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

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

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

  1. 1. © AiVidens 2019 Working Capital Optimization with Artificial Intelligence 14 March 2019
  2. 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. 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. 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. 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. 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. 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. 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. 9. © AiVidens 2019 Appendix Visit us at www.aividens.com

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