20151009 presentation predictive banking
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During the Innovation Bootcamp of ING Commercial Banking I gave this inspirational presentation about 'Predictive Banking' - How can you use (big) data analytics for improving your products and services. The video of this presentation can be watched on www.finno.nl/videokanaal or https://www.youtube.com/watch?v=R1-vAEU4s5E
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20151009 presentation predictive banking
- 1. Innovation Bootcamp Commercial Banking Pascal Spelier, October 9th 2015 Predictive Banking, Two Steps Ahead
- 2. 2 Customer Distribution / Front Office Manufacturing / Back Office Market Infrastructure Individual Institution Investing/ WealthMgmnt Personal Savings Lending Capital Raising Source: based on illustration ‘Financial Services Value Chain Supermarket Age’ by Doug Nelson Payments = flow of capital Current value chain is under pressure…
- 3. 3 Customer Distribution / Front Office Manufacturing / Back Office Market Infrastructure Individual Institution Investing/ WealthMgmnt Personal Savings Lending Capital Raising Source: based on illustration ‘Financial Services Value Chain Next Gen’ by Doug Nelson Payments …Financial services unbundled and revisited Independent, digital front ends API-driven middle- and back office Electrification of market infrastructure Independent, digital front ends and middle- and back office
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- 6. 6 715 MB DNA information in a sperm cel
- 7. 7 105 million GB in an ejaculation
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- 9. 9 95% of current Big Data is created in the last 3 years Volume Velocity
- 11. 11 Big Data no longer a hype
- 12. 12 The new technology gold rush: data
- 14. 14 From data to information, From information to intelligence
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- 17. 17 Deep dive in two big data opportunities Cross channel ‘relevancy engine’ Real-time credit risk management
- 18. 18 Deep dive in two big data opportunities Cross channel ‘relevancy engine’ Real-time credit risk management
- 19. 19 Forecasts project the past into the future. Thats reasonable when nothing changes.
- 20. 20 “But don’t be a Turkey!”* 1000 and 1 Days in the Life of a Thanksgiving Turkey *) Nassim Nicolas Taleb
- 21. 21 VW scandal: Final bill could reach $55 billion Did you predict this ‘black swan’?
- 22. 22 It’s about real-time data
- 23. 23 FICO Credit Scores: 15-20 variables ZestCash: Thousands of indicatorsVS
- 24. 24 “All Data is Credit Data, we just don’t know how to use it yet” Douglas Merrill – CEO ZestFinance (former Google CIO)
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- 32. 32 Watson has the cognitive capacity to analyse unstructured data and make an immediate, rational assessment of risk
- 33. 33 Deep dive in two big data opportunities Cross channel ‘relevancy engine’ Real-time credit risk management
- 34. 34 Cross-channel ‘Relevancy Engine’ Observation (data & information) Trigger (right message, right channel) Interpretation (intelligence) Reaction (call to action)
- 35. 35 Observations… … in the de customer journey (also outside the borders of the organization!) … in processes … in transactions … in the context
- 36. 36 Observation Interpretation Message Reaction Via an API with the accounting software the bank has access to the real-time financials, including rolling forecast of Company X. The financials indicate that the agreed overdraft limit will be exceeded within a few weeks.. Based on a borrowing base related to outstanding debtors and current ratio’s Company X is eligible for an extra facility. The CFO of Company X receives an alert on his smartphone with a binding offer for an extra facility. The CFO has the possibility to accept the offer. He also has also the possibility to contact his relationship banker via (video)chat. Better services & more sales with relevant & personal messages
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- 40. 40 Observation (data & information) Trigger (right message, right channel) Interpretation (intelligence) Reaction (call to action) Cross-channel ‘Relevancy Engine’
- 41. 41 richness - + confidential - + urgent later now relevant 1-n 1-1 intrusive - + archive - + richness - + confidential - + urgent later now relevant 1-n 1-1 intrusive - + archive - + Message Channel Match Find the ideal match between message and channel
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- 44. 44 Source: online survey Edelman ‘Brandshare’ 15.000 respondents in 12 countries Privacy as a currency
- 45. 45 Awareness Orientation Buy Receive Use Service Advice Retention Prerequisites for creating predictive services in commercial banking 360° customer view (Social-CRM) Workflow management Social listening / external data sources Datawarehouse / realtime data Big data analytics / predictive modelling Digital marketing- & campaigns (inbound)
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Notes de l'éditeur
- Distribution / Front Office: The owner of the customer relationship, either through an individual adviser or banker, a physical branch location, or more recently, a captive, online front-end. Manufacturing / Back Office: The product creator (e.g., asset manager or underwriter) as well as back office activities like trade execution and loan servicing. Market Infrastructure: The “guts” that intermediate asset transfer, including exchanges, market makers, central clearing houses, and settlement providers.
- 1. Independent, digital front ends. A number of companies have achieved quick traction through replacing the human, face-to-face interaction with a beautiful online user experience for basic product selection (e.g., Wealthfront for managed accounts or Simple or Moven for personal banking). Traditional firms that have built their own front ends have been slower to innovate in UX / UI, driving the adoption of independent budgeting tools like Level and trading tools like ChartIQ and eSignal. 2. API driven middle / back office. As discussed, most of the new applications have been built on legacy infrastructure (and although marketplace lenders have dipped further into the traditional bank’s territory with underwriting and loan origination, they still often use banks for regulatory reasons or to raise capital). However, in order to enable the next generation of front office, developers need open, well-documented APIs, which many old-world firms either poorly support or don’t offer at all. To solve this problem, a few new startups have gone to market with an API-driven offering — for instance, Standard Treasury in banking or Tradier in online brokerage. 3. The electronification of market structure. This is an old story for many financial markets, with the complete transformation of equity and FX market structure over the past 20 years due to electronic trading (and several new venues that would be seen as “unicorns” today). Regardless, many capital markets are still intermediated by bilateral, voice-driven trading methods, and central clearing firms like the ACH, DTCC, CME and others haven’t changed workflows for many years. Partially driven by regulation, other asset classes liked treasuries, corporates and OTC derivatives are undergoing their own revolutions. Even further on the horizon, the use of blockchain technology for smart asset transfer could replace these intermediaries entirely.
- 150 miljoen zaadcellen, per zaadcel 715 MB aan DNA informatie 150 miljoen x 715 mb = 107.250.00.000 MB per zaadlozing = 104.736.328,125 GB
- 150 miljoen zaadcellen, per zaadcel 715 mb aan DNA informatie,
- Value wordt weleens de 5e V genoemd
- Nassim Nicolas Taleb, writer of the book ‘The Black Swan: The Impact of the Highly Improbable’. Black swans’s refer to unexpected events. “I am interested in how to live in a world we don't understand very well - in other words, while most human thought [particularly since the Enlightenment] has focused us on how to turn knowledge into decisions, I am interested in how to turn lack of information, lack of understanding, and lack of "knowledge" into decisions - how not to be a "turkey".'
- FICO credit scores, thought to be based on 15-20 variables, such as the proportion of credit that is used and whether payments have been missed, ZestCash looks at thousands of indicators
- Aanvraag wordt binnen 2 minuten beoordeeld. Binnen 15 minuten het geld op de rekening.
- Recently their first one billion in loans. Of course, still a drop in the ocean of credits.
- Transactional data, credit data, social data, proprietary data, accounting, government & public records
- Their business model is designed to address the lack of Big Data utilized by banks. Credit Benchmark curates and catalogues analytics into their consensus data platform. They’ve pooled this securely and anonymously with data from the world's largest banks (8), reflecting not only the views of the banks' own risk teams, but that of the numerous other criterion examined by Big Data platforms.
- Ken Jennings had the longest unbeaten run at 74 winning appearances, while Brad Rutter had earned the biggest prize pot with a total of $3.25 million. Rutter and Jennings were Jeopardy-winning machines. And in early 2011, they agreed to an exhibition match against an opponent who'd never even stood behind a Jeopardy podium before. But this Jeopardy unknown had spent years preparing to take on the two giants in the $1m match, playing 100 games against past winners in an effort to improve his chances of winning.
- Bewerkbare plaatje zit eronder!
- Deelnemende landen: USA, UK, China, Japan, Brazilie, Nederland, Frankrijk, Duitsland, Mexico, India, Canada, Australie http://www.edelman.com/post/financial-services-companies-meeting-consumers-needs/
- Als je de customer experience echt wilt verbeteren dan red je het niet met cosmetische ingrepen aan de voorkant; een mooie app of website. Die app en website moeten geintegreerd zijn met je achterliggende processen en systemen. Als je vernieuwende customer journey’s wilt realiseren, zoals genoemd in deze presentatie, dan komt daar veel meer bij kijken. Voor een digital customer experience zijn een aantal achterliggende systemen van essentieel belang. Hoewel dit overzicht niet uitputtend is, vormt het wel de basis voor een optimale digital customer experience. Allereerst is een 360° klantbeeld essentieel. Iedereen heeft het daarover, maar heeft iedereen ook een 360° klantbeeld? Zijn ook de social media accounts van de klant geïntegreerd in het CRM? Ook moet je als organisatie goed inzicht hebben in de workflow je processen, bijvoorbeeld het aanvragen van complexe verzekering. Als je zelf dit inzicht niet hebt, dan kun je ook je klant dit inzicht niet geven. En de klant wil dit inzicht. Uiteraard is webcare niet meer weg te denken. Er wordt in social media al veel geluisterd naar klanten. Maar wat doe je met die informatie. Hoe verleidt je klanten in social media om bij jou producten te kopen? En in hoeverre maak je gebruik van externe databronnen, zodat je meer over de klant te weten komt en de klant ook minder hoeft te vragen? Met al die data is uit processen, systemen, social media en externe bronnen is het wel goed om die data een goede plek te geven. Als de data goed te ontsluiten is en bij voorkeur ook realtime beschikbaar is dan ben je klaar voor de volgende stap: het analyseren van die data en predictive models bouwen. Deze analyses en de uitkomsten uit de modellen zijn de input voor je digitale marketing en digitale campaigns. Deze campagnes zijn bij voorkeur natuurlijk inbound. Kortom, wil je de customer experience echt verbeteren dan is dat niet alleen het feestje van marketing, maar ook van ketenregiseurs en IT-specialisten in de onderneming. Samen creeer je de digital customer experience, waarmee je niet alleen klanten voor je wint, maar ook voor lange tijd aan je bindt.