Fintech. May 18th 2018. Data Driven Innovation 2018. Engineering Department, University of Roma Tre

1. Applying deep learning tools to data available at the banking industry level
Pietro Scabellone
ABI – Associazione Bancaria Italiana
p.scabellone@abi.it
DATA DRIVEN INNOVATION - Rome 2018 Open Summit
Fintech, Room N4: May 18, 2018

2. 2
AI IS THE ANSWER
Artificial intelligence is the answer, but to which question?
AI not only serves to promote efficiency and cost savings
USE CASES
Interventions on the business model, creating innovation in customer services, optimization of business
processes: does all of this involve new risks?
AI & COMPANY SIZE
The AI approach is independent of the market position
HUMAN RESOURCES
Recruitment, training, motivation and inter-functionality
DATA QUALITY
Data quality is the starting point, but also a target of the AI.
TWO OR MORE TECHNIQUES TOGETHER
Mix computer vision, sensor fusion, unsupervised & deep learning...
MODEL TRAINING
To what extent is model training to replace data collection?
Introduction

3. 3
Innovation is also to apply new approaches to well-known matters.
An example: a multiplication table network
• Artificial Intelligence is not yet
a commodity: it requires
innovation
• Success comes gradually,
through a series of minimum
viable products
Time
Velocity
Innovation is learning

4. 4
Cf. La qualità della regolazione nell’esperienza della Consob, DP CONSOB n. 6, aprile 2016
Example #1: innovation and economic impact assessment
Measurement of administrative burdens:
from business management ("network") of obligations ("nodes") to cost measurement

5. 5
Stanford Artificial Intelligence Index
AII
• Artificial Intelligence doesn't
rely only on data, GPU, and
memory
• Today, "AI-learning" is more
a human need than for the
machine
In Computer Science (CS), publications on artificial intelligence are growing strongly
Link:

6. 6
Stanford Artificial Intelligence Index
• In model training, it is always
useful to consider the human
performance as a benchmark
In some fields, the (best) performance of artificial intelligence exceeds that (average) of man
AIILink:

7. 7
Example #2: US Consumer Complaint Database
CFPB
Model training from public complaints about companies
Link:

8. 8
Kaggle
Example #2: Classifying Consumer Complaints
Link:

9. 9
Applying weighted co-expression network analysis (WGCNA) to operational losses (DIPO)
Category
time
• Step 1: Data viz and cleaning
• Step 2: Clustering events and losses
• Step 3: Identifying functional modules
• Step 4: Building the network
• Step 5: Hubs identification
and events interaction
• Step 6: ...
WGCNALinks: DIPO
Example #3: Operational Risks

10. 10
Analytics and artificial intelligence boost performance and opportunities for the whole economy
Conclusions
LOOPYLink:

11. 11
Thank you!