# UK PM Sunak to announce more ‘proportionate’ climate response
Author:  Pal Sinha, Barnali 
Author URL: https://financedigest.com/author/pal-sinha-barnali
Published: 2020-11-12
Category: TECHNOLOGY
Category URL: https://financedigest.com/category/technology
Meta Title: UK PM Sunak Delays Green Policies in Climate Response Speech
Meta Description: British Prime Minister Rishi Sunak will give a speech this week to adjust net zero emissions goals for a more balanced approach amidst global climate change
URL: https://financedigest.com/uk-pm-sunak-to-announce-more-proportionate-climate-response-2html

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_By **Kris Sharma,** Financial Services Lead, Canonical – the publisher of_ [_Ubuntu_](https://ubuntu.com/)

Artificial intelligence (AI) has assumed a growing influence within financial services in recent years, affecting areas such as credit decisions, risk management, fraud detection, and stress testing. And for many fintechs, it has been baked into the process from the outset, to the extent that usage of AI in the fintech market registered [$6 billion in 2019 and is expected to reach $22 billion by 2025](https://www.mordorintelligence.com/industry-reports/ai-in-fintech-market).

Economic fallout from the pandemic, however, has accelerated the timetable for financial services firms to become mass adopters of AI and harness its predictive powers sooner rather than later. For digitally native fintechs, many of which have already embraced AI and its capabilities, this offers the opportunity to invest further in the technology and capitalise on the tools available to accelerate their journeys.

Fintechs across the world are dealing with the effects of [Covid-19 and face an uphill challenge in containing the impact of it on the financial system](https://www.financedigest.com/covid-19-impact-on-attitude-and-heading-reference-systems-market-volume-analysis-future-prediction-industry-overview-and-forecast-2028.html "Covid-19 Impact On Attitude and Heading Reference Systems Market | Volume, Analysis, Future Prediction, Industry Overview And Forecast 2028") and broader economy. With [rising unemployment](https://www.financedigest.com/u-s-job-growth-picks-up-in-june-unemployment-rate-rises-to-5-9.html "U.S. job growth picks up in June; unemployment rate rises to 5.9%") and stagnated economies, individuals and companies are struggling with debt, while the world in general is awash in credit risk. This has pushed operational resilience to the top of fintech CXOs’ agendas, requiring them to focus on systemic risks while continuing to deliver [innovative digital](https://www.financedigest.com/the-hemoglobinopathy-market-to-get-digitally-innovative.html "The Hemoglobinopathy Market to get digitally innovative") services to customers.

To make matters worse, criminals are exploiting [vulnerabilities imposed by the shift to remote](https://www.financedigest.com/how-remote-hiring-could-leave-fintechs-vulnerable.html "How remote hiring could leave fintechs vulnerable") operations post-Covid-19, increasing the risk of fraud and cybercrime. For fintechs, building and maintaining robust defences has, therefore, become a [critical priority](https://www.financedigest.com/pm-rishi-sunak-sets-out-priorities-for-britain-responds-to-critics.html "PM Rishi Sunak sets out priorities for Britain, responds to critics"). Organisations around the globe are forging new [models](https://www.financedigest.com/gary-mcgaghey-explains-how-cfos-can-strengthen-decision-making-processes-and-reimagine-the-finance-model.html "Gary McGaghey Explains How CFOs Can Strengthen Decision-Making Processes and Reimagine the Finance Model") to combat financial crime in collaboration with governments, regulators, and even other fintechs.

The [technological advances in data analytics](https://www.financedigest.com/how-the-global-insurance-market-will-keep-pace-with-evolving-risks-through-data-analytics-and-technology.html "How the global insurance market will keep pace with evolving risks, through data, analytics and technology"), AI and machine learning (ML) have been driving fintechs’ response to the crisis, accelerating the automation journey many had already embarked on.

**A new direction**

Until recently, fintechs have used traditional methods of [data analysis](https://www.financedigest.com/comparative-analysis-of-the-best-data-room-providers.html "Comparative Analysis of the Best Data Room Providers") for various applications, including the detection of fraud and predicting defaults, that require complex and time-consuming investigations.  However, by enabling high frequency analytics across large volumes of [data sets](https://www.financedigest.com/byd-set-to-be-chinas-top-selling-car-brand-for-nov-tesla-gains-data.html "BYD set to be China’s top-selling car brand for Nov, Tesla gains -data") and using AI and ML, fintech firms will significantly increase the speed and accuracy of analysis.

![Kris Sharma](https://prod.superblogcdn.com/site_cuid_cm5qst7v3003gwirgwqtxn8i8/images/kris-sharma-450x352-1737287554236-compressed.jpg)

Kris Sharma

The fintech industry, as a whole, can also capitalise on the huge volumes of data [sets already on record](https://www.financedigest.com/home-prices-are-setting-records-while-mortgage-rates-plunge-is-it-time-to-refinance.html "Home Prices Are Setting Records While Mortgage Rates Plunge – Is It Time To Refinance?"), from diverse sources across multiple business units, to train ML algorithms that can automate many of their processes and AI for operational resilience. The technology and [tools](https://ubuntu.com/kubeflow) for getting these capabilities into production keep improving and becoming more accessible to users beyond data scientists and AI experts, enabling fintechs to speed up technological adoption.

[Kubeflow,](https://www.kubeflow.org/) for example, an open source tool created to orchestrate AL and ML workflows running on Kubernetes, is one such solution – simple, portable, and scalable. It is ideally suited to [TensorFlow](https://www.tensorflow.org/), a comprehensive ecosystem of tools, libraries and community resources that lets developers easily build and deploy ML applications.

Additionally, [Apache Kafka](https://kafka.apache.org/), an open-source distributed event streaming platform, can deliver seamless communication at a fast pace, thus enabling rapid analysis of quantitative data to compute the value of risk in real-time. AI and ML in mission-critical, real-time applications, such as detecting financial fraud by correlating [payment information with other historical data](https://www.financedigest.com/understanding-the-realities-of-payment-data-monetisation.html "Understanding the realities of payment data monetisation") or known patterns, can leverage Apache Kafka as a scalable and reliable central nervous system for enterprise data.

As with any application running at scale, Apache Kafka requires a significant amount of preparation and customisation on the network, hardware, OS, and at the application level. Maintaining a large deployment can be complex and requires constant monitoring and maintenance. Offloading the complexity of managing Apache Kafka to a third-party [technology partner](https://ubuntu.com/managed) would enable financial institutions to focus on innovation and business priorities rather than spending significant effort and resources on managing infrastructure.

With so much uncertainty in the industry arising from Covid-19 and Brexit, the availability of [open source tools and partners allows fintech](https://www.financedigest.com/the-future-of-fintech-and-open-source-cloud-solutions-in-the-united-kingdom.html "The future of fintech and open source cloud solutions in the United Kingdom") firms to better deal with the effects, while at the same time enabling them to adapt and transform.

**The** [fintech future](https://www.financedigest.com/hyper-personalisation-the-future-for-fintechs.html "Hyper-personalisation – the future for fintechs")

AI and ML [solutions have the potential to transform how fintechs](https://www.financedigest.com/why-a-liberated-cfo-and-fintech-solution-are-a-dream-partnership-for-navigating-economic-uncertainty.html "Why a liberated CFO and fintech solution are a dream partnership for navigating economic uncertainty") deal with regulatory compliance issues, financial fraud, and cybercrime. And by using customer data for greater personalisation, fintechs can continue to offer products and services tailored to individual [consumer needs](https://www.financedigest.com/money-orders-vs-checks-what-you-need-to-know-as-a-consumer.html "Money Orders vs Checks: What You Need to Know as a Consumer").

As yet, most financial institutions are unsure whether a [post-Brexit world will focus on gaining more overseas or UK-based customers](https://www.financedigest.com/uk-and-eu-reach-post-brexit-customs-deal-for-n-ireland-the-times.html "UK and EU reach post-Brexit customs deal for N.Ireland-The Times"). With a data-driven approach, fintechs can see where the opportunities lie and fintechs have only just [scratched the surface](https://www.financedigest.com/explainer-western-sanctions-on-banks-only-scratch-surface-of-fortress-russia.html "Explainer-Western sanctions on banks only scratch surface of Fortress Russia") of data analytics. But as the Covid-19 crisis continues and Brexit uncertainty once again moves up the agenda, moving to a data-first [approach will become](https://www.financedigest.com/intuitive-decision-making-could-this-approach-be-the-most-underrated-way-to-becoming-a-successful-leader.html "Intuitive decision making: could this approach be the most underrated way to becoming a successful leader?") less of a choice and more of a necessity.

During this time of economic disruption that has deep implications for the financial [sector](https://www.financedigest.com/the-technologies-set-to-boost-the-finance-sector-in-2022.html "The technologies set to boost the finance sector in 2022"), fintechs need to make AI and ML a core part of their transformation effort to adjust to the new normal, and take advantage of the enabling technologies that can propel adoption more quickly and more efficiently.


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