Financial services in 2030 will leverage big data, machine learning, and AI to provide personalized recommendations and services to customers. Cross-vertical integration will bring in data from various industries to gain more insights. An action plan includes testing recommendations and promotions, investing in data infrastructure, upskilling teams on new technologies, and building partnerships with other sectors. The future will see intelligent virtual assistants like Alexa integrate these capabilities to deliver customized travel planning or financial product suggestions.

1. Financial Services in 2030:
How will Big Data Deliver on Big Promises?
Michelle Katics, CEO and Co-Founder

2. what will Financial
Services look like in
2030?

4. Today:
“I wanttogoon Vacation"
Can we use our points?
Which destinations have
non-stop flights?
Traveller ratings?
Which credit card has the best Forex rates?
How much can I spend on my trip?

5. In 2030:
”ALEXA: I Want to go on vacation”

6. how do we get there?
BIG Data
machine Learning & AI
CROSS-VERTICAL INTEGRATION

7. big data in
banking

8. Big Data: ACTION Plan
Action Plan
1. Test and Learn. Test Tailored discounts, Promotions, Coupons and
Relevant Loyalty offers
2. Reconsider which analytics, data visualization tools, and database
structures you should use. Python? R? SAS? MongoDB? The 'real'
definition of big data is that traditional analysis techniques don't
work.
3. Invest not only in your data lake, but also on data cleansing and data
organization such as data tagging.

9. Example
USE CASE:
ML & AI
Action Plan

10. live example
Value of big data to finance: observations on an internet credit Service Company in China
https://jfin-swufe.springeropen.com/articles/10.1186/s40854-015-0017-2
Examples

11. more examples Examples
30% to 40% lift in Fraud Detection with
no additional false alarms
Luvo: Natural language processing AI
bot
Manual review of 12,000 annual commercial
credit agreements normally requires
approximately 360,000 hours.... the same
amount of agreements could be reviewed in
seconds.

12. action plan: Machine learning & AI
Action Plan
1. Look to other industries for examples, inspiration,
and talent
2. "Stay in your lane" with Machine Learning. Walk
before you run.
3. Upskill and Reskill your teams now - these skills sets
are scarce. Encourage and make space for lots of
pilot tests.

13. Cross-vertical integration What is it?

14. examples: Cross-vertical integration Examples

15. action Plan: Cross-vertical integration
Action Plan
1. Build corporate partnerships which are are data
gold mines
2. Watch consumer, e-commerce and marketing
trends; they are ahead of us
3. Test out every app you can; shopping, transport,
travel.

16. Now, back to ALEXA
BIG Data
ML & AI
CROSS-VERTICAL
1. Always start with the use case,
and the user experience
2. Cross-vertical integration brings
the volume and velocity of big
data
3. Integrate ML and AI as a toolkit
4. Now your intelligence is
actionable.

17. LEARN MORE!
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18. Simulation, Sandboxes, online and Mobile learning
Michelle Katics
CEO and Co-Founder BankersLab
@michellekatics
michelle@bankerslab.com
WhatsApp +65 86503580
www.FinTalent.com
www.BankersLab.com