Session 2B Application of Robotic Process Automation on Actuarial Function. Pu Sheng, FSA

Transcription

1 Session 2B Application of Robotic Process Automation on Actuarial Function Pu Sheng, FSA

2 The SOA Asia-Pacific Annual Symposium 6-7, July 2017 Robotic Process Automation Application for Insurers 2

3 About speakers Paul Sheng, Associate Director Paul is an Associate director of ASEAN Actuarial Service. He leads EY s Actuarial Modelling practice. He has over 12 years experiences and served clients around transactions, financial reporting and actuarial modelling. He is a Fellow of the Society of Actuaries. Paul configured the first Prophet robotic process demo. Insurers are struggling with the current state Most departments are facing increasing demands from key internal (CFO, CRO, CEO, Head Office) and external (regulators, auditors, standard setters) stakeholders and are looking for ways to increase efficiency of their operations. 1 Fast Close 4 New Regulations and Requirements 2 Accuracy Value Added 3 Analysis 5 HR Retention 6 Disruption Solution: Optimize Life Operational Processes using automation and process reengineering on existing processes, to improve control and free up scarce resources to focus on more value adding requirements 4

4 Current and Ideal Time Spend Actuaries and accountants are highly skilled, costly resources whose main value add is to provide Analysis, and to bring insights into the business performance of insurance companies. However, current life operational functions are struggling under a divulge of new regulations and requirements, and diverting resources to running processes using various actuarial tools. As such, up to 70% of actuarial team members time can be spent on process related work this is neither Economical, Efficient nor Effective. How can we move towards a more efficient and analytical actuarial function? Heads of department Managers Process (70%) Analysis (30%) Analysts Process (30%) Analysis (70%) Current Ideal Process Optimization could aim, for example, to shift actuarial time/effort spend from the Current to the Ideal phase 5 Robotic Process Automation is the use of software that mimics the way that people carry out repetitive administration tasks Software that mimics human interaction with core systems, web, and desktop applications to execute processes Robots are a virtual workforce controlled by the business operations teams Dramatically reduce costs, whilst improving service levels, data quality and reducing risk Software Robots sit alongside existing infrastructure, governed and controlled by IT Automated solution can work 24/7 1/3 of the cost of offshore FTE Double-digit reduction in error rates Robotic Process Automation Software Robots work with existing IT landscape Robots can be trained by business users Cuts data entry costs by up to 70% Robots and People a powerful combination Robots deliver repetitive, deterministic, high-volume tasks efficiently People build relationships, provide subjective judgement, deliver low-frequency and exception tasks, and manage change and improvement Business friendly, non-disruptive, code-free 6

5 RPA software is designed to allow trained operations staff to automate and control their processes, using an IT supported platform Key Features of RPA software Software must include the following features to be considered RPA : User Interface Focussed: Accesses existing applications via user interfaces, with advanced tools to facilitate integration and intelligence to minimise impact of core system change Scheduling & Monitoring: Can run 24x7 in a data-centre with performance and incident monitoring, flexible scheduling options Business User Friendly: 100% visual, with little or no coding or macro language Full Audit History: including process definitions, and each task processed Full Security: including fully secured credential management Fully Scalable: including support for virtual and commodity physical infrastructure to run thousands of processes Process Design Process are defined using drag-and-drop, much like Visio. Screenshots taken using Blueprism Software. Blueprism logo used by permission of Blue Prism Ltd, all rights reserved. Implementing Actions and Logic You then click into each object to define logic (e.g. formulas) or capture events (e.g. arrival of s). Screen interactions are easy to capture using a set of spy tools for reading screens, entering data, selecting options and pushing buttons. Objects can be re-used for efficiency. 7 Robotic Process Automation bridges the gap between desktop/human solutions, and (expensive) core IT platforms Process Value / volume ERP, CRM Process Spectrum ERP Customization / Integration / BPMS Robotic Process Automation People / Excel / Lean Frequency of change Key areas of focus for RPA: Multi-system / legacy system processes Processes which evolve regularly Processes linked to future roadmap states more that 6 months out Urgent regulatory or priority change Manual processes requiring enhanced control, MI, or improved SLAs Processes involving Excel, Access, PDF tools, or production of PDF reports Test and Learn approach to new propositions or requirements RPA presents a different approach to a traditional IT Integration or BPO solution. The key success factors are: Business Engagement to drive pace and depth of adoption by business lines and functions building the trust in the RPA capability to motivate process owners to drive automation Speed of automation: the shorter the lifecycle, the larger scope of processes which can be automated Cost of business analysis activities: exploring, standardising, modifying and testing processes 8

6 There are three tiers of Robotic Process Automation Rules-driven Robot Easy to implement using core platforms, Web or Robotic Process Automation: Fast to define and implement, typically with a significant ROI Rules can be built into RPA software, or linked to natural language rules engine Typically targets back-office automation, with limited paper or un-structured data requirements Semi-Cognitive Robot Apply statistical models or machine learning to a very specific task, e.g. comparing signatures, categorising letters, processing speech: Implemented by linking Robotics to an Analytics/Specialist tool Model risk management and compliance required, but straight forward as the models are simple to explain with predictable impact on outcomes. True Cognitive / Optimised Machine Learning Robot This is where the Cognitive Robot uses a Machine Learning or statistical modelling approach to understanding a need and optimising the required action Key task is understand regulatory (and ethical) considerations at play in the decision, and to understand how to implement these in a Learning Algorithm (coding the Moral Compass ) 8 Live demos 10

7 How RPA helps on operational functions of an insurance company Start with looking at how your teams are deployed. Where are resources manually accessing and gathering data from several different applications to complete their activities? manually moving data from one system to another? manually checking the consistency of data between multiple systems? manually updating the same information in multiple systems? waiting for alerts/events to initiate their activities? manually remediating data across several accounts? Example areas being explored (Insurance) Customer on-boarding / KYC Customer management Policy Administration Claims Administration Payments Processing Recoveries Client reporting Digital Transformation Data Migration Interim support to core platform Development roadmap Finance, including regulatory reporting 11 Qualitative benefits expected from RPA include increased control, accuracy and productivity Accuracy The right result, decision or calculation the first time) Elasticity / Flexibility Instant ramp up/down to deal with spikes and troughs in demand Consistency Identical process and tasks reducing the output variation Staff retention Allows focus shift towards more stimulating tasks Audit trail Fully maintained logs essential for compliance Reliability 24/7, all year around, full availability Productivity Freeing up manual resources for more value-added tasks Right shoring Geographical independence allows right shoring a viable alternative to offshoring Low risk - non-invasive technology Can be overlaid on existing systems allowing creation of a platform to introduce more sophisticated algorithms and machine-learning tools 12

8 There are five key areas to address for success Stakeholder Incentives & Engagement Clear communication of the value and potential for RPA at all levels Articulation of RPA potential in the context of broader Automation technology and Operational Excellence agenda Effective change management tools and deployment methods to secure commitment to success Process Prioritisation Leverage enterprise process taxonomies and standards where they exist Develop complexity framework for testing deployment priorities by business area Secure early buy-in from business / process owners to ratify business case and benefit targets Robust and Agile Operating Model Plan for lack of existing process documentation, and lack of clarity over what the standardised process should be this is common Avoid-over analysis of low volume exception paths Automate core process flows, and add further exception paths over time subject to business case Build a strong IT collaboration to facilitate support for core platform test environments and support for the RPA and Digital platforms themselves Build a flexible governance and testing process that can be flexed to support both low-risk (e.g. internal MI) and higher risk (e.g. online customer) process automations Promote clear capacity management of robots, and Task management for processing teams Business & IT Accountability Business led deployments, respectful of IT governance protocol and Compliance and Service Management requirements Clear definition of business and IT roles across during process prioritisation, deployment planning and execution Benefit Realisation Segregation of benefits tracking for cost-reduction, propositional change, and compliance Tightly manage capacity release, to ensure savings are realised rather than simply reinvested by default into quality or propositional enhancement Plan for commercial negotiation where benefit release impacts existing outsource contracts 12 The most successful approach is to build a business-led, IT Supported Operating Model We recommend creation of a centre-of-excellence (CoE) to embed RPA within strategy, business planning and execution. Conceptual CoE Operating Model Real Example (Certified by Vendor) 13

9 Q & A 15