Artificial Intelligence (AI) and finance have become tightly intertwined, revolutionizing how financial institutions operate, make decisions, and serve their customers. The integration of AI into finance is driving unprecedented levels of efficiency, accuracy, and innovation, shaping the future of the industry.

The pace of AI application in Financial Services is clearly accelerating as companies begin to leverage AI to increase profitability and achieve scale. This has complicated and multifaceted implications and repercussions.

Some Key findings are:

  • AI is expected to turn into an essential business driver across the Financial Services industry in the short run, with 77% of all respondents anticipating AI to possess high or very high overall importance to their businesses within two years.
  • The rising importance of AI is accompanied by the increasingly broad adoption of AI across key business functions. Approximately 64% of surveyed respondents anticipate employing AI in all of the following categories – generating new revenue potential through new products and processes, process automation, risk management, customer service, and client acquisition – within the next two years
  • Risk management is the usage domain with the highest current AI implementation rates (56%), followed by the generation of new revenue potential through new AI-enabled products and processes, adopted by 52%.
  • Incumbents expect AI to replace nearly 9% of all jobs in their organization by 2030, while FinTechs anticipate AI to expand their workforce by 19%.
    Regardless of sectors and entity types, quality of and access to data and access to talent are considered to be major obstacles to implementing AI.

What Pinnacle AI® can do for you?

Understand the Requirements:

Define the purpose and terms of the Contract we want to create. Understand the key clauses, conditions required for contract.

Select the AI Tool:

Choose a reliable Generative AI tool that specializes in natural language processing.

Natural Language Processing (NLP):

Evaluate the NLP capabilities of the AI-ML model to accurately interpret and understand user inputs for contract drafting.

Input the Data:

Provide the AI tool with the necessary inputs. This might include the names and addresses of the parties involved, specific clauses, payment terms, project details, timelines, and any other relevant information.

Validate the possibilities of use case:

Provide customer with a multiple use case which helps them evaluate the next steps of building the Contract writing AI-ML product for user consumption.

Cost-Benefit Analysis:

Analyze the costs involved for customer in implementing the AI-ML contract writing solution against the benefits it offers in terms of efficiency and accuracy.

Use Cases of Finance