FinTech Belgium - MeetUp on Digitalisation of Accounting - Edouard Beauvois - Aividens - 14-03-19

1. © AiVidens 2019
Working Capital
Optimization with
Artificial Intelligence
14 March 2019

2. © AiVidens 2019© AiVidens 2019
Starting point
Can we still rely on our habits to portray customers?
What if customers decided not to pay or pay later?
Bad debt and cash flow issues = 25% of SMB bankruptcy cases
Benefit from the
latest
technologies
Be in control of
your risks
Customer Trust as
a new business
indicator!
Working Capital Optimization wtih Artificial Intelligence 2

3. © AiVidens 2019© AiVidens 2019
Example
Rem: average days to payment include overdue invoice
-100
-50
0
50
100
150
200
250
300
350
400
Nombre de Factures
Moyenne de days to payment
Moyenne de days late
# of invoices
Av. Days To Payment
Av. Days Late
2011 2012 2013 20152014 2016 2017 2018
Daystopayment
True case:
• Could we have identified early enough that payment
issues would arise for this customer?
Working Capital Optimization wtih Artificial Intelligence 3

4. © AiVidens 2019© AiVidens 2019
Example
-100
-50
0
50
100
150
200
250
300
350
400
Nombre de Factures
Moyenne de days to payment
Moyenne de days late
# of invoices
Av. Days To Payment
Av. Days Late
2011 2012 2013 20152014 2016 2017 2018
Payment profile: good payer
Payment profile:
average payer
Risk type:
medium
Risk type:
high
Payment profile:
bad payer
Risk type:
very high
Daystopayment
We need to introduce 2 new notions:
• Payment profile
• Risk type
Working Capital Optimization wtih Artificial Intelligence 4

5. © AiVidens 2019© AiVidens 2019
Debt portfolio overview – COMPARE
DSO M-2 M-1 M
84 87 94
DTP M-2 M-1 M
66 69 78
Very Low
19%
Low
39%
Medium
14%
High
12%
Very High
16%
DEBT PORTFOLIO RISK
Your Current Situation
DSO M-2 M-1 M
75 76 74
DTP M-2 M-1 M
66 65 65
Very Low
21%
Low
48%
Medium
13%
High
11%
Very High
7%
DEBT PORTFOLIO RISK
Industry Current Average
Working Capital Optimization wtih Artificial Intelligence 5

6. © AiVidens 2019© AiVidens 2019
Customer view - Bad Payer
Client 1150 – Average # of days to payment
• Top 8 customer revenue wise over the last 3 years
• Revenue for the last 3 years: 1020 keur
• Payment terms: 60 days
• Average DTP last 12 months: 112 days (top 10)
• Average DTP last 36 months: 139 days (top 11)
• # of open invoices within payment terms: 0
• # of open invoices beyond payment terms: 120 (540 keur)
• DSO for period from Jan 2018 to Dec 2018: 300 days
• Immediate action required to recover payment
• Follow up up on 120 open invoices for over than 60
days
• Discuss payment terms with customers
• Additional analysis required
• Overdue analysis for open invoices
KPI’s Key conclusions
-100
-50
0
50
100
150
200
250
300
350
# of invoices
Av. Days To Payment
Av. Days Late
20172016
Payment Profile: Bad Payer
Risk type: Very High
Compare
Your DTP 2018 – 112
Market DTP 2018 - 85
Working Capital Optimization wtih Artificial Intelligence 6

7. © AiVidens 2019© AiVidens 2019
Applied to Working Capital
AiVidens helps companies to further automate cash processes
Segmentation
Predictive Risk
Management &
Alerts
Prioritized worklist
Customer behavior
comparison
Define & automate next best actions
Based on operational data (invoices, payments, orders, write offs, CRM, incidents, other)
Working Capital Optimization wtih Artificial Intelligence 7

8. © AiVidens 2019© AiVidens 2019
AiVidens Value Proposition
Know your customers better than ever
Anticipate payment issues
Reduce outstanding, bad debts and write offs
Improve cash forecast accuracy
Process Automation – Next Best Actions
Working Capital Optimization wtih Artificial Intelligence 8

9. © AiVidens 2019
Appendix
Visit us at www.aividens.com