7 February 2017
Avoiding Pitfalls when Implementing Machine Learning and Blockchain in Insurance
By Cliff Moyce
Cliff Moyce, Global Head of the Finance Practice at DataArt, contributes an article to Insurance Innovation Reporter where he explores use cases for machine learning and blockchain technologies in insurance and offers advice for their effective implementation.
“Top tips for adopting ML:
- Start small—but do start.
- Success of ML depends on an insurer’s ability to provide enough valid data to “train” the software.
- Partnerships are important.
- Diversify. Avoid betting the farm on a single ML approach or technology.
- Use Cloud based/SaaS/on-demand solutions from partners, plus open-source tools.
Top tips for implementing Blockchain:
- Find a small problem and improve the process that is running behind it.
- Use private Blockchains such as Chain.com and Hyperledger for improved peace of mind.
- Blockchain is a distributed network of trust, so consider looking for partners that share the same goals.
- Blockchain experts are rare and hard to employ, but it is crucial that you have a knowledgeable expert in your team.”