How data-centricity is the key to your AI plans
By InterSystems
Artificial intelligence (AI) makes your life easy, right? It helps you to reverse parallel park, reply to emails you’ve been avoiding for weeks, and recommend books you might like to read. It’s also reshaping the way the financial sector generates and uses data insights to understand customer behaviour and anticipate fraudulent transactions. In fact, the proliferation of banking and fintech apps attached to institutional platforms has AI to thank. It is a critical part of the banking and fintech space in terms of improving the customer experience, streamlining processes, collecting data, analysing information, and safeguarding and facilitating transactions.
However, to maximise its benefits, AI needs to be less focused on building models and more focused on the data it captures. The good news is data-centric AI is becoming the next big thing in data science and machine learning circles. It focuses primarily on providing quality data and leveraging that information to develop solutions that improve business outcomes. It also offers precise accuracy, personalisation, and lower operational costs. When it comes to staying relevant and providing the best customer experience, it’s important to understand how your financial business can leverage this new technology.
There are three ways data-centric AI technology can add value to your organisation.
- Service personalisation
In today’s digital world, it’s no surprise to find that customers are shifting towards online banking. In fact, you’d be hard pressed to find a bank that is yet to launch an app for its customers via the engagement of fintech companies or through fintech initiatives of their own. But customers want more than just an app; they’re after a more personal touch, and that’s where data-driven AI comes in. Banks and fintechs are harnessing the power of AI to leverage data and predictive analytics to develop customer-centric banking products and enhance the customer experience. Hyper-personalised experiences are what customers are coming to expect and, with greater visibility into the customer, banks and fintechs can better anticipate needs, and deliver timely and relevant products and services.
- Data-driven decision-making
AI data-driven forecasting can help banks and fintechs make more informed decisions. By collecting and optimising customer data, AI can determine who to lend to (and where to set lending limits), identify potential fraud, and distinguish risky customers. Forecasting future outcomes lets banks and fintechs control financial risks and gain invaluable insight into spending habits, social-demographic trends, and other factors that help personalise services and create better customer experiences. Furthermore, AI-driven forecasting in the fintech space lets customers trade stocks and shares via mobile apps with reduced trading risk.
- Fraud detection and prevention
From credit card and loan application schemes to identity theft and social scams, fraudulent activity has skyrocketed in the past few years and is only going to increase as technology continues to advance. To combat this, financial services organisations are increasingly using data-driven AI to analyse data and monitor user behaviour patterns to spot any unusual incidents. When this technology detects suspicious activity, it automatically flags it for further investigation or rejects the transaction completely. It can also determine the likelihood of fraud occurring and, in some cases, prevent it before it even happens.
There’s no doubt that the COVID-19 pandemic was behind the inevitable surge in the use of digital technologies across the board, which included the finance sector. This has created the perfect opportunity for organisations with large data sets such as banks and fintechs to get significant insights into customers and their user experiences. With the shift from model-centric to data-centric AI, now is the time for you to invest and accelerate the application of new technology to meet the requirements of your business. When harnessed effectively, data-centric AI can lead to faster development, increased accuracy, and a higher return on investment, all while providing a superlative customer experience.
