Are you ready for an AI integration in your bank? Top-10 questions for brainstorming in your company

How to make an AI transformation in your bank?

Steinbeis Consulting Center AI (STAI) provides AI software development and use state-of-the-art algorithms to give clients a competitive edge. Bringing our expertise in artificial intelligence, finances & banking, we have prepared a guideline how to organize a successful brainstorming for your strategy meeting.

Define your goals based on the value chain

Several trends in digital engagement have accelerated during the COVID-19 pandemic, and big-tech companies are looking to the digital transformation in their financial services. According to McKinsey & Company research the potential annual value of AI and analytics for global banking could reach as high as $1 trillion. Overall, AI creates value with across four value chains:

  1. Project – R&D project with the focus on real-time forecasting, deep-tech or independency as a new business unit.
  2. Produce – improvement of operations, lower cost, increment in efficiency
  3. Promote – marketing, pricing analysis, right message, and right targets
  4. Provide – enrich user experience with personalization

Segment your goals by sectors

In each value chain you may create a short list of sectors in your bank which requires priority. Artificial intelligence is applicable in customer service, front office, back office, SMEs solutions, infrastructure and some other topics. There is ideas shortlist:

Customer service

Analytics-backed personalized offers, personalized money-management solutions, savings and investment recommendations, conversational bots for basic servicing requests, users purchases segmentation

Front office

Micro-expression analysis with virtual loan officers, humanoid robots in branches to serve, up-sells recommendations

Back office

Biometrics (voice, video, print) to authenticate and authorise, Machine vision and natural language processing to scan and process documents, machine learning to detect fraud patterns, cybersecurity attacks, real-time transaction analysis for risk monitoring

SME solutions

Customised leading solutions, micro-expression analysis to review loan applications, seamless inventory and receivables management, SME platform to source suppliers and buyers, beyond-banking support services, AI-powered virtual adviser

Banking infrastructure

Data-lakes development, fraud detection, data management, intelligent infrastructure (AI operations, hybrid cloud setup, etc.), Modern API architecture

Match the business goals over a bank stream for value  creation.

To become AI-leaders, banks must invest in digital transformation across all layers of the integration capability. You must understand that AI-powered value is always supported by a new operating model, investments into infrastructure, core technology. In a digital transformation a bank usually restructure value creation stack. We give the check-list what could be discussed in your company as a first step.

A. Reimagined engagement

  1. Intelligent products, tools, experiences
  2. Within-bank channels and journeys (mobile banking, smart devices, IoT)
  3. Beyond-bank channels and journeys (ecosystem, partners, distributors)
  4. Smart device and operations

B. AI-powered decision making

  1. customer acquisition
  2. credit decision making
  3. monitoring and collections
  4. retention and cross-selling, up-selling
  5. servicing and management

C. AI capabilities

  1. Natural Language Processing (NLP)
  2. Voice-script analysis
  3. Virtual agents, bots
  4. Computer vision
  5. Facial recognition
  6. Blockchain
  7. Robotics
  8. Behavioural analytics

D. Core technology and data

  1. Tech-forward strategy
  2. Data management for AI world
  3. Modern API Architecture
  4. Intelligent infrastructure
  5. Hollowing the core
  6. Cyber-security and control tiers

Questions for brainstorming

  1. What value across the value chain is the most priorе to creating value with AI?
  2. What cases of digitalization have you successfully integrated into the company?
  3. What are your business goals for digitalization, AI integration? Define short-term, mid-term, long-term goals
  4. What are the priorities for the AI technologies in front office, back office?
  5. Which sectors of banking & finances are the most relevant for AI integration?
  6. Do you have the vision to become a digital ecosystem? If yes: which sectors are the most interesting for you to become in the digital ecosystem?
  7. Which of the following banking streamline is the most relevant for current goals?
  8. Which metrics, KPIs, business goals could be defined for each of your ideas?
  9. Which data & technology infrastructure challenges could be faced?
  10. Which operating model challenges could be faced?

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