AI in the financial sector: A few remarks

AI in the financial sector: A few remarks Jorge Sicilia October 2019

AI in the financial sector

AI and big data are proving to be a well of positive innovation.

AI is helping BBVA To better understand the environment in which the banking business develops through the analysis of social dynamics; consumer´s trends; trust in the industry players; but also geopolitical dynamics and their interconnection with the economy (expectations/animal spirits/confidence).

To adjust our strategy and commercial offer to prevailing economic conditions that we can now assess in real time.

To help detect fraud, providing a better customer experience (no joke!)

To generate new high-frequency indicators that complement (anticipate) data published by official statistical institutes to predict the economic cycle and provide more granularity not yet available in official data. Retail sales.

Improve official data with public-private partnerships.

To enrich and personalize our offer to clients by incorporating their data into our analysis and offering them information that allows them to make better decisions.

Financial Health (B Economy; One View)

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AI in the financial sector

Yet AI and big data test the bedrock of the financial sector.

ETHICS

GOVERNANCE

Principles by firms assuring �autonomy, non-maleficence, beneficence and justice�.

TRUST

Processes and technology assuring data anonymity and security.

REGULATION Norms by authorities assuring accountability, non-discrimination, privacy and consumer rights. (Horizontal and sector specific) Data has been at the forefront of all the innovation processes in banking.

The data revolution will change banking services (a market for each customer?).

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AI in the financial sector

As AI and big data reshape the sector …

New set of players Traditional Banks

New business models

Competition framework

?

Platforms Open banking

Fintechs Bigtechs

Broader “experience economy”

Superstar economy Competition for the market (a larger market than the financial one!)

Commoditization within the value chain

Human capital / technology / organization / relation with other firms (all within the realm of general purpose technology)

Access to data as a barrier to entry

Will it be different across jurisdictions?

Regulation will be absolutely key

How will international coordination be?

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AI in the financial sector

… technical challenges to competition and stability arise (an example from AI and markets)

May AIs among different firms learn “optimal outcomes” equivalent to those under explicit collusion?

(Calvano et al, 2019)

May “deep” layers of AI obscure the risk of infrequent but catastrophic systemic dynamics? (a la LTCM)

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AI in the financial sector

And broad market challenges and competition policies are a cause of major concern in some jurisdictions

As sectoral boundaries fade so as to provide a broad experience

Risks to competition and stability arise from unregulated new entrants (Vives, 2018) and also

Network effects and their “tipping points” may in practice

to the customer, opportunities for cross-investment risk hampering competition. (De la Mano and Padilla, 2018).

from a current “information asymmetry” between incumbents and new entrants (at least in Europe). What to do with the competition policy (Europe vs others)

impede any contestability to large players. The “best of breed” principle might not work. Does it matter?

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AI is a disruptive change towards a data based personal experience in banking.

AI will require trust; for which ethics, governance and regulation are key in determining how and by whom that service will be provided and the competitive environment of those services

ANNEX

AI in the financial sector

Eighth challenge

AI and labor

AI is a “prediction technology” “Predicting what a radiologist would interpret from an X-ray, what an interpreter would say of a foreign text or dialogue, what animal would a child think is in a given picture …

AI diffusion is about reformulating old tasks as predictions:

As price for predictions

Predictions are only part of any decision making process, which also include data management, good judgment and decisive action.

falls, the value of complements rise”

SKILL INBALANCE INDICATOR, SPAIN 0,61 0,51

0,51

0,49

0,24

0,22 0,11

Adjustment

0,08 Conscientiousness

Financial and Insurance Activities

0,10

Independence

Simple mean - all economic sectors

0,12

Achievement Orientation

0,06 Judgment and Decision Making

0,10

Computer and Electronics

Note: Positive values indicate skill shortage while negative values point to skill surplus. The larger the absolute value, the larger the imbalance. Results are presented on a scale that ranges between -1 and +1. The maximum value reflects the strongest shortage observed across OECD (31) countries and skills dimensions.

Source: OECD

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AI in the financial sector: A few remarks Jorge Sicilia October 2019