Navigating the Financial Revolution: How AI is Shaping Tomorrow’s Finance Today

In the ever-evolving landscape of the financial services sector, innovation, especially the meteoric rise of Artificial Intelligence, has become the driving force behind adaptability. For decades, the global financial industry languished in old-school ways, leaving inefficiency in its wake. But the dawn of computing and AI in the early 80s triggered a seismic shift that continues to reverberate from integrating Microsoft Excel in finance and accounting in the 1980s to robo-advisors and the incorporation of machine learning in personal finance today.

With vast datasets and intricate global markets, the financial services industry is the perfect canvas for innovation, with AI as its brush. Consumer demand for improved experiences, transparency, and efficiency has pushed emerging technology to the forefront.

In the realm of business, the keys to success are efficiency and precision, and AI is no longer a distant vision but a present-day reality. In this blog, we seek to interrogate the integration of AI into the various areas of finance, such as:

  • Investment Research,
  • Accounting,
  • Personal finance management and
  • Financial planning & analysis.

1. Elevating Insights with AI in Investment Research
AI has revolutionized investment research. Picture AI-driven Natural Language Processing (NLP) seamlessly applied to investment research and analysis. The outcome? AI swiftly distils critical insights, crafts concise summaries, and charts actionable pathways from data – a treasure trove for asset managers. With the relatively recent availability of mountains of data, AI has been applied to gather alternative data sets to help find alpha (the performance of a holding in relation to the market) to achieve higher returns, as Rick Roche, managing director of Little Harbour Advisors, notes. AI leverages machine-learning algorithms to navigate vast datasets, offering in-depth analysis and predictive capabilities.

2. Transforming Personal Finance with AI
AI is at the forefront of a financial evolution, fundamentally altering the manner in which individuals oversee their finances. It doesn’t stop at automation; it offers custom-tailored insights, refining financial decisions. The rise of AI-powered products and platforms has ushered in a new era of personal finance, touching every aspect from budgeting and expenditure tracking to investment management and even fraud detection. It’s like carrying a personal financial advisor and assistant in your pocket who can:

  • Streamline the Mundane: AI takes the reins in automating the drudgery of personal finance.
  • Proactively Monitor: Keeping a vigilant eye on financial matters.
  • Enhance Outcomes: Elevating results to unprecedented levels.
  • Predict Analytics: Leveraging data-driven foresight for superior financial management.
  • The Fraud Sentinel: Unraveling the intricacies of fraud detection with AI-powered precision.

3. The Future of Accounting: Embracing AI
AI is revolutionizing the accounting sector, promising increased efficiency and improved client services. Recent surveys and studies show that the accounting profession recognises AI’s potential in improving efficiency and client services. According to Quantum Finance and Business Intelligence, 24 per cent of top-performing CAS practices are actively harnessing AI, as revealed in the and AICPA PCPS CAS Benchmark Survey. Additionally, the “2022 VSCPA Future of Work Survey” identified AI as one of the top five technologies respondents plan to incorporate in 2023. AI streamlines repetitive tasks like data entry and data categorization, reducing errors and freeing up accountants for more strategic work. It also enhances data analysis, offering insights that human accountants might miss. Furthermore, AI provides real-time insights to clients, facilitates long-term financial planning, and enables efficient scalability, making it a transformative force in the accounting profession.

4. Real-World AI in Finance
AI has significantly impacted the financial sector, with robo-advisors leading the charge. These AI-driven platforms offer efficient, cost-effective portfolio management and expanded services like tax strategies and access to human advisors. While A.T. Kearney’s prediction of robo-advisors managing $2.2 trillion in investments by 2020 didn’t materialize, they’ve made a substantial impact. In 2022, robo-advisors managed $1,164 billion in the US, a figure expected to nearly double by 2027, reaching $2,193 billion. Globally, robo-advisors already oversaw over a trillion dollars in assets by 2020, highlighting their profound influence on finance. Additionally, we have witnessed the emergence of some well-funded AI startups, each contributing to the expanding landscape of AI’s influence in finance:

  • Signifyd streamlines e-commerce checkout approvals, enhances compliance, and reduces fraud by leveraging AI-driven customer risk profiles. They collaborate with major companies like and have raised $206 million, serving e-commerce platforms like Shopify, Magento, Big Commerce, and Salesforce Commerce Cloud.
  • DataVisor, founded in 2013, uses AI and unsupervised machine learning to predict and prevent fraud and financial crimes for banks and financial institutions. They’ve raised $54 million in funding from investors like Sequoia Capital and Genesis Capital.
  • Wealthfront is an AI-driven robo-advisor providing software-based financial planning, investment management, and banking services, with a mission to democratize investing. They have $12 billion in assets under management and $204 million in funding.

These examples collectively showcase AI’s diverse and influential role in revolutionizing the financial landscape, from robo-advisors changing how we manage investments to the significant investments pouring into AI startups shaping the industry’s future.

AI in Finance: Opportunities and Challenges
AI offers opportunities in:

  • Fraud Detection and Prevention: AI systems can analyze vast amounts of data in real time to swiftly detect suspicious patterns and potential fraud cases, enhancing security in digital transactions.
  • Credit Risk Assessment: Machine learning algorithms can provide more accurate and predictive credit risk assessments, allowing financial institutions to make informed lending decisions and reduce loan defaults.
  • Customer Experience Enhancement: AI-powered chatbots and virtual assistants offer personalized recommendations and assist customers with various financial tasks, from account management to investment advice.
  • Trading and Investment Management: Algorithmic trading systems can analyze data and make real-time trading decisions, while AI-driven investment management systems identify and analyze market trends, aiding investors in decision-making.

However, challenges like:

  • Bias and Discrimination: AI systems can perpetuate existing biases and discrimination in financial decision-making, which is a significant ethical concern.
  • Lack of Transparency: The lack of transparency in AI systems makes it difficult to understand how algorithms make decisions, potentially eroding trust in these systems.
  • Overreliance on Data: AI systems may make decisions solely based on statistical data, potentially ignoring social and ethical considerations.

In conclusion, the future of finance is undoubtedly intertwined with AI. As we’ve explored the various ways AI is transforming personal finance, investment research, accounting, and the broader financial landscape, it’s clear that AI is shaping tomorrow’s finance today. This technology can potentially create a more efficient, accessible, and inclusive financial system, enhancing decision-making, reducing costs, and improving the overall customer experience.

Felix Hoddinott, Chief Analytics Officer at Quantexa, aptly points out that regulators recognise the impactful improvements achievable through AI, especially in risk assessment and monitoring. Regulators are expected to issue guidance to accelerate AI adoption in the financial sector. While challenges like bias and transparency need addressing, responsible AI implementation is critical to a thriving financial industry.

With these considerations in mind, the financial industry is poised for a future where AI-driven innovation continues to offer better services and experiences to its clients. The marriage of AI’s transformative capabilities and regulatory guidance is laying the foundation for a financial landscape where efficiency, accessibility, and ethical practices coexist.

By Kelvin Kipkoriri, Analyst InVhestia Africa

Startup Growth: Go Big, Go Slow, or Find Balance?

In recent years, several startups ditched the disciplined approach to growth and went for the growth-at-all-costs model. Examples such as Sendy and Twiga, among others, are a testament to this.

With this “Go Big or Go Home” approach, characterized by Reid Hoffman’s book “Blitz Scaling,” those who have not yet achieved sustainability now have to make significant changes to their business models, with some even shutting down.

This strategy involves raising significant capital, scaling rapidly to achieve market dominance, and then optimizing the business model. Uber is a prime example of this approach. However, this method requires ample capital and investor patience, as it can take time to optimize the business model.

On the other hand, the “Slow and Steady Wins the Race” approach entails growing a company gradually without taking substantial risks. This conservative method focuses on sustainability through internally generated funds. While this approach looks like it may prove successful in the long run, it does not always work in a competitive global market where international companies are constantly expanding into new territories.

The way forward lies in striking a balance between these two approaches: “Go Big, but Be Ready to Shift When the Tune Changes.” This middle ground involves considering unit economics from the outset and building towards a sustainable business while focusing on growth and scaling. Founders should always have a Plan B if funding slows down or market conditions change.

For those founders who were all in the Go Big or Go Home way of doing business, the time has come to swallow the bitter medicine. This is necessary for plain survival to see another day. The founders and their advisors have to take action as fast as possible without perfect information. In the current scenario, it is better to cut too close to the bone and correct course later rather than wait for perfect information, run out of cash and go out of business altogether.
In conclusion, adopting a balanced approach between aggressive growth and steady progress can help startups navigate the challenges of today’s competitive business landscape. Remember to “Go Big but Be Ready to Shift When the Tune Changes” to maximize your chances of success.


By Stephen Gugu- Principal InVhestia Africa and Co-Founder Viktoria Ventures