Industry deep dive: Financial services
Data and AI
Data-driven insights and intelligence; AI-powered products and solutions
The power of data combined with the transformative potential of AI is reshaping the financial services industry.
From predicting market trends with precision to optimising risk management, data and AI can empower financial institutions to navigate complexity and lead with confidence.
The future of finance: Harnessing data and leveraging AI
There’s a major shift happening in financial services, due in large part to data and AI. Technology decision makers are moving away from managing infrastructure and architectures, as well as relying on systems powered by historical information.
They now have revolutionary tools at their disposal that will not only change the way in which financial institutions adapt and implement technology, but also influence strategic decisions and future growth.
The new normal in financial services is harnessing data and leveraging AI to:
- Increase customer personalisation – Thanks to personalised conversational interfaces and biometric profiles, financial institutions can provide customers with tailored products and offerings as well as things like payment schedules.
- Better decision making – By utilising predictive analytics and AI, financial institutions are better equipped to make appropriate, informed choices about risk and capital allocation in addition to underwriting, lending and investment decisions.
- Reduce and prevent fraud – AI can be used to monitor credit card and online transactions daily to detect changes in purchasing behaviour and provide a more streamlined process to deal with fraud.
- Keep pace with new industry players – FinTech and neo-banks aren’t necessarily doing anything new; they’re just increasing digital availability for existing services. Data and AI helps traditional institutions keep pace with their less established counterparts.
- Automate slow processes – Everyday services such as loan processing and customer onboarding can be brought up to speed with data and AI helping to augment and automate.
Data and AI at DiUS
While everyone is talking about GenerativeAI right now, our clients tell us one of their biggest challenges is actually data. Whether that’s because they are not storing it at all or they have too many platforms or systems or they are not collecting the right data to enable machine learning.
We’ve helped many companies build their data, analytics and AI/ML capabilities to unlock the value in their data, in many cases working on the foundational elements or processes needed to take their data game to the next level.
- Data architecture and strategy – Enable data connectivity and interoperability across different infrastructure components by breaking down data silos and providing trustworthiness, security and compliance.
- Data platform modernisation & management – Reshape current applications, or build brand new ones to automate data governance, reduce administrative complexity and get more value from your data.
- Data products – Put data into action by developing reusable datasets, data-as-code, analytics models or dashboard reports that support use cases across multiple functions or create new revenue streams.
- AI/ML and analytics – Use data analytics or the power of machine learning, predictive or generative, to automate routine work or drive decision making to deliver business efficiencies, improve customer experience or create new sources of revenue.
Our clients in financial services include:
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Gen AI - A Technical Deep Dive
Generative AI could add up to $4.4 trillion annually to the global economy*, and grow even further, with more models being trained and new solutions being announced; making the landscape even more complex to navigate.
Hear from Shahin Namin— Principal Machine Learning Specialist—and Marc Phoa—ML Practice Lead—as they break down generative AI and take you on a technical deep dive. They discuss the steps that go into building a generative AI solution, show examples, and highlight the things you’ll need to consider along the way.
You have the data, now what?
How can you do more with the data your organisation has and produces? What is data engineering and big data, and how can you enable data-driven decision-making within your organisation?
Hear from Nabi Rezvani—Lead Data Engineer—and Gaurav Thadani—Lead Software Engineer at DiUS on the latest trends, use cases and real-life examples of how our clients are using data and analytics to improve their decision making, customer experiences and business operations.
Data and AI insights
Progress your data and AI journey with DiUS
Let’s talk about how you can make the most of your data and stay one step ahead of the curve with AI.