8 Use Cases for AI in Fintech and Banking

AI in FintechThe Fintech and banking industry is in a constant state of innovation and one of the most important tech areas that will allow this to continue for years to come is Artificial Intelligence (AI). Finance professionals who are leading their organization’s AI efforts need to understand evolving customer expectations, evolving threat vectors, and internal capabilities such as culture, tech, and data infrastructure to pull off successful AI initiatives.


8 Uses of AI in Financial Services

Artificial Intelligence (AI) is the key to creating customer-centric experiences that satisfy customers’ wants and needs. The most successful companies will be those who utilize AI in a way that satisfies these 8 criteria:


1. Customer Engagement

Most consumers are already comfortable with voice-activated assistants like Amazon Alexa, Google Home, Samsung’s Bixby, Microsoft Cortana and Apple Siri for a variety of tasks including playing music, controlling home lighting systems, making restaurant reservations, checking the weather forecast or to get an Uber ride. If AI can help banks better understand relationships with their customers, AI can make it far easier for banks to deliver convenient banking experiences.


2. Personalized Customer Service

AI is already being used by some financial institutions to provide customer service by handling simple requests quickly and at scale.  A bot powered by Artificial Intelligence could be programmed to handle routine tasks such as password resets, delivery of monthly statements, and other time-consuming jobs.  In the future, intelligent bots powered by AI will be able to fully answer customer questions as well as anticipate their needs. Chatbots are already being used by some financial institutions but currently lack the capabilities or context necessary to provide a truly personalized experience.


3. Fraud Prevention and Security

AI in fintech can be used to identify and stop security threats, fraudulent activities or abnormal behavior in real-time.  In addition, sensitive data such as financial transactions can also be encrypted via AI algorithms to prevent hacking and minimize the risk of identity theft.  Sophisticated machine learning algorithms are being used to discover new fraud patterns that human investigators would likely miss.


4. Customer Segmentation and Microtargeting

AI can provide financial institutions with deeper insight into customer behavior, needs, preferences, and purchase intent to deliver more personalized experiences across all channels (digital/social/mobile).  Micro-segmentation based on aggregates of transaction history combined with social media profiles, web activity, and purchase history can allow banks to deliver more relevant messages and personalized offers.


5. In-App Chatbots

Banks are already using chatbots to automatically suggest financial products based on consumer preferences or transaction history.  In the future, chatbots will be able to have targeted conversations with consumers about their banking needs while providing personalized recommendations.


6. Chatbots for Financial Advisors

Chatbots can be used to provide basic advice on the more straightforward aspects of financial planning while freeing up financial advisors’ time so they can focus on being trusted counselors rather than transactional helpers.  A chatbot could also help guide consumers through the process of opening an account, learn about their financial goals, and present them with product recommendations.


7. Predictive Analytics for Wealth Management

AI can be used to improve the wealth management experience for both advisors and clients by looking across accounts held at different institutions to provide holistic analysis of client risk profile, net worth, family status, assets under management (AUM), etc.  AI algorithms can be used to detect when clients are likely to engage with their advisors for advice on selling or buying certain financial products.  AI can also help improve the accuracy of portfolio rebalancing by recognizing changes in market conditions and investment preferences


8. Loan Underwriting

The banking industry has already seen loan underwriting being partially automated by AI.  AI algorithms are being designed to look across multiple data points to build a complete picture of financial health, employment history, income potential and other metrics associated with the riskiness of an individual loan applicant.


Is AI Already Operating In These Industries?

AI-enabled chatbots and robo-advisors such as Kasisto, x.ai, and MoneyLion are already widely used by consumers for simple tasks such as keeping track of expenses.  Fintech startups such as Even and Acorns have raised significant amounts of funding to develop tools that help consumers save money and invest smarter.  AI algorithms are also being used to help banks and financial institutions make smarter decisions on everything from fraud prevention to loan underwriting.

Artificial intelligence is already permeating every aspect of the financial industry.  AI algorithms can be used to provide more personalized experiences for consumers, enhance security, improve fraud protection and reduce costs across all business lines.  Many fintech startups are utilizing AI-based tools to educate consumers on their financial options while saving money and investing smarter.  AI will continue to play a significant role in the financial industry, both by further empowering fintech startups and transforming traditional banks.

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