Financial planning is a complex and dynamic process that involves collecting, analysing, forecasting, and reporting financial data for various purposes. Financial planners need to deal with multiple sources of information, such as client profiles, market trends, tax regulations, investment options, and risk factors. They also need to provide timely and accurate advice to their clients while ensuring compliance with ethical and legal standards.
However, financial planning is also full of repetitive and tedious tasks that consume a lot of time and resources. For example, financial planners may need to manually enter data from different sources, validate transactions, generate reports, update records, send emails, schedule appointments, and more. These tasks not only reduce the efficiency and productivity of financial planners but also increase the risk of human errors and fraud.
This is where robotic process automation (RPA) and artificial intelligence (AI) can help. RPA and AI are two emerging technologies that can automate and optimize various aspects of financial planning. RPA is a software that can mimic human actions and execute predefined rules on structured data. AI is a broader term that encompasses various techniques that can mimic human intelligence and perform tasks that require judgment and learning on unstructured data.
By combining RPA and AI, financial planners can achieve what Gartner calls “hyper-automation” – in which entire processes, not just tasks, are automated. This can result in improved efficiency, accuracy, speed, compliance, and customer satisfaction. Here are some examples of how RPA and AI can work together to transform a financial planning business digitally:
- Data collection and integration: RPA can automate the process of collecting data from various sources, such as bank statements, tax returns, investment portfolios, market reports, etc. AI can then analyze the data and extract relevant insights, such as cash flows, risk profiles, financial goals, etc. This can help financial planners to have a comprehensive and up-to-date view of their clients’ financial situation.
- Financial analysis and forecasting: AI can use advanced techniques such as machine learning (ML), natural language processing (NLP), and computer vision (CV) to perform complex financial analysis and forecasting. For example, AI can use ML to identify patterns and trends in historical data, NLP to understand the sentiment and tone of news articles and social media posts, and CV to recognize images and charts. This can help financial planners to generate accurate and reliable financial projections and scenarios.
- Financial advice and reporting: RPA can automate the process of generating customised financial plans and reports for each client based on their preferences and needs. AI can then enhance the quality and relevance of the financial advice and reporting by using NLP to generate natural language summaries, explanations, recommendations, etc. This can help financial planners to communicate effectively with their clients and provide them with actionable insights.
These are just some of the ways in which combining RPA and AI can digitally transform a financial planning business. However, there are many more possibilities and benefits that these technologies can offer. By embracing RPA and AI, financial planners can not only automate their mundane tasks but also augment their capabilities and value proposition. This can help them to stay ahead of the competition and deliver better outcomes for their clients.