Cognitive Computing in Banking and Financial Markets
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The presentation discusses how cognitive computing can help transform the banking industry by (1) providing more personalized customer engagement and insights, (2) improving decision making through analysis of complex structured and unstructured data, and (3) enabling new operational efficiencies through automation and augmentation of human expertise. A number of use cases are described across functions like wealth management, risk management, fraud detection, and debt collection. Critical success factors for banks adopting cognitive computing include defining clear value propositions, investing in data and talent, and change management.
![©2015 IBM Corporation4
Cognitive computing is a new generation of computing
Cognitive: of, relating to, or
involving conscious mental
activities (such as thinking,
understanding, learning, and
remembering)1
Learns and builds knowledge from various structured and unstructured sources of information
Understands natural language and interacts more naturally with humans
Captures the expertise of top performers and accelerates the development of expertise in others
Enhances the cognitive process of professionals to help improve decision making
Elevates the quality and consistency of decision making across an organization
Cognitive computing…
Sources: [1] Merriam-Webster Dictionary. [Online]. Available at: http://www.merriam-webster.com/dictionary/cognitive](https://image.slidesharecdn.com/cognitivecomputingbfmsummary20160524-181030204118/85/Cognitive-Computing-in-Banking-and-Financial-Markets-4-320.jpg)
Cognitive Computing in Banking and Financial Markets
- 1. ©2015 IBM Corporation1 Redefining customer engagement and operational management Cognitive Computing in Banking and Financial Markets Gianpaolo Zampol | Business Development Executive, Financial Services Sector São Paulo | May 24th, 2016
- 2. ©2015 IBM Corporation2 The age of new customers Digital natives The age of new channels Omni channels Smart wearable The age of new product mix Banking and non banking products Growth of non-interest income The age of new insight Data mining Risk management The age of new value propositions Life stage and life style driven Instant offers and gratification Financial institutions Theageofnewcompetition Theageofnewregulations The global banking industry has been experiencing a process of radical transformation Cognitive computing provides a means through which external pressures can be harnessed and transformation managed
- 3. ©2015 IBM Corporation3 Cognitive computing Digital network Enabling infrastructure Business ecosystems The cognitive bank Mobile and social Omni-channel Analytics Digital operations Customer value chains Customer economic choices Integration Big data IT infrastructure Security Resilience Natural language processing Machine learning algorithms Ecosystem services and partners Cognitive analytics Within this transformation, a new type of bank is beginning to emerge – the cognitive bank Combined with other transformation engines, cognitive helps banks orchestrate metadata to produce massively expanded business value
- 4. ©2015 IBM Corporation4 Cognitive computing is a new generation of computing Cognitive: of, relating to, or involving conscious mental activities (such as thinking, understanding, learning, and remembering)1 Learns and builds knowledge from various structured and unstructured sources of information Understands natural language and interacts more naturally with humans Captures the expertise of top performers and accelerates the development of expertise in others Enhances the cognitive process of professionals to help improve decision making Elevates the quality and consistency of decision making across an organization Cognitive computing… Sources: [1] Merriam-Webster Dictionary. [Online]. Available at: http://www.merriam-webster.com/dictionary/cognitive
- 5. ©2015 IBM Corporation5 Cognitive analytics Cognitive engagement Customers, bank staff and ecosystem partners Cognitive operations Data Structured Unstructured Better decisions New areas of productivity Harness information from various sources with different forma for decision making ▪ Better customer insights ▪ Better risk/pricing decisions ▪ Better compliance decisions Alleviate the cognitive burden with answers and insights ▪ Context based workflow ▪ Next best actions ▪ Automation and Straight-through processing (STP) Cognitive unleashes new realms of engagement, discovery and decision making… Personalized responses ▪ Context based engagement ▪ Next best offers ▪ Increased integration Improved customer engagement Engage DecideDiscover
- 6. ©2015 IBM Corporation6 And cognitive computing enables and supports a new, deeper type of business decision making Analytics Cognitive computing ▪ Addresses predefined problems ▪ Addresses ambiguous problems ▪ Provides accurate and definitive answers ▪ Provides answers with a margin of error ▪ Handles information with known semantics ▪ Handles information without explicitly knowing semantics ▪ Interacts in formal digital means (e.g. commands, screens) with humans ▪ Interacts in natural language with humans Decide
- 7. ©2015 IBM Corporation7 Successful banks tend to have stronger capabilities in customer engagement, discovery of new ideas, and decision-making Engage DecideDiscover Outperformers are 43% more competent in customer engagement than underperformers 44% more outperformers are strong in decision making than underperformers 48% Outperformers 18% Underperformers 167% more outperformers make innovation a major priority than underperformers Source: IBM Institute for Business Value Cognitive Computing Survey (Q4, Q7, Q12) 2015, Cross-industry data. See speaker notes for outperformer and underperformer definition 60% Outperformers 42% Underperformers 62% Outperformers 43% Underperformers
- 8. ©2015 IBM Corporation8 Cognitive can be easily applied to many functional areas of the bank complex workflows, ecosystem partners, unstructured data ▪ Loan origination ▪ Trade finance ▪ Financial supply ▪ Account opening COLLABORATE ▪ Help desk ▪ Contact centre ▪ Inquiry transactions ▪ Maintenance transactions ▪ Loan close and fulfilment AUTOMATE ▪ Product development ▪ Marketing ▪ Customer lifetime value ▪ Product profitability ▪ Business intrinsic value INNOVATE ▪ Financial advice ▪ Retirement planning ▪ Trading support ▪ Fraud detection ▪ Underwriting ▪ Compliance ▪ Client prospecting ▪ Product management AUGMENT simple workflows, single end user structured data routine, predictable, fact finding expert, knowledge intensive, judgment based Engagement complexity Advice complexity
- 9. ©2015 IBM Corporation9 A leading financial services group in Asia helps relationship managers in providing higher quality, bespoke investment advice to customers Cognitive enables relationship managers to gain relevant market and client insights through analysis of structured and unstructured data, and through interaction in conversational language A leading financial services group in Asia operating in 15 countries, wanted to enable relationship managers to provide better quality investment advice to clients Relationship managers are able to offer improved, bespoke service and investment advice to affluent clients BENEFITSOLUTIONNEED Engage Source: IBM case study Now
- 10. ©2015 IBM Corporation10 A large European bank uses cognitive to gain insights into institutional client behavior to predict future transactions Discover Bank identified business functions to apply cognitive, such as sales, trading, and risk management. Insights were sought on competitor and institutional client behavior, trading patterns and external data Bank wanted to invest in a technological capability that would provide a competitive edge Fund managers have better understanding of market sentiment real time and are better able to time their transactions in the financial markets BENEFITSOLUTIONNEED Source: IBM case study Now
- 11. ©2015 IBM Corporation11 One of the world’s largest banks employ cognitive to help mass market customers at call centers select higher value investments Decide Source: IBM case study Bank implements cognitive at its call center as many mass market customers do not understand what alternative investment options they have other than cash deposits One of the world’s largest banks wanted to help its call center mass market customers decide to invest in higher value assets instead of retaining cash deposits BENEFITSOLUTIONNEED Cognitive provides customers with answers to their questions about investments and dialogues with customers to reassure them about their investment options Now
- 12. ©2015 IBM Corporation12 Banks will provide better financial advice more widely through cognitive, with minimal human intervention (automatic-advisors) Tom, branch manager of retail bank XYZ, has dealt with thousands of banking customers over the years Allan, 28 year old, recently joined a technology company on an average income Allan wants his bank to understand his financial needs at his time in life Millennial such as Allan can service himself and digitally engage by having meaningful dialogue about their financial needs with cognitive system-based virtual relationship managers (automatic-advisors) Cognitive solution Cognitive expert system can enable bankers to understand retail customer’s financial needs and answer customer queries in natural language Retail banking Near Future Tom wants to provide a seamless omni- channel and personalized experience to all customer segments Tom can use cognitive to draw insights about his customers from internal and external structured and unstructured data to provide a seamless experience
- 13. ©2015 IBM Corporation13 Banks will use cognitive to provide better portfolio management online Jim, a senior advisor of private wealth advisory group of ABC bank manages a portfolio of fifty HNWI customers Amaira, a 32 year old single mother salaried with an annual income of $200K Amaira intends to save a large retirement fund and an education fund for her daughter. She calls her financial advisor, Jim, to advise on her current portfolio Cognitive can enable Amaira to manage and increase her wealth to improve her lifestyle and health (wellness) Cognitive solution Near Future Jim needs to provide expert and customized advice to Amaira Jim can use cognitive to know Amaira’s risk appetite by matching her personality type, enabling Jim to understand the volatility of portfolio and develop a range of scenarios to predict likely returns and in turn recommend best advice Wealth management Cognitive solution can enable wealth advisors to provide expert and unbiased advice on client’s investment portfolio based on each client’s unique financial requirements
- 14. ©2015 IBM Corporation14 Banks use cognitive to better manage credit risk on loans and money market instruments ▪ Estimating default probability despite healthy track record in repayment of loans ▪ Estimating and mitigating credit risk associated with money market instruments due to issuer default Risk management – credit risk Current challenges for banks Cognitive transformation Enables banks to mitigate credit risk through more accurate calculation of default rates in new and existing loans by: ▪ Complete analysis of complex data available internally of similar customer profiles and loan portfolios ▪ Predicting customer behavior towards loan repayment through insights from loan history and other unstructured data ▪ Providing better understanding of portfolio composition Allows banks to reduce credit risk associated with money market instruments by analyzing both structured and unstructured data on counterparty data (security issuer, credit rating agency etc.) Enables more robust view on the credit quality of security and credibility of the issuer . Near Future
- 15. ©2015 IBM Corporation15 Banks can use cognitive computing to identify complex early-stage fraud through context-based research ▪ Prevention and solution of variety of fraud cases across multi- product, multi-geographical dimensions, multi-channel usage ▪ Identification of new patterns of fraud and creation of mitigation plans Risk management - fraud Current challenges for banks Cognitive transformation Enables banks to detect frauds through pattern recognition and self learning mechanisms that can identify and predict fraudulent transaction more accurately Allows banks to assess potential threats through insights into current attack trends, case-studies and scenarios from other bank and geographies Helps identify relationships and cross-reference fraudulent activities in other locations and organizations Near Future
- 16. ©2015 IBM Corporation16 Banks can use cognitive to manage debt collections and better monitor collateralized assets ▪ Monitoring collateral of mortgaged loans on an ongoing basis ▪ Managing debt collection process with minimal delinquencies, costs and loss of customers Complex transactions processing - mortgages/collections Current challenges for banks Cognitive transformation Enables banks to monitor collateralized assets efficiently by: ▪ Calculating the exact volatility of portfolio and assets ▪ Establishing relationships between the value of fixed assets and market movements ▪ Predicting the timing of reviews Enables banks to take effective decisions in debt recovery and collections by: ▪ Broadening customer risk segmentation criteria beyond days passed due, to include other useful customer insights through analysis of unstructured data ▪ Providing more detailed analysis of the structure and risks on loan portfolios Near Future
- 17. ©2015 IBM Corporation17 Three critical success factors emerge for cognitive computing pioneers Lay the foundation Manage the changeDefine the value 1 2 3 Find the right opportunities for cognitive Define the value proposition and chart a course for cognitive Be realistic about value realization Invest in specialist human talent Build and ensure a quality data corpus Consider impacts, business processes, and policy requirements Ensure executive involvement along the cognitive journey Communicate the cognitive vision at all levels Continue to raise the cognitive IQ level of the organization
- 18. ©2015 IBM Corporation18 For more information about cognitive computing on Banking & Financial Markets IBM Institute for Business Value Gianpaolo Zampol Business Development Executive Financial Services Sector gianpaolozampol @gzampol gzampol