours, which can be an indication of more wide-ranging financial problems and enable us to proactively support these customers before they fall into debt. Our new debt management system will allow us to develop real-time collection strategies, using a number of customer behaviour traits. The management information we will have access to will give us a detailed picture of debt management reported, for example, by strategy, age or vulnerability. And because it will enable real-time, constant monitoring, it means we will be able to proactively tailor our responses to individual customer circumstances ”
Why Rimilia Collect? 1. Need for Cash 2. Reduce Bad Debt 3. Treat Customers fairly • Strategies for each type of Customer • Sub-Strategy for every change to a Customer • Communication path and method to suit customer 4. Measure activity – use AI to be smart and increase Productivity 5. Functionality • Payment plans • Reporting - including cash flow • Dynamic Diary
Why Rimilia Collect? Proven up to: • 89% reduction in 60 day aged Debt. • 70% reduction in 6 months+ in aged Debt. • 160% Increase in amount Collected per call. • 60% Increase in Average Collections per day. • 51% of those forecasted customers accurately predicted within 3 days either side of the forecast date.
Why Rimilia Collect? • Significant reductions in bad debt provision. • Cash collection targets set from working day one. • Estimated Head count reduction = 25% overall FTE count. • Multiple Collection strategies and workflows will allow improved collection activities. • Ability to import CRA data to enhance collection strategies. • Multiple contact strategies – Print, E-mail, SMS. • Dynamic Diary system automating collection paths. • Integration of Cash and Collect – Resulting in automatic allocation of payments, allowing collectors to only contact those that have not paid. • Credit Controllers do the right thing at the right time.
Software finance people love email brian.morgan@rimilia.com tel 07470 453 177 | rimilia.com
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