RPA stands for "Robotic Process Automation" and is already improving productivity by utilising machine learning, AI et al to automate the processing of repetitive processes. More than that, algorithms can apply business rules to select best options, to accept applications and diagnose situations.
Where the past predicates the future, where patterns follow a normal profile this can be accurate. Where the opposite is the case RPA may fall down.
The optimal solution lets RPA automate the repetitive processes and identify the abnormal and fast changing process for human intervention i.e. the human brain to apply its cognitive powers.
Taking the insurance industry, this helps identify fraud as criminals tend to repeat the same (previously successful) tactics. They use the same road junctions and roundabouts to trick unwary drivers into collisions and then claim whiplash injuries.
The use of location intelligence can help by linking such locations with individuals, solicitors, dates. previous claims. You would think insurance companies would do this today but few actually analyse specific location data effectively.
I have been impressed by the productivity increases achieved by insurtech innovators like 360Globalnet that digitally transform insurance claims processes
Combine this with location intelligence solutions likes those from Carto and you can unearth far more insight from location data and predict spatial relationships better.
This brings me, as often, to analytics; often touted as an end in itself it too often sits in an enterprise silo delivering insights but not the better decision execution that leads to real productivity improvements. To do that analytics must be embedded within the processes that RPA automates. Must be integrated with the legacy systems that underpay the insurance claims processing applications of large enterprises AND with the new cloud platform from 360Globalnet et al.
Purpose-built analytics available to the full continuum of employees that need the contextual insights to manage their tasks and those of their teams. Transparent visibility of the past, current and future status of:-
- Claimants & customers
- The full loop of the claims process from beginning to end
- Managing the supply chain of inspectors, contractors, repairers, vehicle hire etc
- Taking out waste and increasing service
That is why it is rare that one solution provider can deliver all that is required, even in a narrow need such as analytics.
Digital transformation in reality.
The robots are coming RPA is part of the spectrum of emerging artificial intelligence tools, including virtual agents, machine learning, computer vision and natural language classification. The move to artificial intelligence technologies can have many applications in insurance, for example, image classification for claims and text analytics for servicing customer inquiries. 2: Scaling the workforce Properly implemented, automation programs enable the scalable, flexible and responsive insurance workforce that is so essential in a digital marketplace. Freed from routine process activities by their new automated co-workers, back-office staff can be redeployed into front-office roles where they can focus on complex customer demands and help generate growth. 3: Pilots prove the business case RPA pilots have demonstrated a 40-80 percent reduction in processing times, along with improvements in quality, auditability and risk management.