
A Definitive Guide To Composite AI in Banking
The global artificial intelligence (AI) in Banking is expected to reach
USD 130 Billion by 2027, and register a CAGR of 42.9% during the
forecast period, according to the latest analysis by Emergen
Research.
Early adopters of Artificial Intelligence in Banking have realized that
Isolated AI use cases do not create sustainable value for business and
they need a comprehensive AI approach to leverage Composite AI embedded
with Domain knowledge.
What is Composite AI?
Composite AI is a breakthrough approach combining multiple AI realms to more deeply interpret data and efficiently solve a wider range of business problems. The techniques applied include- knowledge graphs, natural language processing, contextual analysis, machine learning, deep learning, Computer vision, Recommendation systems, and other methods.
Why Composite AI for Banking?
Banking system deployments have created silos of data which ultimately
lead to broken customer journeys and poor data quality for machine
learning and analysis.
Composite AI with a common knowledge graph ontology of customer
attributes, product attributes, and AI models can help overcome the
silos with comprehensive intelligence across customer journeys. Read more
A good example is Contextual banking with Machine Reasoning whereby Big
Data, recommendation systems, computer vision, and Natural Language
processing are used to hyper-personalize customer journeys for existing
customers.
Benefits of Composite AI
A. Intelligent interactions
Composite AI enables intelligent customer interactions with proactive
service, contextual cross-sell and upsell, and persona-based offers and
recommendations.
B. Frictionless customer journey
Composite AI can enhance digital customer journeys across channels e.g.
Higher conversion in Digital sales for new to bank prospects by
streaming live product recommendations based on dynamic persona driven
by location, device, context understanding from clickstream/NLP chat
conversations, machine reasoning based dynamic pricing & instant
personalized offers, followed by eKYC/onboarding in the channel with
face verification & liveness detection for a frictionless journey.
C. Lightning-fast time to market
Composite AI with prebuilt customer journeys brings built-in best
practices, workflows, security, governance, and backend adapters for
quick launch.
D. Seamless expandability
A single Data and AI layer with a development toolkit and SDK enable the
bank to build new use cases easily from scratch or by reusing the
pre-built models e.g. extend the propensity model to churn prevention by
leveraging the same data and customer attributes.
Read more about Composite AI https://www.bankbuddy.ai//cognitive-banking-architecture