Top 5 Artificial Intelligence Trends in Finance for 2021
AI is one of the fastest growing tools adopted by financial firms today. Here are the top five AI trends.
Despite economic turmoil experienced by most businesses due to the pandemic, the AI market experienced a massive growth with software accounting for more than 80% of revenue shares. As these companies paved the way for AI and automation at the foundational level in managing customer relationships, businesses became familiar with the benefits of applying AI and automation into their daily workflows, paving the way for broader adoption of AI.
Despite an unprecedented year across most industries, the demand for AI grew, especially within financial services. In 2021 and beyond, artificial intelligence will lead the stage in innovation for financial firms as more companies will realize that artificial intelligence tools and machine learning tools will be necessary to remain competitive. Here are the top five trends of artificial intelligence to look out for within the financial sphere in 2021.
1. The migration to Software as a Service (SaaS) platforms
As one of the most heavily regulated industries, the financial services industry has been wary about adopting the public cloud into their workflows due to concerns for privacy and data security. It's not that financial companies are slow or uneducated about new technologies (they did introduce ATMs, online banking, and mobile transfers), but the heavy regulations, compliance laws, and lack of infrastructure have made it difficult for financial firms to completely disregard old ways, migrate workflows to a public cloud system, and trust that it'll work.
However, technological advancements have proven the ability to use multi-cloud platforms that are completely secure. According to a Gartner survey, almost 40 percent of enterprises planned to migrate to cloud solutions for core financial applications and transactional records. In 2021, 32% of IT budgets will be dedicated to the cloud, as cloud technologies like Cisco, IBM Cloud, and Oracle, to name a few are increasingly embedded into enterprises' business strategies. Emerging cloud platforms in 2021 include:
- Artificial intelligence services: Financial firms will use artificial intelligence cloud services to integrate AI into their workflows through simple API calls. Platforms like Microsoft Azure, AWS (Amazon Web Services), Google Cloud are a few of the top platforms that bring AI and cloud infrastructure together to deliver smart insights.
- Machine learning on a cloud platform: Financial firms will be able to create, deploy, and manage machine learning models through a single platform. FinTech firms like Accern, Allegro, and Vidora will strengthen their value proposition for financial services and more FinTech startups will begin to emerge offering machine learning and automation on Cloud platforms.
2. The adoption of no-code artificial intelligence
As more financial enterprises adopt AI technologies to make their business operations more efficient and to gain a competitive advantage, the no-code movement will bring a wider adoption of AI to firms. Innovations in technology have trained organizations to look for quick, easy, and cost-efficient solutions to spearhead business challenges. No-code offers a pre-developed backend and customizable front-end user interface for financial teams to build and deploy artificial intelligence models without having to code or pass through IT.
No-code AI provides financial services teams with more efficient, smart solutions to the time-consuming, manual processes of data research, extraction, and analysis. No-code artificial intelligence will empower financial firms to become nimbler, make faster and better decisions and save time and money while implementing AI solutions that match their business needs. With that being said, this will open opportunities for existing FinTech firms to innovate and implement no-code into existing workflows and for new FinTech firms to emerge within the no-code AI field.
From 2019 to 2020 financial firms already began implementing no-code AI tools like H2O.ai, RavenPack, and Accern, realizing the value of building and deploying AI models with simple point-and-click commands. Take Next Alpha, for example, who took the plunge with no-code AI to validate its models. The results were impressive returns of 40% during a period which the S&P 500 lost 4.9%. In 2021, we will see both smaller and larger financial firms explore more possibilities of no-code AI within their financial firms. The finance industry will increasingly see the value of investing in no-code AI platforms to generate quick and large returns through validating models, building and deploying custom NLP (natural language processing) models, using off-the-shelf AI models, and more to gain smart insights.
3. Data management with AI
Nearly 90 percent of data today is unstructured and is growing at a compound annual growth rate of 55-65% each year. With data changing by the second, financial firms must continuously monitor these changes, which can amount to monitoring thousands of transactions per day. As business analysts spend hours manually researching, extracting, and analyzing data, and then monitoring data for any changes, the room for human error is broad.
Artificial intelligence enables financial teams to automate the manual data research, extraction, and monitoring processes by streamlining the way data is ingested, extracted, analyzed, and managed. Financial teams can then stay up-to-date on data, offer more accurate insights to clients, manage risk, and focus on improving other business functions.
4. Integrating AI and SaaS platforms
With the migration towards the public cloud, financial firms are realizing that integrating artificial intelligence and machine learning into SaaS platforms adds more value to their business functions. Simultaneously, SaaS providers like Amazon AWS, Microsoft Azure, and Google Cloud Platform are integrating AI into their software for more functionality and to add value for end-users.
As the widespread use of technology for end-users is providing comfort, speed, and personalization, clients are now demanding more from financial firms. In order to meet the rising demands of customers, financial institutions will need to approach clients with more personalized services and results. For example, wealth management firms must find ways to deliver personalized financial advice to clients based on their portfolio preferences and goals or risk client attrition. One way that AI and SaaS integrations help are by allowing wealth advisors to use smart search capabilities and intelligent tagging on client meeting notes within their CRM (customer relationship management) system.
5. Using AI to ensure compliance and manage risk
AI is opening the door to greater possibilities within a shorter time frame. As financial firms are identifying the use cases, they have found artificial intelligence in compliance and risk management to create value. Traditionally, business analysts would manually research, extract, and evaluate data around corporations to ensure that actions matched with their words, and bankers and insurers would need to go through piles of documents to ensure that data are in line together.
As ESG (environmental, social, governance) investments have been a hot topic within the financial sphere, exacerbated in 2020 with the impact of COVID-19, financial firms identified that AI can ensure that corporations' ESG statements are in line with their actions. Artificial intelligence algorithms can be used to gather data on companies from structured and unstructured data sets and monitor companies' actions to ensure daily ESG compliance. Additionally artificial intelligence predictions can help financial firms identify a corporation's ESG initiatives and its future financial performance.
Large financial firms like Deloitte, Bridgewater Associates, and BlackRock to name a few are maximizing the use of AI in their workflows for these purposes. In 2021 we will see an increase in AI adoption from smaller to medium-sized financial firms. As AI becomes widely accessible, more financial firms will inevitably need to adopt these new technologies to remain competitive.
About Accern:
Accern is a no-code AI platform that provides an end-to-end data science process that enables data scientists at financial organizations to easily build models that uncover actionable findings from structured and unstructured data. With Accern, you can automate processes, find additional value in your data, and inform better business decisions- faster and more accurately than before. For more information on how we can accelerate artificial intelligence adoption for your organization, visit accern.com