Under the epidemic, major financial institutions focusing on offline exhibition are accelerating the online transformation, and the application of artificial intelligence technology in the financial field is accelerating. Deloitte analyzed how financial institutions deal with the risks brought by artificial intelligence and benefit from it, in order to enlighten enterprises.
Financial institutions accelerate online transformation
Affected by the epidemic, all industries are actively exploring the “zero contact” online service or production mode. In the past, significant changes have taken place in financial institutions dominated by offline exhibition.
The summary of changes in the financial industry under the epidemic situation is mainly reflected in four “accelerations”: “first, the online acceleration of customer behavior; second, the intelligent acceleration of business delivery; third, the acceleration of financial institutions’ shift to lean operation; fourth, the acceleration of technological innovation of financial institutions.” as one of the important technologies in the development of online mode, artificial intelligence, In this epidemic, the accelerator button was pressed.
As the offline service and marketing mode is forced to stop, financial institutions will accelerate the construction of online mode, and intelligent applications will usher in further development. In the short term, artificial intelligence will be widely used in front customer service and middle and back office delivery of financial institutions.
Artificial intelligence admission: risks and opportunities coexist
It is generally believed in the industry that the high degree of data in the financial industry and its clear business rule objectives are the best application scenarios of artificial intelligence technology. As early as 2018, the integration of artificial intelligence and the financial industry has begun. At present, the rise of a new generation of artificial intelligence in the world has injected new impetus into economic and social development. Artificial intelligence will also bring more possibilities to the financial industry.
However, in this unknown ocean, there are still many challenges and uncertainties. How should financial institutions effectively deal with risks?
Ozmca summarizes and analyzes the main risks of using artificial intelligence in the current financial field, among which interpretability, systemic risk and discrimination and justice are the three most concerned key issues.
1、 Interpretability of artificial intelligence. With the development of technology, artificial intelligence is becoming more and more complex. Sometimes it is difficult for developers to fully understand the reasons and logic of artificial intelligence decision-making, so there are huge risks. Financial institutions need to establish a balanced informed trust to improve interpretability by improving transparency.
2、 Systematic risk of artificial intelligence. When financial institutions adopt artificial intelligence for decision-making, their interpretation of market signals tends to converge, resulting in the continuous strengthening of the impact of a market signal and the result of deviating from the normal market law.
These abnormal market changes will become the learning basis of artificial intelligence and further distort the decision logic of artificial intelligence, resulting in bad consequences. In order to deal with this problem, financial institutions should reduce systemic risk by strengthening the capture and reporting of key market signals, adopting interactive artificial intelligence decision engine and circuit breaker tools.
3、 Discrimination and equity. Discrimination in the financial system mainly includes human discrimination, data discrimination, model discrimination and indirect discrimination. Financial institutions should strengthen anti discrimination training for employees, promote workplace diversification, and monitor and correct potential discrimination through existing statistical analysis tools. At the same time, solving this problem also requires the joint efforts of policy makers and financial institutions.
In addition, there are other uncertain factors in AI in the financial field, such as algorithm trust, algorithm collusion and so on.
With the rapid development of technology, artificial intelligence is increasingly involved in the reform of the financial industry. Financial institutions should face up to technology, actively change and seize opportunities.
Ozmca made five suggestions to financial institutions: “First, value guidance. Any AI research and application should take the output of business value as the core goal; second, strategy first. Financial institutions should take a comprehensive view of the opportunities and challenges brought by AI, re conceive the new business model in the era of data and AI, build their own ‘data flywheel’ model, and refine the construction tasks and functions of AI Application scenarios; third, comprehensive transformation.
Financial institutions should expand their attention to the technology itself to the systematic application of artificial intelligence, and comprehensively reshape their core capabilities from the organizational mechanism, talent team, corporate culture, business model and technical basis around artificial intelligence; fourth, from point to area, financial institutions should find appropriate core artificial intelligence scenarios and quickly Start construction and agile iteration to achieve the best results, and condense methods and capabilities on this basis to promote large-scale application; fifth, strategic determination. Financial institutions should clearly recognize the value of artificial intelligence and resolutely invest resources to promote change. “