This column is by Big Data Strategis Arav Narasimhamurthy.
Godfather of Artificial Intelligence (AI), Alan Turing defined it’s concept in 1950’s and it has existed as a defined concept since its inception for what determined a machine to be “intelligent. Turning starts with ‘Can Machines think?’ since the words ‘think’ and ‘machine’ cannot be defined in a clear way that satisfied everyone. AI has evolved over last few decades overcoming long winters of disillusionment and now being integrated with other disruptive technologies for new age storytelling attracting millennials.
Why AI will work this time?
Financial services is been revolutionized by disruptive technologies and fintechs upending workflow and processes. Days are gone where banks were operated with paper money, bulky computers and human interaction, organizations are moving entirely towards digital interfaces.
Fintechs have developed algorithm based products and solutions to track customer’s online pattern and create personalized experiences. The idea of augmenting human interactions and intelligence with AI doesn’t end with consumer-facing products.
AI could power technologies that overlay humans to provide an oversight and tracking mechanism to employee actions, helping with compliance, security, and the monitoring of actions.
The implications for the financial sector is that by tracking customers habits, activities, interactions, events and behavioral characteristics, products and data can be personalized to meet each and every customer needs, identify frauds and recommend financial investments .
Below are few examples of how financial organizations are deploying AI to address customer needs
- Customer service delivered by AI Digital Assistants
- Financial Advisors through combining multiple data points and provide visual insights
- Digital assistants in channels like ATM, Mobile..etc
- Delivering better and personalized customer experiences
- Customer acquisition through Digital channels
- Creating personalized customer profiles
- New connected products
- Fight fraud with Artificial Intelligence
- Enhanced fraud and authentication
- Device identification, behavior analysis, anomaly detection
- Credit Scoring
- Gather customer data from non traditional sources
- Quantify qualitative aspects
- Customize scoring models
While the benefits of AI are increasing enormously the challenges faced by adopting it is also growing as days goes by:
- Governance – The growing regulatory and compliance requirements are making effective data governance a must have for industries like financial services and healthcare. The demanding around data privacy, personal information protection, data security, data lineage, and historical data regulatory requirements are now more
- What has been done to address the challenges resulting from the requirement to use more granular data?
- Are there appropriate governance procedures around data integrity and model validation?
- Security and Privacy concern – Privacy could become an even bigger deal in the future. The data used to make advice and recommendations more relevant can also be used for purposes that could be considered an invasion of a person’s privacy
- When things fail and access is denied, or resulting recommendations tampered with, the consequences could be shattering.
- Similarly, if the applications can’t identify their users accurately, hackers could successfully impersonate the real user and convince the program to turn over sensitive data, or to take instructions from the wrong person.
- Federal Regulations – Fed is yet to approve pre-defined set of machine learning algorithms to be used for deriving Insights and respond to customer needs and leverage the information/insight for regulatory reporting hence it is challenge for the organization to meet both customer needs and align to regulations.
Because of the significant positive benefits AI provides there is probably no turning back, financial services will see increase in adoption of automation often employing AI technology. Organizations have to find a way to address security, privacy concerns and build trust so that user can believe the advice and services provided. It is very important you find a way to detect malicious AI programs and isolate them from production. Deploying stringent governance policies and monitoring the development and use is very critical to success of AI usage in the organization.
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Image Credit – WNS