PPS: Managing risk with machine learning, AI, and Google Cloud
About PPS
Founded in 1941, PPS is the largest financial services company in South Africa that still embraces an ethos of mutuality, which means that it exists solely for the benefit of its members.
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About Siatik Systems
Siatik Systems is a leading Google Cloud solutions provider in South Africa, delivering consultancy and bespoke software engineering in the public and private sectors.
PPS uses TensorFlow and Google Cloud ML to transform from a traditional insurance broker into a modern, digital provider with cutting-edge AI and machine learning technology at its core.
Google Cloud results
- Uses AI to recommend products to 200,000 members based on their individual preferences and history
- Runs 70% faster than on-premises infrastructure with fewer resources
- Adds flexibility to strategic goals with manageable operational expenditure flows instead of intermittent, large capital outlays
Improved sales by 5% with AI recommendation platform
For a business to succeed in the long term, it needs to learn not just to adapt to inevitable change, but to harness it. South Africa-based PPS has been an insurance company since 1941 and today is the biggest mutual insurance provider in the country. As a mutual company, PPS is owned by more than 200,000 members, making them shareholders. In recent years, PPS and other companies like it have been affected by a number of external factors. "For one thing, technology platforms have brought in a new gig economy that has all kinds of implications for insurance," says Avsharn Bachoo, CTO at PPS. "What we've been seeing is basically a disruption of the South African insurance industry. We chose to see that as an opportunity."
"Our servers were at the end of their life cycle and we had to decide whether to refresh them or switch completely. To embrace the world of AI and machine learning effectively, we knew we needed a cloud-based infrastructure. We've found the answer in Google Cloud."
—Avsharn Bachoo, CTO, PPSIn early 2018, faced with an uncertain economic environment that was squeezing growth and profitability, PPS decided to transform itself from a traditional broker-based business into a digital insurance provider. A key pillar of this new strategy was to overhaul the company's technology infrastructure. To turn the strategy into reality, Avsharn and his team chose Google Cloud.
"Our servers were at the end of their life cycle and we had to decide whether to refresh them or switch completely," says Avsharn. "To embrace the world of AI and machine learning (ML) effectively, we knew we needed a cloud-based infrastructure. We've found the answer in Google Cloud."
Power, speed, flexibility with Google Cloud
Previously, PPS maintained an on-premises IT infrastructure, which worked for its traditional business but was unsuited for its new way of working. In early 2018, the company started working on new products for its members but this required large amounts of compute power that proved prohibitively expensive with on-premises servers. Even existing products were starting to require more than the infrastructure could deliver. Aging equipment meant that it's testing and quality assurance environments bore little resemblance to the actual production environment.
"We had no pre-production environments at all," says Avsharn, resulting in more work for developers after products had been released. Meanwhile, the capital required to buy and configure more servers for new projects meant fewer resources available for innovation, and left the company less able to react to changes in the market. PPS knew it had to find a cloud-based alternative.
Shortly after devising a new digital strategy, PPS engineers attended a training session on cloud infrastructure given by leading South African Google Cloud Siatik. Impressed with the presentation, PPS engaged Siatik to help run a proof of concept for a cloud-based infrastructure, running on Google Cloud. With on-site engineers and constant communication, Siatik formed a very close working relationship with PPS. "The team at Siatik was exemplary," recalls Avsharn. "They were well-organized, with cutting-edge technical acumen and very creative solutions to our problems. They were real game-changers."
"We wanted the platform to retrain its models in response to new data and improve its recommendations with more information. Normally this would be a manual process but Google Cloud ML Engine lets the models do this automatically."
—Kimoon Kim, Lead Solution Architect and Data Engineer, SiatikThe proof of concept was successful, with Google Cloud outperforming the existing infrastructure in terms of how it handled compute demands, databases, and storage. "It's the speed of Google Cloud that really impresses us," says Avsharn. PPS saw that Google Cloud wasn't just an opportunity to migrate its existing infrastructure to the cloud. With Siatik's help, it redesigned its monolithic core architecture to one based around microservices using Google Kubernetes Engine (GKE). For data processing and storage, Cloud Dataflow and Cloud Datastore proved invaluable, while Stackdriver helped the IT team stay on top of logging and monitoring the system. "Google Cloud makes migrations very easy," says Brett St. Clair, CEO at Siatik. "It takes care of all the hard work with configurations and replications, so when we switch the machines on, everything is ready and working."
The ease with which PPS migrated to Google Cloud means that it can now tackle strategic goals much more quickly than before. The most ambitious of these is an AI-powered product recommendation platform. Information is collected from customers who opt in at a defined point in their journey, this database is queried using BigQuery, and the information is fed into the platform. The AI model then calculates the most appropriate products for each member, according to their personal history. "Most of the product recommendation engines out there are based on clustering, where you're offered products based on your peer groups," explains Avsharn. "For the first time, we can make recommendations to members based on their individual preferences and historical behavior. That's really powerful for us."
Siatik helped PPS use TensorFlow and Cloud Machine Learning Engine to build the AI platform. For the engineers, these easy-to-use tools helped speed up the process considerably, allowing them to host the models locally without any fuss. Previously, it took one to three months to manually build the model and match an offer to a customer. With the AI platform, a match takes just a few minutes. Cloud ML Engine, in particular, helped the platform adapt to new information on the fly and easily make adjustments to its hyperparameters, that is, preset variables which define the model-training process.
"We wanted the platform to retrain its models in response to new data and improve its recommendations with more information," says Kimoon Kim, Lead Solution Architect and Data Engineer at Siatik. "Normally this would be a manual process but Google Cloud ML Engine lets the models do this automatically."
"Google Cloud helped us cancel out a lot of the noise around machine learning and AI. We don't have to build new complicated algorithms or hire huge teams of data scientists to benefit. We just bring our data and use the right tools to focus on what's really important."
—Avsharn Bachoo, CTO, PPSHarnessing artificial intelligence for real-world results
PPS deployed its new AI recommendation platform in December, 2018. Just a couple of months later, its impact was clear. "In around eight weeks, we saw a 5 percent growth in sales," says Avsharn. "It's been a direct result of building our recommendation platform with Google Cloud. We can offer the right products to the right members."
For developers and engineers at PPS, working with Google Cloud gives them access to high performance technology and automation options with GKE. As a result, the infrastructure runs 70 percent faster than before with fewer cores and less memory. Developers can also work in mature testing environments, and for the first time, are able to build pre-production environments, leading to better quality products. More strategically, moving to a serverless, cloud-based infrastructure has helped PPS take control of its budget, moving away from intermittent, large capital spends to more manageable, project-to-project flows of operational expenditure. The company expects to see savings of around 50 percent, or $695,000.
"We have a lot more flexibility with our resources thanks to Google Cloud," says Avsharn. "When we have a new idea, we don't have to outlay new capital such as servers before we can even start working on it. We just spin up instances when we want and spin them back down when we're done."
With the AI platform deployed and working well, PPS is already looking at ways to improve it, including real-time updates and further automation. Later this year, the company will integrate the platform with more sales campaigns for more effective targeting to boost sales even further. Meanwhile, it's also experimenting with machine learning to spot patterns in data at scale for fraud analytics and risk assessment.
For PPS, working with Google Cloud has helped it transform quickly and effectively from disrupted to disruptor. The company is now looking to gain the same transformative effects by implementing Google Workspace for increased productivity and collaboration.
"Google Cloud helped us cancel out a lot of the noise around machine learning and AI," says Avsharn. "We don't have to build new complicated algorithms or hire huge teams of data scientists to benefit. We just bring our data and use the right tools to focus on what's really important."
Tell us your challenge. We're here to help.
Contact us
About PPS
Founded in 1941, PPS is the largest financial services company in South Africa that still embraces an ethos of mutuality, which means that it exists solely for the benefit of its members.
About Siatik Systems
Siatik Systems is a leading Google Cloud solutions provider in South Africa, delivering consultancy and bespoke software engineering in the public and private sectors.