Insurance and Banking Analytics

Create innovative solutions for customers using advanced data analytics and new technology

image
Digital Transformation is changing Insurance and Banking

Digital Transformation is changing Insurance and Banking

Like all progressive industries, insurance and banking organisations want to increase the competitive advantage by gaining key insight across their operations. As the world becomes more volatile, uncertain and complex, insurance and banking organisations are forced to rethink their digital transformation strategy.

Increasing demands from clients, among other things, are further compounding challenges and forcing the adoption of new technologies. What’s more, regulatory compliance and clients’ expectations of consumer-grade experience within applications, such as self-service analytics, are forcing the industry to innovate further.

Challenges in the Insurance and Banking Industry

Legacy infrastructure and disconnected data hinders innovation

Legacy infrastructure, disconnected data silos and a lack of knowledge of the value of analytics are the primary obstacles to innovation and progress for the insurance and banking sector. The new International Financial Reporting Standard (IFRS) is also changing the way insurers’ and banks’ financials are measured and reported on.

To achieve compliance, insurers and banks need to update their systems, adopt new processes and improve integration between departments. Accounting processes need to be more transparent.

New technology is the way to compliant, customer-centric solutions

AI, analytics and digital transformation allow insurance and banking businesses to simplify and automate the process of consolidating data from disparate systems, allowing you to make more effective and impactful decisions.

More advanced uses of AI and machine learning give you the power to improve security and compliance around anti-money laundering and risk management. They also enable you to offer a more proactive, personal customer experience and streamlined back-end business process management. Customer service can also be improved through the adoption of chatbots and RPA applications.

The Opportunities Presented by Insurance and Banking Analytics

The Opportunities Presented by Insurance and Banking Analytics

Technology is advancing the use of analytics in insurance and banking. It presents a real opportunity for insurers and banks  to change the approaches by which they use data and deliver analytical insight to the business, whilst at the same time minimising disruption.

Insurers and banks need to take action on key insights provided by IoT applications and related services. They must simplify the process of collecting customer data from disparate sources to make more effective decisions and realise the full value of data with insurance and banking analytics. Gaining insight across operations with multiple brands or syndicates is highly challenging if you have legacy data warehouses, outdated systems and processes. This makes it near impossible for insurers and banks to get full end-to-end insight into customers’ activities and business operations.

How does NTT DATA support the insurance and banking sector?

At NTT DATA, we employ some of the world’s leading experts in the field for AI, big data analytics and digital transformation.

We have adopted a new approach to data that drives operational excellence and customer-intimacy by combining the modern data platform and advanced insurance and banking analytics. This allows us to help our customers integrate data across complex landscapes, access new types of data and share insight across the organisation.

Data and Analytics Services at NTT DATA

Big Data

Big Data

Leverage big data analytics to store and manage the volumes and variety of data, including unstructured data, alongside structured data records.

Advanced Analytics

Advanced Analytics

Rapidly blend data with advanced analytics to improve the detection of links and patterns associated with fraud.

Actionable Insights

Actionable Insights

Better identify and understand customer profiles, needs and behaviours to improve customer penetration, profitability, higher persistency and propensity for new spend.

Consolidated Data

Consolidated Data

Introduce a consolidated and consistent view of your customer profile and relationships across businesses while dealing with fragmented underlying technology and data.

Machine Learning and AI

Machine Learning and AI

Benefit from machine learning and AI to provide automation and intelligence.

Speak to Us Today

Are you searching for answers or would like to receive more information on Insurance and Banking? Would you like more detailed advice from our experts?

Just contact us – we will be glad to help you.

Contact Us
Contact Us

Have questions? Please contact us.