Artificial intelligence (AI) is profoundly impacting the banking industry today. AI is assisting financial institutions and banks to become more efficient, much like a digital genius. Banking and finance stand to gain a lot from AI when used strategically.
The key is its ability to handle vast volumes of data, identify hidden patterns, and make deft decisions, revolutionising the sector. Beyond the technical terms and buzzwords, AI indicates a change in the forces of the market, the possibility of monetary gain, and a way to increase customer loyalty. Read on to learn more about the risks to be aware of and how AI tools have customised financial services.
Major AI Technologies for Finance
Forecasts indicate that the worldwide market adopting generative AI in finance and banking will increase from an estimated $712.4 million in 2022 to $12,337.87 million in 2032, a CAGR of 33%. Here are some useful examples of AI technologies used in the financial sector.
Natural Language Processing: It allows machines to comprehend and react to human language. Almost all high-quality voice assistants and chatbots today use some form of natural language processing. Utilising natural language processing, chatbots like Erica, developed by Bank of America, can comprehend and instantly react to client inquiries.
Robotic process automation: Programmable bots automate mundane but necessary operations, improving efficiency and precision. Robotic process automation (RPA) bots can automate repetitive data entry operations, which allows for faster account setup and less room for human mistakes.
Predictive analytics: It determines potential outcomes by analysing current and past data. It aids in making educated decisions, which benefits service providers and users alike. Banks can provide customers with tailored financial advice and product suggestions by examining their spending habits.
Biometrics and Voice Recognition: These automated systems recognize people by their distinctive characteristics, whether fingerprints or vocal patterns. Some financial applications now let you log in with your voice or fingerprint for an extra layer of protection.
Blockchain and DLT: It is an encrypted, distributed method of keeping track of financial dealings. It functions similarly to a trustworthy shared digital ledger. Beyond cryptocurrencies, banks need to use blockchain, as demonstrated by initiatives like J.P. Morgan’s Quorum, to improve transaction security and transparency.
Examples of AI’s Tailored Financial Services
For a holistic understanding of AI in financial services, aligning adoption with specific products is essential.
KYC: AI streamlines Know Your Customer processes include, automating document verification, behavioural analysis, facial recognition, and continuous data updates for swift, compliant customer onboarding.
Checking and Savings: Transforming traditional banking products, AI offers personal financial management, anomaly detection, and future spending predictions, providing users with insightful budgeting tools and proactive spending oversight.
Loans and Mortgages: In lending, AI in financial services ensures fair play, quick approvals, advanced issue spotting, and a comprehensive credit scoring approach, enhancing the borrowing experience for customers while safeguarding institutions.
Investment Services: AI-driven robo-advisors, market pulse with sentiment analysis, and automated portfolio management cater to novice and experienced investors, offering personalised advice, market insights, and efficient portfolio adjustments.
Digital Wallets and Payments: AI in financial services predicts user payments, optimises transaction routes, and facilitates smart promotions, ensuring swift, secure, and personalised financial transactions.
Trade Finance: AI expedites trade operations through automated document verification, provides trade risk forecasts for better risk management, and optimizes currency conversions, ensuring efficient and reliable trade finance services.
Asset Management: In asset management, AI brings algorithmic valuation, market movement forecasting, automated asset allocation, and streamlining processes for accurate valuations and informed investment decisions.
Parting Thoughts
Using artificial intelligence in banking and finance is not just a passing trend but marks a substantial shift towards increased productivity, customer focus, and innovation. With the right knowledge of AI tools, knowing where to put your efforts, and taking advantage of contracting app development to a reliable partner, banks can meet regulatory requirements and quickly capture value.
