FREMONT, CA: Corporate finance departments face multiple challenges that technologies like Artificial intelligence (AI) can help overrule. Many financial directors and CFOs understand this fact but are unaware of what needs to be done to maximize outcomes. The undetermined scale and velocity of the challenge is to increase pressure regarding digital transformation by maximizing effectiveness and speed. The danger is of invading the unknown territory of technology without a sense of direction or destination.
• Learn from the Company’s DNA:
As there is no straight line connecting technical capacities of machine learning and business applications for the creation of long term value, the organization must position the technology in a focal point to learn and strengthen its business DNA—a unique pathway to create value for those instances, which are encoded in its data, expertise, processes, and other elements.
• AI Customized to Business’s Needs:
The true essence of strategy is competitive differentiation. To put a value for something when no one else can, to unravel the greatest value from AI is what the corporate finance needs to understand. How does technology fit into the business? How to tailor-make the unique strengths to suit the organization? How can internal processes be streamlined to success? These questions suggest adapting AI to FinTech and then adjusting the finance technology to AI.
• Selecting the Right Course:
The application worth pursuing must compulsorily deliver business values across a minimum of one of the listed dimensions: revenue generation, improved client experience, efficiency gains, and risk management. A typical roadmap effort is mostly an opportunity generation exercise, which reveals potential applications; following it is the segregation of authentic AI use-cases that can be addressed with different solutions combination.
• Extracting Untapped Data for Generating Insights and Automating Processes:
The range of data that can be ingested and acted on by AI is extensive and includes all kinds of data sources such as client or third party, transaction or market data, and structured or unstructured data sources. The holistic extraction of data from varying sources can generate new insights that enable employees to make quick and informed decisions.
The adoption of AI is to balance the short-term value creation and early lessons with strengthening long-term capabilities and vision. The key is to get the ball rolling on the definition of AI with alignment to the company’s DNA and strategic goals.
