XNUMX년 후, FS의 생성적 AI에 대한 전망

XNUMX년 후, FS의 생성적 AI에 대한 전망

타임 스탬프 : 14 년 2023 월 5 일 오전 28:XNUMX
소스 노드 : 3020456

XNUMX 년 전에 ChatGPT launched. The excitement, anxiety and optimism associated with the new AI shows little sign of abating. In November OpenAI CEO Sam Altman was removed from his position, only to return
some days later. Rishi Sunak hosted world leaders at the
영국 AI 안전 서밋, 세계 지도자와 기술 기업가들이 모인 자리에서 Elon Musk를 인터뷰합니다. 그 이면에는 AI 연구자들이 훨씬 더 많은 혁신에 가까워졌다는 소문이 돌고 있습니다. 

AI의 혜택을 원하지만 위험을 확신하지 못하는 산업에 이는 무엇을 의미합니까?

우리가 AI라고 부르던 일종의 기계 학습 형태는 한 세기 동안 존재해 왔습니다. 1990년대 초부터 이러한 도구는 일부 은행, 정부 및 기업 프로세스의 핵심 운영 요소로 사용되었지만 다른 프로세스에서는 눈에 띄게 사용되지 않았습니다.

So why the uneven adoption? Generally, that’s down to risk. AI tools are great for tasks like fraud detection where well-established and tested algorithms can do things that analysts simply can’t by reviewing vast swathes of data in milliseconds. That has become
the norm, particularly because it is not essential to understand each and every decision in detail.

Other processes have been more resistant to change. Usually, that’s not because an algorithm couldn’t do better, but rather because – in areas such as credit scoring or money laundering detection – the potential for unexpected biases to creep in is unacceptable.
That has particularly acute in credit scoring when a loan or mortgage could be declined due to non-financial characteristics – including racial biases.

While the adoption of older AI techniques has been progressing year after year, the arrival of Generative AI, characterised by ChatGPT, has changed everything. The potential for the new models – both good and bad – is huge, and commentary has divided accordingly.
What is clear is that no organisation wants to miss out on the upside. Despite the talk about risks with Generative and Frontier models, 2023 has been brimming with excitement about the revolution ahead.

두 가지 목표

A primary use case for AI in the financial crime space is to detect and prevent fraudulent and criminal activity. Efforts are generally concentrated around two similar but different objectives. These are 1) thwarting fraudulent activity – stopping you or
your friend or relative from getting defrauded – and 2) adhering to existing regulatory guidelines to support anti-money laundering (AML), and combatting the financing of terrorism (CFT).

Historically, AI deployments in the AML and CFT have faced concerns about potentially overlooking critical activity compared to traditional rule-based methods. That has changed over the last 5-10 years, with regulators initiating a shift by encouraging innovation
to help with AML and CFT cases – declaring that innovators will be judged by their overall results not by some missed alerts.

However, despite the use of machine learning models in fraud prevention over the past decades, adoption in AML/CFT has been much slower with a prevalence for headlines and predications over actual action. The advent of Generative AI looks likely to change
that equation dramatically.

One bright spot for AI in compliance over the last 5 years, has been in customer and counterparty screening, particularly when it comes to the vast quantities of data involved in high-quality Adverse Media (aka Negative News) screening where organisations
look for the early signs of risk in the news media to protect themselves from potential issues.

The nature of high-volume screening against billions of unstructured documents has meant that the advantages of machine learning and artificial intelligence far outweigh the risks and enable organisations to undertake checks which would simply not be possible
그렇지 않으면.

Now banks and other organisations want to go a stage further. As Generation AI models start to approach AGI (Artificial General Intelligence) where they can routinely outperform human analysts, the question is when, and not if, they can use the technology to
better support decisions and potentially even make the decisions unilaterally.

규정 준수에 따른 AI 안전

2023년 AI 안전 서밋은 AI의 중요성을 인식하는 중요한 이정표였습니다. 이번 정상회담에서는 28개국이 AI 위험을 해결하기 위한 회의를 계속하겠다는 선언문에 서명했습니다. 이번 행사는 총회 출범으로 이어졌다.

AI안전연구소, 이는 안전성 확보를 위한 향후 연구와 협력에 기여할 것입니다.

AI 대화에 국제적인 초점을 맞추면 이점이 있지만 GPT 변환기 모델은 Summit 동안 주요 초점 영역이었습니다. 이는 익숙하지 않은 개인에게 더 넓은 AI 스펙트럼을 지나치게 단순화하거나 혼란스럽게 할 위험이 있습니다.

AI is not just Generative and different technologies provide a massive range of different characteristics. For example, while the way that Generative AI works is almost entirely opaque or “black box”, much of the legacy AI can showcase the reasons for its
결정.

If we don’t want to go backwards with AI panic, regulators and others need to understand the complexity. Banks, government agencies, and global companies must exert a thoughtful approach to AI utilisation. They must emphasise its appropriate safe, careful,
and explainable use when leveraged inside and outside of compliance frameworks.

앞서가는 길

The compliance landscape demands a review of standards for responsible AI use. It is essential to establish best practices and clear objectives to help steer organisations away from hastily assembled AI solutions that compromise accuracy. Accuracy, reliability,
and innovation are equally important to mitigate fabrication or potential misinformation.

Within the banking sector, AI is being used to support compliance analysts who already struggling with time constraints and growing regulatory responsibilities. AI can significantly aid teams by automating mundane tasks, augmenting decision-making processes,
and enhancing fraud detection.

The UK can and should benefit from the latest opportunities. We should cultivate an innovation ecosystem with is receptive to AI innovation across fintech, regtech, and beyond. Clarity from government and thought leaders on AI tailored to practical implementations
in the industry is key. We must also be open to welcoming new graduates from the growing global talent pool for AI to fortify the country’s position in pioneering AI-driven solutions and integrating them seamlessly. Amid industry change, prioritising and backing
responsible AI deployment is crucial for the successful ongoing battle against all aspects of financial crime.

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