How Combining RPA and AI Can Digitally Transform a Financial Planning Business

Published on 2nd November, 2023

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.

Challenges in Financial Planning

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.

The Role of RPA and AI

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.

Difference Between RPA and AI in Finance

While RPA and AI are both transformative technologies in finance, they serve different purposes and operate in distinct ways:

RPA (Robotic Process Automation)

Function: RPA automates repetitive, rule-based tasks. It is designed to handle structured data and execute predefined processes.
Use Cases: Data entry, transaction validation, report generation, record updates, email automation, and appointment scheduling.
Strengths: Increases efficiency and reduces errors in mundane tasks, freeing up human workers for more strategic activities.

AI (Artificial Intelligence)

Function: AI performs tasks that require human-like intelligence, such as learning, reasoning, and decision-making. It handles unstructured data and can adapt to new situations.
Use Cases: Financial analysis, forecasting, sentiment analysis, image and chart recognition, and generating natural language summaries.
Strengths: Provides deeper insights, enhances decision-making, and can learn from data to improve over time.

Benefits of Combining RPA and AI

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.

With VBP, we can help you navigate this transformation and achieve hyper-automation in your financial planning business.

About the Author

David Carney

VBP

DC lives in Queensland and visits our Cebu site every quarter. DC brings 21 years of experience working in the financial services industry. He is a Certified Financial Planner and was the Managing Director of Aspect Partners – a financial planning firm he previously owned and successfully sold in 2008. He is a Gazelles Certified business coach and has worked with several planning firms to help them with strategic thinking and execution planning.

Subscribe to the VBP newsletter

Stay tuned to our latest stories through your email.

A Platform for adviser firms to scale and leverage

Improve back-office operation, reduce cost and improve task turnaround time.

Discover VBP’s Evolving Approach to Boost Your Business Growth

Your Financial Data Is at Risk: 4 Steps to Protect It Now!

As data breaches surge, the financial industry faces increasing cyber threats. In this article, Neriza, VBP Deputy Manager, outlines four essential steps to protect your information. Learn how strong passwords, multifactor authentication, phishing awareness, and regular updates can safeguard your digital environment and keep your data secure.

9 minutes

Solving Recruitment Challenges in Australian Accounting with Offshoring and AI

Australia's accounting firms are grappling with a severe skills shortage, impacting client deadlines and growth. Daniel Harrison explores key challenges—including lack of interest in public practice and shortfalls in skilled migration—and provides strategic solutions like offshoring and AI integration to help firms overcome these issues and thrive in an increasingly competitive market.

7 minutes

All topics