6 Adoption Essentials for Generative AI in Financial Services

Generative AI in Financial Services

Last Updated on April 8, 2024 by Team Experts

Over 80% of firms plan to learn more about generative AI technology and the possibilities it offers over the course of the next 12 months. According to research by Accenture, 98% of worldwide executives concur that AI foundation models would be crucial to their businesses’ goals during the next three to five years. It is logical. After all, the possibilities that this new technology is creating are endless.

Although artificial intelligence (AI) is not a new concept, the machine learning algorithms that underpin products like ChatGPT and DALL-E have advanced to new levels, and their applications are just now becoming clear. People are beginning to wonder what has to change in the way we conduct business in light of these new technologies.

AI in financial services

An industry that uses a lot of data, notably in the banking and insurance sectors, is financial services. According to research from the Economist on early adopters of AI in corporate America, it’s not surprising that the generative AI in finance services business is the leading industry sector in artificial intelligence.

Financial services have a head start in understanding the potential for generative AI, including both possibilities and threats, according to their expertise with AI. Opportunities to provide better customer service, cut expenses, and comply with regulations, but also concerns related to how data is utilised and responsible tool use. To adequately reduce these risks, a defined structure is required.

While Gen AI products presently have ‘wide’ applications, it won’t be long until the industry has ‘foundational models’ – pre-trained for many industries and giving a number of options for balancing size, transparency, adaptability, and performance. As soon as they’re in place, these new AI systems will give you the ability to:

  • boosting productivity
  • unleashing creativity
  • optimising costs
  • offer equal opportunities

We have already seen instances of businesses leveraging Gen AI techniques to build highly individualised marketing that interacts with clients in various ways according to their habits. Emerging patterns are being captured through synthetic data creation, and Gen AI systems can digitally evaluate and enter data into business applications.

Generating better outcomes with AI

Consider that you are an insurer. The quantity of paperwork your clients have to fill out is one of their most common complaints, according to you. Imagine that instead of completing a form, your client could speak with an AI avatar that would gather the required data and fill up the form for them to see. The next-generation artificial intelligence application merely utilises the data you currently have on file and then queries your customers to fill in the blanks as necessary. This would significantly reduce friction from the customer experience in a crucial situation with increased stress for the consumer.

Similar to this, consider hiring a new employee for your call centre. Although this agent is prepared to interact with your consumers, they are unsure of where to go for all the information they may want. A service person may rely on these details since generative AI can be designed to search your company’s papers and to bring up pertinent information within a set scope. The client may get each response provided by the AI verbatim or as a link once the service agent has verified it by looking at the information’s source. This increases the accuracy of first call resolution for the client and enhances the agent’s experience by supporting knowledge growth and productivity.

Thirdly, Gen AI can help employees who feel that email correspondence consumes a significant amount of their day by composing emails using the user’s preferences. For instance, if a customer writes with a specific request, the AI tool may prepare a response with the choice to either acknowledge the email with empathy, produce a report, or reply with a solution that refers to a certain area of the PDS. once again, enhancing both the knowledge worker’s and the customer’s experience.

How to get started with Gen AI

There are six fundamental adoption strategies that are advised in order to effectively accept and benefit from the generative AI era. Which are:

1. Get started with a business-focused attitude: Learn how Gen AI will improve your organisational structure and how you can eliminate silos to foster the kind of cooperation required for creativity.

2. Put the needs of people first: What are the time-consuming and tedious chores that your customers or workers find? Is this something that a future AI tool could do or help with?

3. Prepare your confidential information: No matter what you do, the quality of the result depends entirely on the input. Make sure your papers are accurate if you want a Gen AI tool to use them to deliver information.

4. Contribute to a foundation for green technology: Think of your needs as ranging from supporting experimentation to scaling up into production for your infrastructure, architecture, operational models, and governance structure. Do make sure you comprehend how future challenges will affect these.

5. Quicken the development of ecosystems: Consider how rapidly you will need to adapt to maintain learning as the industry develops, as well as how you can take use of the industry best practices and insights provided by ecosystem partners including large tech companies, start-ups, professional services companies, and academic institutions.

6. Employ your ethical AI: With consumers in the financial services industry, trust is crucial. Do your homework, evaluate the hazards, and establish a risk mitigation strategy before incorporating any Gen AI technology. Integrate continuous controls for evaluating this risk, and encourage ethical AI practises across the organisation.

Get going

Gen AI tool implementation and customization in your firm demands the same careful analysis and deliberation as implementing any other significant change. It pays to think about how and where you can best take advantage of this new opportunity since these technologies will radically alter how the financial service business is formed.

Read more: The Future of AI is No-Code: Discover the Benefits of No-Code AI Platforms


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Anil is an enthusiastic, self-motivated, reliable person who is a Technology evangelist. He's always been fascinated at work especially at innovation that causes benefit to the students, working professionals or the companies. Being unique and thinking Innovative is what he loves the most, supporting his thoughts he will be ahead for any change valuing social responsibility with a reprising innovation. His interest in various fields and the urge to explore, led him to find places to put himself to work and design things than just learning. Follow him on LinkedIn

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