Building an AI-powered financial institution


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For most organizations, the discussion of the benefits and potential of artificial intelligence is much more prevalent than the actual deployment of these technologies there. In fact, most of the use of advanced analytics and AI continues to focus on traditional areas of use, such as risk, compliance, and security. In other areas of the organization, most financial institutions still run only pilots or tests in the most rudimentary fashion.

The inability to understand and deploy AI is further evidence of the challenges faced by most financial institutions in digital transformation. With leadership and culture not embracing the power of AI, it’s difficult to create business cases or integrated solutions that can take advantage of AI opportunities.

Opportunities missed by not fully utilizing the power of AI include massive back office cost savings, dramatically improved customer experiences, improved risk and fraud detection, and other implementations done independently or with strategic partners. In other words, AI and machine learning can have a significant positive impact on the entire banking organization at a time when the risk of not using AI is greater than ever.

It’s time to move from talk to action on AI in banking, no matter the size of your institution.

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AI is a game for the long haul

In an industry where quarterly financial results drive energy and investment, advanced analytics and artificial intelligence require a long-term perspective. In addition, for the deployment of AI to have the greatest impact, there must be a to treat perspective as opposed to a project seen.

The energy and financial investment required in data, advanced analytics, machine learning and AI, while less than in the past, is still not negligible. Therefore, performing modest tests of these abilities will never bring the great victories promised by AI advocates. This underscores the importance of leadership, culture, willingness to change organizational structures, and the scope of AI testing.

AI is the basis of the digital transformation process. It takes more than technology to work. This requires new talent, new thinking and the will to reinvent the bank.

The beauty of AI is that it supports data-driven decision making over time… across the organization. It has the best impact when developed and deployed using cross-functional applications, as opposed to solving small challenges. It’s also most effective when all levels of the organization support AI results. This tends to flatten the organizational structure, as the information is available to more people.

The results of AI deployment should always be tested, with improvements made in an agile environment. This perspective of testing and learning allows constant and continuous improvements in the shortest possible time. This propels pilot cases to larger deployments faster than in the past.

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Reduce costs with AI

By 2030, front-office and middle-office AI applications have the potential to reduce operating costs in the financial services industry by 22%, representing $ 1 trillion in savings total, according to an Autonomous Next report. The report predicts that $ 490 billion of the overall impact of $ 1 trillion will occur in the front office industry through technologies including authentication and biometrics, voice assistants and conversational interfaces.

“Most fintech innovations start with the interaction with the retail customer. Whether it’s putting payments in an app, a bank in your phone, a robo-advisor in a skill for a chat assistant, or your bank in the chat channel inside Facebook Messenger. It’s all about thinking about how to replace customer interaction, ”said Lex Sokolin, global director of fintech strategy and partner at Autonomous Research.

The middle office, which includes compliance, security and risk management applications, is expected to have a cost reduction impact of $ 350 billion by 2030. In these areas, financial services organizations are using the AI technology to replace repetitive processes that can be more easily replicated and improved. . AI is already helping digital lending companies save money (and positively impact the customer experience) by making real-time credit decisions.

Improve customer experience with AI

In a item written by Danial Newman for Forbes, it provides five key ways to positively impact customer experience through artificial intelligence. These include:

  • Empower self-service
  • Improve personalization
  • 24/7/365 real-time availability activation
  • Make everyday life easier
  • Provide consistent customer service

Each customer experience benefit depends on the maturity level of the AI ​​and the data used to deliver a product or service. It also depends on the culture of the organization and the ability of leadership to embrace the internal change required to deploy these solutions.

From chatbots and voice assistants to biometric integration and personalization, the power of AI can have a huge impact on the customer journey and level of satisfaction. One of the unique characteristics of AI in customer support is the ability to learn more about each individual consumer with each interaction.

In the same way that Google and Amazon are able to improve experiences based on an individual’s use of the platform over time, banks and credit unions can improve the advice provided, the offers. proposed and the channels used to communicate based on engagement over time. This type of learning can even help with budgeting and financial recommendations based on how a person manages their money over time.

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Mitigate risks with AI

As mentioned at the start, the first deployments of AI in most financial institutions were in the areas of compliance, fraud and risk. By using financial models and transaction models, organizations are better able to identify anomalies that may indicate potential risks. This is an important area of ​​deployment due to the sophistication of cyber threats and fraud schemes.

“Banks are investing in AI to streamline their Know Your Customer (KYC) processes and to analyze criteria humans cannot detect in the fight against money laundering fraud,” says Business Insider Intelligence, in a recent report. “AI can help banks perform real-time checks on all transactions, improving both reliability and speed over batch processing sample transactions, as well as staying on top of any regulatory changes to ensure compliance with the AML regulatory controls undertaken. “

Deploy AI across the organization

According to Harvard business review, educating the entire organization on the use and benefits of AI cannot be overstated. From senior management to teams, it is imperative to ensure that everyone is on the same page and that processes are standardized across all departments and areas of responsibility.

Equally important, the implementation of AI needs to be stepped up on an ongoing basis to avoid slowing down or the misconception that AI is just “another program”. Role models are important for the success of the program and internal training should be carried out to enable all partners in the process to transform.

Finally, as with any major initiative, the impact of AI must be monitored, measured and reported. Accountability over time between divisions is necessary to support and justify the human and financial commitment to AI.

“The ways in which AI can be used to increase decision making are expanding all the time,” says the HBR. “New applications will create fundamental and sometimes difficult changes in workflows, roles and culture, which leaders will need to carefully manage their organizations. Companies that excel at implementing AI across the organization will find themselves at a great advantage in a world where humans and machines working together outperform humans or machines working alone.


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