AI, Financial Industry, Transformation and Corporate Social Responsibility

It’s been decades since scientists first envisioned human intelligence in machines and, by the end of 2018, visions of the past are becoming every-day realities for more than 80% of all American households. In 2019, it will time for businesses to make the leap, and over 55% major corporate CIO’s have already prioritized Machine Learning in their business acceleration strategies.

After reading the World Economic Forum’s discussion about how AI is ‘transforming the fight against money laundering’ and Forbes 2019 Tech Forecast, it’s become clear that amongst an infinite list of use cases for AI, one of the most compelling is its use in financial institutions.

We all know that in technology and finance, one bright mind can impact the whole organization, so maintaining a fair balance of using AI and creating employment will impact the organization efficiency internally and in the community. With that in mind, it is important to recognize that Today’s talents are very socially conscious and can easily transition from one organization to the other if they do not feel their employer supports their community. This is the time for corporations to take the opportunity to establish or re-establish  their commitment to corporate social responsibility through innovation and creativity. To that end, the partnership between the stakeholders and human resources has never been as crucial as it is today.

With this in mind, below are the highlights of ‘transforming the fight against money laundering’ and Forbes 2019 Tech Forecast.

Financial industry leaders have been cautious of new AI innovations, and reasonably so. Until recently, so-called “black box” models of AI solutions meant that the functions being performed were not transparent to the end users. Without that knowledge, some banks cannot understand it’s technology, let alone explain to regulators how it is being compliant with regulations.

But when five federal US agencies (including the Financial Crimes Enforcement Network) came together last month, they issued a joint statement that would completely change the game. With AI integration as a top priority, the agencies encouraged banks to implement innovative approaches to further the protection of the financial system against unlawful activities.

In order to understand, and reap  the true benefits of, AI, the significance of collaboration (as opposed to replacement) must be recognized alongside the basic foundations.

There are two types of AI and Machine Learning: Supervised or Unsupervised, and both work in conjunction with humans to maximize efficiency.

In supervised learning, machines rely on humans to provide them with categorized data, and  to program them to identify certain patterns or abnormalities. Acting as a Level 1 reviewer, these machines could  identify suspicious financial transactions and alert their human counter-parts to investigate further. reducing the number of false-alerts and allowing humans to utilize their intelligence to verify the  behaviours

In Unsupervised learning, the system uses its own experiences to organize and analyze un-sorted raw data identifying patterns that could signal illicit activities such as money laundering which would then be reported to human-counterparts for further investigation and action. This is of particular use for financial institutions as the systems continuously recognize new patterns that can help differentiate typical banking behaviours from potentially suspicious activities.

Of particular interest, is intelligent segmentation which will allow AI to group customers more distinctly. Traditionally, banks segment their customers based on factors such as industry, business type and size and apply rules that have previously worked for similar customers. While effective, these segments are static and objective and do not consistently represent groups of entities with similar transaction behaviours.

Intelligent segmentation allows the AI system to analyze transactions, observe patterns and create new and more relevant segments that accurately represent banking activities. This would allow for more accurate monitoring of transactions, a decrease in false alerts and increased productivity.

Just the beginning, but never-the-less exciting, 2019 is going to be an exciting year for many industries especially Financial. With a government go-ahead and a strong focus on human-AI partnerships, we’re excited to see how the industry will transform and adapt new methodologies of safety, security and analysis while protecting human jobs.

VTRAC Wants your Opinion!
In your opinion how organizations can expand in AI and modernization while maintaining or exceeding their commitment to social responsibility, starting with maintaining the employment of their own employees?